Lung Cancer

Researchers studying a large set of small cell lung cancer (SCLC) tumor samples have identified four SCLC subtypes, and they propose that matching baseline tumor subtypes to SCLC therapy may enhance the depth and duration of response.

Carl M. Gay, MD, PhD, of University of Texas MD Anderson Cancer Center in Houston, and colleagues conducted this research and described their findings in Cancer Cell.

The authors noted that survival rates in SCLC remain dismal despite recent modest gains in progression-free survival and overall survival achieved through adding immunotherapy to platinum-based frontline chemotherapy.

Based on transcription factors indicating which genes are activated, prior research had already identified three possible SCLC subtypes. Many SCLC tumors, however, do not fit into one of these three groups, the authors said.
 

Inflamed gene signature

The four groups were identified using tumor expression data and nonnegative matrix factorization from published sources on 81 SCLC patients, and then validated via the largest SCLC data set available (276 SCLC patients enrolled in the phase 3 IMpower133 trial).

The SCLC subtypes were defined largely by differential expression of transcription factors – subtype SCLC-A by ASCL1, subtype SCLC-N by NEUROD1, and subtype SCLC-P by POU2F3. The fourth subtype, SCLC-I, is characterized by low expression of all three transcription factor signatures and an inflamed gene signature with a high expression of multiple immune genes, including significantly greater levels of genes indicating the presence of CD8-positive cytotoxic T cells.

Because each subtype demonstrates unique vulnerability to investigational therapies, this subtype classification has significant clinical implications.

“We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients,” the authors stated.

“Our paper shows that the inflamed group has a distinct biology and environment and tends to be more responsive to immunotherapy,” study author Lauren Averett Byers, MD, also of the University of Texas MD Anderson Cancer Center, stated in a press release. “Identifying the inflamed group is very important because, so far, there have not been any validated biomarkers for small cell lung cancer that predict which patients get the most benefit from immunotherapy.”

In samples from the other three subtypes, SCLC-A was most responsive to BCL2 inhibitors, SCLC-N to Aurora kinase inhibitors, and SCLC-P to PARP inhibitors.

Treatment resistance

The tendency of SCLC to develop treatment resistance, even after an initial response, is a known challenge. Using single-cell RNA sequencing to evaluate tumor evolution, the authors observed a tendency of SCLC-A to switch to SCLC-I after chemotherapy treatment, a possible contributor to treatment resistance.

It will be necessary to verify the study findings through further investigations, particularly regarding the therapeutic vulnerabilities for each group.

“Now we can develop more effective strategies for each group in clinical trials, taking into account that they each have different biology and optimal drug targets,” Dr. Byers said. “As a field, small cell lung cancer is about 15 years behind non–small cell lung cancer’s renaissance of biomarkers and personalized therapies. This represents a huge step in understanding which drugs work best for which patients and gives us a path forward for personalized approaches for small cell lung cancer.”

“Dr. Gay’s work is the latest in a growing series of exciting studies demonstrating the utility of defining subtypes of small cell lung cancer based on expression of master transcriptional regulators,” commented Charles Rudin, MD, PhD, of Memorial Sloan Kettering Cancer Center in New York, in an interview.

He added, “While tumors can evolve between some of these categories, the dominant subtype assignment influences therapeutic vulnerabilities. It is an exciting time for those of us engaged in small cell research. Subtyping should help guide more focused and successful clinical trials for patients with small cell lung cancer.”

The authors disclosed multiple relationships with companies. The study was supported by the National Institutes of Health/National Cancer Institute, the University of Texas Southwestern and MD Anderson Cancer Center, and a variety of other governmental and nonprofit groups. Dr. Rudin is principal investigator of the NCI small cell lung cancer research consortium.

Researchers studying a large set of small cell lung cancer (SCLC) tumor samples have identified four SCLC subtypes, and they propose that matching baseline tumor subtypes to SCLC therapy may enhance the depth and duration of response.

Carl M. Gay, MD, PhD, of University of Texas MD Anderson Cancer Center in Houston, and colleagues conducted this research and described their findings in Cancer Cell.

The authors noted that survival rates in SCLC remain dismal despite recent modest gains in progression-free survival and overall survival achieved through adding immunotherapy to platinum-based frontline chemotherapy.

Based on transcription factors indicating which genes are activated, prior research had already identified three possible SCLC subtypes. Many SCLC tumors, however, do not fit into one of these three groups, the authors said.
 

Inflamed gene signature

The four groups were identified using tumor expression data and nonnegative matrix factorization from published sources on 81 SCLC patients, and then validated via the largest SCLC data set available (276 SCLC patients enrolled in the phase 3 IMpower133 trial).

The SCLC subtypes were defined largely by differential expression of transcription factors – subtype SCLC-A by ASCL1, subtype SCLC-N by NEUROD1, and subtype SCLC-P by POU2F3. The fourth subtype, SCLC-I, is characterized by low expression of all three transcription factor signatures and an inflamed gene signature with a high expression of multiple immune genes, including significantly greater levels of genes indicating the presence of CD8-positive cytotoxic T cells.

Because each subtype demonstrates unique vulnerability to investigational therapies, this subtype classification has significant clinical implications.

“We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients,” the authors stated.

“Our paper shows that the inflamed group has a distinct biology and environment and tends to be more responsive to immunotherapy,” study author Lauren Averett Byers, MD, also of the University of Texas MD Anderson Cancer Center, stated in a press release. “Identifying the inflamed group is very important because, so far, there have not been any validated biomarkers for small cell lung cancer that predict which patients get the most benefit from immunotherapy.”

In samples from the other three subtypes, SCLC-A was most responsive to BCL2 inhibitors, SCLC-N to Aurora kinase inhibitors, and SCLC-P to PARP inhibitors.

Treatment resistance

The tendency of SCLC to develop treatment resistance, even after an initial response, is a known challenge. Using single-cell RNA sequencing to evaluate tumor evolution, the authors observed a tendency of SCLC-A to switch to SCLC-I after chemotherapy treatment, a possible contributor to treatment resistance.

It will be necessary to verify the study findings through further investigations, particularly regarding the therapeutic vulnerabilities for each group.

“Now we can develop more effective strategies for each group in clinical trials, taking into account that they each have different biology and optimal drug targets,” Dr. Byers said. “As a field, small cell lung cancer is about 15 years behind non–small cell lung cancer’s renaissance of biomarkers and personalized therapies. This represents a huge step in understanding which drugs work best for which patients and gives us a path forward for personalized approaches for small cell lung cancer.”

“Dr. Gay’s work is the latest in a growing series of exciting studies demonstrating the utility of defining subtypes of small cell lung cancer based on expression of master transcriptional regulators,” commented Charles Rudin, MD, PhD, of Memorial Sloan Kettering Cancer Center in New York, in an interview.

He added, “While tumors can evolve between some of these categories, the dominant subtype assignment influences therapeutic vulnerabilities. It is an exciting time for those of us engaged in small cell research. Subtyping should help guide more focused and successful clinical trials for patients with small cell lung cancer.”

The authors disclosed multiple relationships with companies. The study was supported by the National Institutes of Health/National Cancer Institute, the University of Texas Southwestern and MD Anderson Cancer Center, and a variety of other governmental and nonprofit groups. Dr. Rudin is principal investigator of the NCI small cell lung cancer research consortium.

Researchers studying a large set of small cell lung cancer (SCLC) tumor samples have identified four SCLC subtypes, and they propose that matching baseline tumor subtypes to SCLC therapy may enhance the depth and duration of response.

Carl M. Gay, MD, PhD, of University of Texas MD Anderson Cancer Center in Houston, and colleagues conducted this research and described their findings in Cancer Cell.

The authors noted that survival rates in SCLC remain dismal despite recent modest gains in progression-free survival and overall survival achieved through adding immunotherapy to platinum-based frontline chemotherapy.

Based on transcription factors indicating which genes are activated, prior research had already identified three possible SCLC subtypes. Many SCLC tumors, however, do not fit into one of these three groups, the authors said.
 

Inflamed gene signature

The four groups were identified using tumor expression data and nonnegative matrix factorization from published sources on 81 SCLC patients, and then validated via the largest SCLC data set available (276 SCLC patients enrolled in the phase 3 IMpower133 trial).

The SCLC subtypes were defined largely by differential expression of transcription factors – subtype SCLC-A by ASCL1, subtype SCLC-N by NEUROD1, and subtype SCLC-P by POU2F3. The fourth subtype, SCLC-I, is characterized by low expression of all three transcription factor signatures and an inflamed gene signature with a high expression of multiple immune genes, including significantly greater levels of genes indicating the presence of CD8-positive cytotoxic T cells.

Because each subtype demonstrates unique vulnerability to investigational therapies, this subtype classification has significant clinical implications.

“We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients,” the authors stated.

“Our paper shows that the inflamed group has a distinct biology and environment and tends to be more responsive to immunotherapy,” study author Lauren Averett Byers, MD, also of the University of Texas MD Anderson Cancer Center, stated in a press release. “Identifying the inflamed group is very important because, so far, there have not been any validated biomarkers for small cell lung cancer that predict which patients get the most benefit from immunotherapy.”

In samples from the other three subtypes, SCLC-A was most responsive to BCL2 inhibitors, SCLC-N to Aurora kinase inhibitors, and SCLC-P to PARP inhibitors.

Treatment resistance

The tendency of SCLC to develop treatment resistance, even after an initial response, is a known challenge. Using single-cell RNA sequencing to evaluate tumor evolution, the authors observed a tendency of SCLC-A to switch to SCLC-I after chemotherapy treatment, a possible contributor to treatment resistance.

It will be necessary to verify the study findings through further investigations, particularly regarding the therapeutic vulnerabilities for each group.

“Now we can develop more effective strategies for each group in clinical trials, taking into account that they each have different biology and optimal drug targets,” Dr. Byers said. “As a field, small cell lung cancer is about 15 years behind non–small cell lung cancer’s renaissance of biomarkers and personalized therapies. This represents a huge step in understanding which drugs work best for which patients and gives us a path forward for personalized approaches for small cell lung cancer.”

“Dr. Gay’s work is the latest in a growing series of exciting studies demonstrating the utility of defining subtypes of small cell lung cancer based on expression of master transcriptional regulators,” commented Charles Rudin, MD, PhD, of Memorial Sloan Kettering Cancer Center in New York, in an interview.

He added, “While tumors can evolve between some of these categories, the dominant subtype assignment influences therapeutic vulnerabilities. It is an exciting time for those of us engaged in small cell research. Subtyping should help guide more focused and successful clinical trials for patients with small cell lung cancer.”

The authors disclosed multiple relationships with companies. The study was supported by the National Institutes of Health/National Cancer Institute, the University of Texas Southwestern and MD Anderson Cancer Center, and a variety of other governmental and nonprofit groups. Dr. Rudin is principal investigator of the NCI small cell lung cancer research consortium.

The Food and Drug Administration has approved cemiplimab-rwlc (Libtayo) for the treatment of advanced non–small cell lung cancer (NSCLC).

Specifically, the indication is for first-line treatment as monotherapy for patients with locally advanced or metastatic disease who are not candidates for surgical resection or definitive chemoradiotherapy and whose tumors have a high expression of programmed death–ligand 1 (PD-L1) (Tumor Proportion Score >50%), as determined by an FDA-approved test, with no EGFR, ALK, or ROS1 aberrations.

This is the third indication for cemiplimab-rlwc, a monoclonal antibody and PD-1 inhibitor.

In February, it was approved as the first immunotherapy to treat patients with locally advanced or metastatic basal cell carcinoma that was previously treated with a hedgehog pathway inhibitor or for whom a hedgehog inhibitor is inappropriate.

Cemiplimab-rlwc previously received FDA approval in 2018 for locally advanced or metastatic cutaneous squamous cell carcinoma for patients who were not eligible for curative surgery or radiotherapy. At the time, Karl Lewis, MD, a professor at the University of Colorado at Denver, Aurora, and a trial investigator, predicted that the drug “will change the treatment paradigm for patients with advanced basal cell carcinoma.”
 

Outperforms chemotherapy

The approval for use in NSCLC is based on results from the phase 3, open-label EMPOWER-Lung 1 trial, which randomly assigned 710 patients in a 1:1 ratio to receive either cemiplimab-rwlc or platinum-doublet chemotherapy. Patients had either locally advanced NSCLC and were not candidates for surgical resection or definitive chemoradiotherapy, or they had metastatic NSCLC.

Patients in the experimental arm received cemiplimab-rwlc 350 mg intravenously every 3 weeks. The primary efficacy outcome measures were overall survival (OS) and progression-free survival (PFS), determined on the basis of blinded independent central review.

Results showed statistically significant improvements in both outcomes. Median OS was 22.1 months with cemiplimab-rwlc versus 14.3 months with chemotherapy (hazard ratio, 0.68; P = .0022). Median PFS was 6.2 months versus 5.6 months (HR, 0.59; P < .0001).

The confirmed overall response rate was 37% for the cemiplimab arm versus 21% for the chemotherapy arm.

The most common adverse reactions (>10%) with cemiplimab-rlwc were musculoskeletal pain, rash, anemia, fatigue, decreased appetite, pneumonia, and cough.

This approval “means physicians and patients have a potent new treatment option against this deadly disease,” said Naiyer Rizvi, MD, Price Family Professor of Medicine, director of thoracic oncology, and codirector of cancer immunotherapy at Columbia University Irving Medical Center, New York, in a statement. He was a steering committee member on the EMPOWER-Lung-1 Trial.

“Notably, Libtayo was approved based on a pivotal trial where most chemotherapy patients crossed over to Libtayo following disease progression, and that allowed for frequently underrepresented patients who had pretreated and clinically stable brain metastases or who had locally advanced disease and were not candidates for definitive chemoradiation,” said Dr. Rizvi. “This gives doctors important new data when considering Libtayo for the varied patients and situations they treat in daily clinical practice.”

A version of this article first appeared on Medscape.com.

The Food and Drug Administration has approved cemiplimab-rwlc (Libtayo) for the treatment of advanced non–small cell lung cancer (NSCLC).

Specifically, the indication is for first-line treatment as monotherapy for patients with locally advanced or metastatic disease who are not candidates for surgical resection or definitive chemoradiotherapy and whose tumors have a high expression of programmed death–ligand 1 (PD-L1) (Tumor Proportion Score >50%), as determined by an FDA-approved test, with no EGFR, ALK, or ROS1 aberrations.

This is the third indication for cemiplimab-rlwc, a monoclonal antibody and PD-1 inhibitor.

In February, it was approved as the first immunotherapy to treat patients with locally advanced or metastatic basal cell carcinoma that was previously treated with a hedgehog pathway inhibitor or for whom a hedgehog inhibitor is inappropriate.

Cemiplimab-rlwc previously received FDA approval in 2018 for locally advanced or metastatic cutaneous squamous cell carcinoma for patients who were not eligible for curative surgery or radiotherapy. At the time, Karl Lewis, MD, a professor at the University of Colorado at Denver, Aurora, and a trial investigator, predicted that the drug “will change the treatment paradigm for patients with advanced basal cell carcinoma.”
 

Outperforms chemotherapy

The approval for use in NSCLC is based on results from the phase 3, open-label EMPOWER-Lung 1 trial, which randomly assigned 710 patients in a 1:1 ratio to receive either cemiplimab-rwlc or platinum-doublet chemotherapy. Patients had either locally advanced NSCLC and were not candidates for surgical resection or definitive chemoradiotherapy, or they had metastatic NSCLC.

Patients in the experimental arm received cemiplimab-rwlc 350 mg intravenously every 3 weeks. The primary efficacy outcome measures were overall survival (OS) and progression-free survival (PFS), determined on the basis of blinded independent central review.

Results showed statistically significant improvements in both outcomes. Median OS was 22.1 months with cemiplimab-rwlc versus 14.3 months with chemotherapy (hazard ratio, 0.68; P = .0022). Median PFS was 6.2 months versus 5.6 months (HR, 0.59; P < .0001).

The confirmed overall response rate was 37% for the cemiplimab arm versus 21% for the chemotherapy arm.

The most common adverse reactions (>10%) with cemiplimab-rlwc were musculoskeletal pain, rash, anemia, fatigue, decreased appetite, pneumonia, and cough.

This approval “means physicians and patients have a potent new treatment option against this deadly disease,” said Naiyer Rizvi, MD, Price Family Professor of Medicine, director of thoracic oncology, and codirector of cancer immunotherapy at Columbia University Irving Medical Center, New York, in a statement. He was a steering committee member on the EMPOWER-Lung-1 Trial.

“Notably, Libtayo was approved based on a pivotal trial where most chemotherapy patients crossed over to Libtayo following disease progression, and that allowed for frequently underrepresented patients who had pretreated and clinically stable brain metastases or who had locally advanced disease and were not candidates for definitive chemoradiation,” said Dr. Rizvi. “This gives doctors important new data when considering Libtayo for the varied patients and situations they treat in daily clinical practice.”

A version of this article first appeared on Medscape.com.

The Food and Drug Administration has approved cemiplimab-rwlc (Libtayo) for the treatment of advanced non–small cell lung cancer (NSCLC).

Specifically, the indication is for first-line treatment as monotherapy for patients with locally advanced or metastatic disease who are not candidates for surgical resection or definitive chemoradiotherapy and whose tumors have a high expression of programmed death–ligand 1 (PD-L1) (Tumor Proportion Score >50%), as determined by an FDA-approved test, with no EGFR, ALK, or ROS1 aberrations.

This is the third indication for cemiplimab-rlwc, a monoclonal antibody and PD-1 inhibitor.

In February, it was approved as the first immunotherapy to treat patients with locally advanced or metastatic basal cell carcinoma that was previously treated with a hedgehog pathway inhibitor or for whom a hedgehog inhibitor is inappropriate.

Cemiplimab-rlwc previously received FDA approval in 2018 for locally advanced or metastatic cutaneous squamous cell carcinoma for patients who were not eligible for curative surgery or radiotherapy. At the time, Karl Lewis, MD, a professor at the University of Colorado at Denver, Aurora, and a trial investigator, predicted that the drug “will change the treatment paradigm for patients with advanced basal cell carcinoma.”
 

Outperforms chemotherapy

The approval for use in NSCLC is based on results from the phase 3, open-label EMPOWER-Lung 1 trial, which randomly assigned 710 patients in a 1:1 ratio to receive either cemiplimab-rwlc or platinum-doublet chemotherapy. Patients had either locally advanced NSCLC and were not candidates for surgical resection or definitive chemoradiotherapy, or they had metastatic NSCLC.

Patients in the experimental arm received cemiplimab-rwlc 350 mg intravenously every 3 weeks. The primary efficacy outcome measures were overall survival (OS) and progression-free survival (PFS), determined on the basis of blinded independent central review.

Results showed statistically significant improvements in both outcomes. Median OS was 22.1 months with cemiplimab-rwlc versus 14.3 months with chemotherapy (hazard ratio, 0.68; P = .0022). Median PFS was 6.2 months versus 5.6 months (HR, 0.59; P < .0001).

The confirmed overall response rate was 37% for the cemiplimab arm versus 21% for the chemotherapy arm.

The most common adverse reactions (>10%) with cemiplimab-rlwc were musculoskeletal pain, rash, anemia, fatigue, decreased appetite, pneumonia, and cough.

This approval “means physicians and patients have a potent new treatment option against this deadly disease,” said Naiyer Rizvi, MD, Price Family Professor of Medicine, director of thoracic oncology, and codirector of cancer immunotherapy at Columbia University Irving Medical Center, New York, in a statement. He was a steering committee member on the EMPOWER-Lung-1 Trial.

“Notably, Libtayo was approved based on a pivotal trial where most chemotherapy patients crossed over to Libtayo following disease progression, and that allowed for frequently underrepresented patients who had pretreated and clinically stable brain metastases or who had locally advanced disease and were not candidates for definitive chemoradiation,” said Dr. Rizvi. “This gives doctors important new data when considering Libtayo for the varied patients and situations they treat in daily clinical practice.”

A version of this article first appeared on Medscape.com.

Doctors say a woman in Michigan contracted COVID-19 and died last fall 2 months after receiving a tainted double-lung transplant from a donor who turned out to harbor the virus that causes the disease – despite showing no signs of illness and initially testing negative.

Officials at the University of Michigan Medical School suggested it may be the first proven case of COVID-19 in the U.S. in which the virus was transmitted via an organ transplant. A surgeon who handled the donor lungs was also infected with the virus and fell ill but later recovered.

The incident appears to be isolated – the only confirmed case among nearly 40,000 transplants in 2020. But it has led to calls for more thorough testing of lung transplant donors, with samples taken from deep within the donor lungs as well as the nose and throat, said Dr. Daniel Kaul, director of Michigan Medicine’s transplant infectious disease service.

“We would absolutely not have used the lungs if we’d had a positive COVID-19 test,” said Dr. Kaul, who coauthored a report about the case in the American Journal of Transplantation.

The virus was transmitted when lungs from a woman from the Upper Midwest, who died after suffering a severe brain injury in a car accident, were transplanted into a woman with chronic obstructive lung disease at University Hospital in Ann Arbor. The nose and throat samples routinely collected from both organ donors and recipients tested negative for SARS-CoV-2, the virus that causes covid.

“All the screening that we normally do and are able to do, we did,” Dr. Kaul said.

Three days after the operation, however, the recipient spiked a fever; her blood pressure fell and her breathing became labored. Imaging showed signs of lung infection.

As her condition worsened, the patient developed septic shock and heart function problems. Doctors decided to test for SARS-CoV-2, Dr. Kaul said. Samples from her new lungs came back positive.

Suspicious about the origin of the infection, doctors returned to samples from the transplant donor. A molecular test of a swab from the donor’s nose and throat, taken 48 hours after her lungs were procured, had been negative for SARS-Cov-2. The donor’s family told doctors she had no history of recent travel or COVID-19 symptoms and no known exposure to anyone with the disease.

But doctors had kept a sample of fluid washed from deep within the donor lungs. When they tested that fluid, it was positive for the virus. Four days after the transplant, the surgeon who handled the donor lungs and performed the surgery tested positive, too. Genetic screening revealed that the transplant recipient and the surgeon had been infected by the donor. Ten other members of the transplant team tested negative for the virus.

The transplant recipient deteriorated rapidly, developing multisystem organ failure. Doctors tried known treatments for COVID-19, including remdesivir, a newly approved drug, and convalescent blood plasma from people previously infected with the disease. Eventually, she was placed on the last-resort option of ECMO, or extracorporeal membrane oxygenation, to no avail. Life support was withdrawn, and she died 61 days after the transplant.

Dr. Kaul called the incident “a tragic case.”

While the Michigan case marks the first confirmed incident in the U.S. of transmission through a transplant, others have been suspected. A recent Centers for Disease Control and Prevention report reviewed eight possible cases of what’s known as donor-derived infection that occurred last spring, but concluded the most likely source of transmission of the COVID-19 virus in those cases was in a community or health care setting.

Before this incident, it was not clear whether the COVID-19 virus could be transmitted through solid organ transplants, though it’s well documented with other respiratory viruses. Donor transmission of H1N1 2009 pandemic influenza has been detected almost exclusively in lung transplant recipients, Dr. Kaul noted.

While it’s not surprising that SARS-CoV-2 can be transmitted through infected lungs, it remains uncertain whether other organs affected by COVID-19 – hearts, livers and kidneys, for instance – can transmit the virus, too.

“It seems for non-lung donors that it may be very difficult to transmit COVID-19, even if the donor has COVID-19,” Dr. Kaul said.

Organ donors have been tested routinely for SARS-CoV-2 during the pandemic, though it’s not required by the Organ Procurement and Transplantation Network, or OPTN, which oversees transplants in the U.S. But the Michigan case underscores the need for more extensive sampling before transplant, especially in areas with high rates of covid transmission, Dr. Kaul said.

When it comes to lungs, that means making sure to test samples from the donor’s lower respiratory tract, as well as from the nose and throat. Obtaining and testing such samples from donors can be difficult to carry out in a timely fashion. There’s also the risk of introducing infection into the donated lungs, Dr. Kaul said.

Because no organs other than lungs were used, the Michigan case doesn’t provide insight into testing protocols for other organs.

Overall, viral transmissions from organ donors to recipients remain rare, occurring in fewer than 1% of transplant recipients, research shows. The medical risks facing ailing patients who reject a donor organ are generally far higher, said Dr. David Klassen, chief medical officer with the United Network for Organ Sharing, the federal contractor that runs the OPTN.

“The risks of turning down transplants are catastrophic,” he said. “I don’t think patients should be afraid of the transplant process.”
 

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of KFF (Kaiser Family Foundation), which is not affiliated with Kaiser Permanente.

Doctors say a woman in Michigan contracted COVID-19 and died last fall 2 months after receiving a tainted double-lung transplant from a donor who turned out to harbor the virus that causes the disease – despite showing no signs of illness and initially testing negative.

Officials at the University of Michigan Medical School suggested it may be the first proven case of COVID-19 in the U.S. in which the virus was transmitted via an organ transplant. A surgeon who handled the donor lungs was also infected with the virus and fell ill but later recovered.

The incident appears to be isolated – the only confirmed case among nearly 40,000 transplants in 2020. But it has led to calls for more thorough testing of lung transplant donors, with samples taken from deep within the donor lungs as well as the nose and throat, said Dr. Daniel Kaul, director of Michigan Medicine’s transplant infectious disease service.

“We would absolutely not have used the lungs if we’d had a positive COVID-19 test,” said Dr. Kaul, who coauthored a report about the case in the American Journal of Transplantation.

The virus was transmitted when lungs from a woman from the Upper Midwest, who died after suffering a severe brain injury in a car accident, were transplanted into a woman with chronic obstructive lung disease at University Hospital in Ann Arbor. The nose and throat samples routinely collected from both organ donors and recipients tested negative for SARS-CoV-2, the virus that causes covid.

“All the screening that we normally do and are able to do, we did,” Dr. Kaul said.

Three days after the operation, however, the recipient spiked a fever; her blood pressure fell and her breathing became labored. Imaging showed signs of lung infection.

As her condition worsened, the patient developed septic shock and heart function problems. Doctors decided to test for SARS-CoV-2, Dr. Kaul said. Samples from her new lungs came back positive.

Suspicious about the origin of the infection, doctors returned to samples from the transplant donor. A molecular test of a swab from the donor’s nose and throat, taken 48 hours after her lungs were procured, had been negative for SARS-Cov-2. The donor’s family told doctors she had no history of recent travel or COVID-19 symptoms and no known exposure to anyone with the disease.

But doctors had kept a sample of fluid washed from deep within the donor lungs. When they tested that fluid, it was positive for the virus. Four days after the transplant, the surgeon who handled the donor lungs and performed the surgery tested positive, too. Genetic screening revealed that the transplant recipient and the surgeon had been infected by the donor. Ten other members of the transplant team tested negative for the virus.

The transplant recipient deteriorated rapidly, developing multisystem organ failure. Doctors tried known treatments for COVID-19, including remdesivir, a newly approved drug, and convalescent blood plasma from people previously infected with the disease. Eventually, she was placed on the last-resort option of ECMO, or extracorporeal membrane oxygenation, to no avail. Life support was withdrawn, and she died 61 days after the transplant.

Dr. Kaul called the incident “a tragic case.”

While the Michigan case marks the first confirmed incident in the U.S. of transmission through a transplant, others have been suspected. A recent Centers for Disease Control and Prevention report reviewed eight possible cases of what’s known as donor-derived infection that occurred last spring, but concluded the most likely source of transmission of the COVID-19 virus in those cases was in a community or health care setting.

Before this incident, it was not clear whether the COVID-19 virus could be transmitted through solid organ transplants, though it’s well documented with other respiratory viruses. Donor transmission of H1N1 2009 pandemic influenza has been detected almost exclusively in lung transplant recipients, Dr. Kaul noted.

While it’s not surprising that SARS-CoV-2 can be transmitted through infected lungs, it remains uncertain whether other organs affected by COVID-19 – hearts, livers and kidneys, for instance – can transmit the virus, too.

“It seems for non-lung donors that it may be very difficult to transmit COVID-19, even if the donor has COVID-19,” Dr. Kaul said.

Organ donors have been tested routinely for SARS-CoV-2 during the pandemic, though it’s not required by the Organ Procurement and Transplantation Network, or OPTN, which oversees transplants in the U.S. But the Michigan case underscores the need for more extensive sampling before transplant, especially in areas with high rates of covid transmission, Dr. Kaul said.

When it comes to lungs, that means making sure to test samples from the donor’s lower respiratory tract, as well as from the nose and throat. Obtaining and testing such samples from donors can be difficult to carry out in a timely fashion. There’s also the risk of introducing infection into the donated lungs, Dr. Kaul said.

Because no organs other than lungs were used, the Michigan case doesn’t provide insight into testing protocols for other organs.

Overall, viral transmissions from organ donors to recipients remain rare, occurring in fewer than 1% of transplant recipients, research shows. The medical risks facing ailing patients who reject a donor organ are generally far higher, said Dr. David Klassen, chief medical officer with the United Network for Organ Sharing, the federal contractor that runs the OPTN.

“The risks of turning down transplants are catastrophic,” he said. “I don’t think patients should be afraid of the transplant process.”
 

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of KFF (Kaiser Family Foundation), which is not affiliated with Kaiser Permanente.

Doctors say a woman in Michigan contracted COVID-19 and died last fall 2 months after receiving a tainted double-lung transplant from a donor who turned out to harbor the virus that causes the disease – despite showing no signs of illness and initially testing negative.

Officials at the University of Michigan Medical School suggested it may be the first proven case of COVID-19 in the U.S. in which the virus was transmitted via an organ transplant. A surgeon who handled the donor lungs was also infected with the virus and fell ill but later recovered.

The incident appears to be isolated – the only confirmed case among nearly 40,000 transplants in 2020. But it has led to calls for more thorough testing of lung transplant donors, with samples taken from deep within the donor lungs as well as the nose and throat, said Dr. Daniel Kaul, director of Michigan Medicine’s transplant infectious disease service.

“We would absolutely not have used the lungs if we’d had a positive COVID-19 test,” said Dr. Kaul, who coauthored a report about the case in the American Journal of Transplantation.

The virus was transmitted when lungs from a woman from the Upper Midwest, who died after suffering a severe brain injury in a car accident, were transplanted into a woman with chronic obstructive lung disease at University Hospital in Ann Arbor. The nose and throat samples routinely collected from both organ donors and recipients tested negative for SARS-CoV-2, the virus that causes covid.

“All the screening that we normally do and are able to do, we did,” Dr. Kaul said.

Three days after the operation, however, the recipient spiked a fever; her blood pressure fell and her breathing became labored. Imaging showed signs of lung infection.

As her condition worsened, the patient developed septic shock and heart function problems. Doctors decided to test for SARS-CoV-2, Dr. Kaul said. Samples from her new lungs came back positive.

Suspicious about the origin of the infection, doctors returned to samples from the transplant donor. A molecular test of a swab from the donor’s nose and throat, taken 48 hours after her lungs were procured, had been negative for SARS-Cov-2. The donor’s family told doctors she had no history of recent travel or COVID-19 symptoms and no known exposure to anyone with the disease.

But doctors had kept a sample of fluid washed from deep within the donor lungs. When they tested that fluid, it was positive for the virus. Four days after the transplant, the surgeon who handled the donor lungs and performed the surgery tested positive, too. Genetic screening revealed that the transplant recipient and the surgeon had been infected by the donor. Ten other members of the transplant team tested negative for the virus.

The transplant recipient deteriorated rapidly, developing multisystem organ failure. Doctors tried known treatments for COVID-19, including remdesivir, a newly approved drug, and convalescent blood plasma from people previously infected with the disease. Eventually, she was placed on the last-resort option of ECMO, or extracorporeal membrane oxygenation, to no avail. Life support was withdrawn, and she died 61 days after the transplant.

Dr. Kaul called the incident “a tragic case.”

While the Michigan case marks the first confirmed incident in the U.S. of transmission through a transplant, others have been suspected. A recent Centers for Disease Control and Prevention report reviewed eight possible cases of what’s known as donor-derived infection that occurred last spring, but concluded the most likely source of transmission of the COVID-19 virus in those cases was in a community or health care setting.

Before this incident, it was not clear whether the COVID-19 virus could be transmitted through solid organ transplants, though it’s well documented with other respiratory viruses. Donor transmission of H1N1 2009 pandemic influenza has been detected almost exclusively in lung transplant recipients, Dr. Kaul noted.

While it’s not surprising that SARS-CoV-2 can be transmitted through infected lungs, it remains uncertain whether other organs affected by COVID-19 – hearts, livers and kidneys, for instance – can transmit the virus, too.

“It seems for non-lung donors that it may be very difficult to transmit COVID-19, even if the donor has COVID-19,” Dr. Kaul said.

Organ donors have been tested routinely for SARS-CoV-2 during the pandemic, though it’s not required by the Organ Procurement and Transplantation Network, or OPTN, which oversees transplants in the U.S. But the Michigan case underscores the need for more extensive sampling before transplant, especially in areas with high rates of covid transmission, Dr. Kaul said.

When it comes to lungs, that means making sure to test samples from the donor’s lower respiratory tract, as well as from the nose and throat. Obtaining and testing such samples from donors can be difficult to carry out in a timely fashion. There’s also the risk of introducing infection into the donated lungs, Dr. Kaul said.

Because no organs other than lungs were used, the Michigan case doesn’t provide insight into testing protocols for other organs.

Overall, viral transmissions from organ donors to recipients remain rare, occurring in fewer than 1% of transplant recipients, research shows. The medical risks facing ailing patients who reject a donor organ are generally far higher, said Dr. David Klassen, chief medical officer with the United Network for Organ Sharing, the federal contractor that runs the OPTN.

“The risks of turning down transplants are catastrophic,” he said. “I don’t think patients should be afraid of the transplant process.”
 

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of KFF (Kaiser Family Foundation), which is not affiliated with Kaiser Permanente.

Research has shown that, compared with their urban counterparts, rural cancer patients have higher cancer-related mortality and other negative treatment outcomes.

Among other explanations, the disparity has been attributed to lower education and income levels, medical and behavioral risk factors, differences in health literacy, and lower confidence in the medical system among rural residents (JCO Oncol Pract. 2020 Jul;16(7):422-30).

The COVID-19 and Oncology Patient Experience Consortium

Ms. Daniels explained that the COVID-19 and Oncology Patient Experience (COPES) Consortium was created to investigate various aspects of the patient experience during the pandemic. Three cancer centers – Moffitt Cancer Center, Huntsman Cancer Institute, and the Sylvester Comprehensive Cancer Center – participate in COPES.

At Huntsman, investigators studied social and health behaviors of cancer patients to assess whether there was a difference between those from rural and urban areas. The researchers looked at the impact of the pandemic on psychosocial outcomes, preventive measures patients implemented, and their perceptions of the risk of SARS-CoV-2 infection.

The team’s hypothesis was that rural patients might be more vulnerable than urban patients to the effects of social isolation, emotional distress, and health-adverse behaviors, but the investigators noted that there has been no prior research on the topic.
 

Assessing behaviors, attitudes, and outcomes

Between August and September 2020, the researchers surveyed 1,328 adult cancer patients who had visited Huntsman in the previous 4 years and who were enrolled in Huntsman’s Total Cancer Care or Precision Exercise Prescription studies.

Patients completed questionnaires that encompassed demographic and clinical factors, employment status, health behaviors, and infection preventive measures. Questionnaires were provided in electronic, paper, or phone-based formats. Information regarding age, race, ethnicity, and tumor stage was abstracted from Huntsman’s electronic health record.

Modifications in daily life and social interaction were assessed on a 5-point scale. Changes in exercise habits and alcohol consumption were assessed on a 3-point scale. Infection mitigation measures (the use of face masks and hand sanitizer) and perceptions about the likelihood of SARS-CoV-2 infection were measured.

The rural-urban community area codes system, which classifies U.S. census tracts by measures of population density, urbanization, and daily commuting, was utilized to categorize patients into rural and urban residences.
 

Characteristics of urban and rural cancer patients

There were 997 urban and 331 rural participants. The mean age was 60.1 years in the urban population and 62.6 years in the rural population (P = .01). There were no urban-rural differences in sex, ethnicity, cancer stage, or body mass index.

More urban than rural participants were employed full- or part-time (45% vs. 37%; P = .045). The rural counties had more patients who were not currently employed, primarily due to retirement (77% vs. 69% urban; P < .001).

“No health insurance coverage” was reported by 2% of urban and 4% of rural participants (P = .009), and 85% of all patients reported “good” to “excellent” overall health. Cancer patients in rural counties were significantly more likely to have ever smoked (37% vs. 25% urban; P = .001). In addition, alcohol consumption in the previous year was higher in rural patients. “Every day to less than once monthly” alcohol usage was reported by 44% of urban and 60% of rural patients (P < .001).
 

Changes in daily life and health-related behavior during the pandemic

Urban patients were more likely to report changes in their daily lives due to the pandemic. Specifically, 35% of urban patients and 26% of rural patients said the pandemic had changed their daily life “a lot” (P = .001).

However, there were no major differences between urban and rural patients when it came to changes in social interaction in the past month or feeling lonely in the past month (P = .45 and P = .88, respectively). Similarly, there were no significant differences for changes in alcohol consumption between the groups (P = .90).

Changes in exercise habits due to the pandemic were more common among patients in urban counties (51% vs. 39% rural; P < .001), though similar percentages of patients reported exercising less (44% urban vs. 45% rural) or more frequently (24% urban vs. 20% rural).

In terms of infection mitigation measures, urban patients were more likely to use face masks “very often” (83% vs. 66% rural; P < .001), while hand sanitizer was used “very often” among 66% of urban and 57% of rural participants (P = .05).

Urban participants were more likely than were their rural counterparts to think themselves “somewhat” or “very” likely to develop COVID-19 (22% vs. 14%; P = .04).

It might be short-sighted for oncology and public health specialists to be dismissive of differences in infection mitigation behaviors and perceptions of vulnerability to SARS-CoV-2 infection. Those behaviors and perceptions of risk could lead to lower vaccination rates in rural areas. If that occurs, there would be major negative consequences for the long-term health of rural communities and their medically vulnerable residents.
 

Future directions

Although the first 6 months of the COVID-19 pandemic had disparate effects on cancer patients living in rural and urban counties, the reasons for the disparities are complex and not easily explained by this study.

It is possible that sequential administration of the survey during the pandemic would have uncovered greater variances in attitude and health-related behaviors.

As Ms. Daniels noted, when the survey was performed, Utah had not experienced a high frequency of COVID-19 cases. Furthermore, different levels of restrictions were implemented on a county-by-county basis, potentially influencing patients’ behaviors, psychosocial adjustment, and perceptions of risk.

In addition, there may have been differences in unmeasured endpoints (infection rates, medical care utilization via telemedicine, hospitalization rates, late effects, and mortality) between the urban and rural populations.

As the investigators concluded, further research is needed to better characterize the pandemic’s short- and long-term effects on cancer patients in rural and urban settings and appropriate interventions. Such studies may yield insights into the various facets of the well-documented “rural health gap” in cancer outcomes and interventions that could narrow the gap in spheres beyond the COVID-19 pandemic.

Ms. Daniels reported having no relevant disclosures.
 

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Research has shown that, compared with their urban counterparts, rural cancer patients have higher cancer-related mortality and other negative treatment outcomes.

Among other explanations, the disparity has been attributed to lower education and income levels, medical and behavioral risk factors, differences in health literacy, and lower confidence in the medical system among rural residents (JCO Oncol Pract. 2020 Jul;16(7):422-30).

The COVID-19 and Oncology Patient Experience Consortium

Ms. Daniels explained that the COVID-19 and Oncology Patient Experience (COPES) Consortium was created to investigate various aspects of the patient experience during the pandemic. Three cancer centers – Moffitt Cancer Center, Huntsman Cancer Institute, and the Sylvester Comprehensive Cancer Center – participate in COPES.

At Huntsman, investigators studied social and health behaviors of cancer patients to assess whether there was a difference between those from rural and urban areas. The researchers looked at the impact of the pandemic on psychosocial outcomes, preventive measures patients implemented, and their perceptions of the risk of SARS-CoV-2 infection.

The team’s hypothesis was that rural patients might be more vulnerable than urban patients to the effects of social isolation, emotional distress, and health-adverse behaviors, but the investigators noted that there has been no prior research on the topic.
 

Assessing behaviors, attitudes, and outcomes

Between August and September 2020, the researchers surveyed 1,328 adult cancer patients who had visited Huntsman in the previous 4 years and who were enrolled in Huntsman’s Total Cancer Care or Precision Exercise Prescription studies.

Patients completed questionnaires that encompassed demographic and clinical factors, employment status, health behaviors, and infection preventive measures. Questionnaires were provided in electronic, paper, or phone-based formats. Information regarding age, race, ethnicity, and tumor stage was abstracted from Huntsman’s electronic health record.

Modifications in daily life and social interaction were assessed on a 5-point scale. Changes in exercise habits and alcohol consumption were assessed on a 3-point scale. Infection mitigation measures (the use of face masks and hand sanitizer) and perceptions about the likelihood of SARS-CoV-2 infection were measured.

The rural-urban community area codes system, which classifies U.S. census tracts by measures of population density, urbanization, and daily commuting, was utilized to categorize patients into rural and urban residences.
 

Characteristics of urban and rural cancer patients

There were 997 urban and 331 rural participants. The mean age was 60.1 years in the urban population and 62.6 years in the rural population (P = .01). There were no urban-rural differences in sex, ethnicity, cancer stage, or body mass index.

More urban than rural participants were employed full- or part-time (45% vs. 37%; P = .045). The rural counties had more patients who were not currently employed, primarily due to retirement (77% vs. 69% urban; P < .001).

“No health insurance coverage” was reported by 2% of urban and 4% of rural participants (P = .009), and 85% of all patients reported “good” to “excellent” overall health. Cancer patients in rural counties were significantly more likely to have ever smoked (37% vs. 25% urban; P = .001). In addition, alcohol consumption in the previous year was higher in rural patients. “Every day to less than once monthly” alcohol usage was reported by 44% of urban and 60% of rural patients (P < .001).
 

Changes in daily life and health-related behavior during the pandemic

Urban patients were more likely to report changes in their daily lives due to the pandemic. Specifically, 35% of urban patients and 26% of rural patients said the pandemic had changed their daily life “a lot” (P = .001).

However, there were no major differences between urban and rural patients when it came to changes in social interaction in the past month or feeling lonely in the past month (P = .45 and P = .88, respectively). Similarly, there were no significant differences for changes in alcohol consumption between the groups (P = .90).

Changes in exercise habits due to the pandemic were more common among patients in urban counties (51% vs. 39% rural; P < .001), though similar percentages of patients reported exercising less (44% urban vs. 45% rural) or more frequently (24% urban vs. 20% rural).

In terms of infection mitigation measures, urban patients were more likely to use face masks “very often” (83% vs. 66% rural; P < .001), while hand sanitizer was used “very often” among 66% of urban and 57% of rural participants (P = .05).

Urban participants were more likely than were their rural counterparts to think themselves “somewhat” or “very” likely to develop COVID-19 (22% vs. 14%; P = .04).

It might be short-sighted for oncology and public health specialists to be dismissive of differences in infection mitigation behaviors and perceptions of vulnerability to SARS-CoV-2 infection. Those behaviors and perceptions of risk could lead to lower vaccination rates in rural areas. If that occurs, there would be major negative consequences for the long-term health of rural communities and their medically vulnerable residents.
 

Future directions

Although the first 6 months of the COVID-19 pandemic had disparate effects on cancer patients living in rural and urban counties, the reasons for the disparities are complex and not easily explained by this study.

It is possible that sequential administration of the survey during the pandemic would have uncovered greater variances in attitude and health-related behaviors.

As Ms. Daniels noted, when the survey was performed, Utah had not experienced a high frequency of COVID-19 cases. Furthermore, different levels of restrictions were implemented on a county-by-county basis, potentially influencing patients’ behaviors, psychosocial adjustment, and perceptions of risk.

In addition, there may have been differences in unmeasured endpoints (infection rates, medical care utilization via telemedicine, hospitalization rates, late effects, and mortality) between the urban and rural populations.

As the investigators concluded, further research is needed to better characterize the pandemic’s short- and long-term effects on cancer patients in rural and urban settings and appropriate interventions. Such studies may yield insights into the various facets of the well-documented “rural health gap” in cancer outcomes and interventions that could narrow the gap in spheres beyond the COVID-19 pandemic.

Ms. Daniels reported having no relevant disclosures.
 

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Research has shown that, compared with their urban counterparts, rural cancer patients have higher cancer-related mortality and other negative treatment outcomes.

Among other explanations, the disparity has been attributed to lower education and income levels, medical and behavioral risk factors, differences in health literacy, and lower confidence in the medical system among rural residents (JCO Oncol Pract. 2020 Jul;16(7):422-30).

The COVID-19 and Oncology Patient Experience Consortium

Ms. Daniels explained that the COVID-19 and Oncology Patient Experience (COPES) Consortium was created to investigate various aspects of the patient experience during the pandemic. Three cancer centers – Moffitt Cancer Center, Huntsman Cancer Institute, and the Sylvester Comprehensive Cancer Center – participate in COPES.

At Huntsman, investigators studied social and health behaviors of cancer patients to assess whether there was a difference between those from rural and urban areas. The researchers looked at the impact of the pandemic on psychosocial outcomes, preventive measures patients implemented, and their perceptions of the risk of SARS-CoV-2 infection.

The team’s hypothesis was that rural patients might be more vulnerable than urban patients to the effects of social isolation, emotional distress, and health-adverse behaviors, but the investigators noted that there has been no prior research on the topic.
 

Assessing behaviors, attitudes, and outcomes

Between August and September 2020, the researchers surveyed 1,328 adult cancer patients who had visited Huntsman in the previous 4 years and who were enrolled in Huntsman’s Total Cancer Care or Precision Exercise Prescription studies.

Patients completed questionnaires that encompassed demographic and clinical factors, employment status, health behaviors, and infection preventive measures. Questionnaires were provided in electronic, paper, or phone-based formats. Information regarding age, race, ethnicity, and tumor stage was abstracted from Huntsman’s electronic health record.

Modifications in daily life and social interaction were assessed on a 5-point scale. Changes in exercise habits and alcohol consumption were assessed on a 3-point scale. Infection mitigation measures (the use of face masks and hand sanitizer) and perceptions about the likelihood of SARS-CoV-2 infection were measured.

The rural-urban community area codes system, which classifies U.S. census tracts by measures of population density, urbanization, and daily commuting, was utilized to categorize patients into rural and urban residences.
 

Characteristics of urban and rural cancer patients

There were 997 urban and 331 rural participants. The mean age was 60.1 years in the urban population and 62.6 years in the rural population (P = .01). There were no urban-rural differences in sex, ethnicity, cancer stage, or body mass index.

More urban than rural participants were employed full- or part-time (45% vs. 37%; P = .045). The rural counties had more patients who were not currently employed, primarily due to retirement (77% vs. 69% urban; P < .001).

“No health insurance coverage” was reported by 2% of urban and 4% of rural participants (P = .009), and 85% of all patients reported “good” to “excellent” overall health. Cancer patients in rural counties were significantly more likely to have ever smoked (37% vs. 25% urban; P = .001). In addition, alcohol consumption in the previous year was higher in rural patients. “Every day to less than once monthly” alcohol usage was reported by 44% of urban and 60% of rural patients (P < .001).
 

Changes in daily life and health-related behavior during the pandemic

Urban patients were more likely to report changes in their daily lives due to the pandemic. Specifically, 35% of urban patients and 26% of rural patients said the pandemic had changed their daily life “a lot” (P = .001).

However, there were no major differences between urban and rural patients when it came to changes in social interaction in the past month or feeling lonely in the past month (P = .45 and P = .88, respectively). Similarly, there were no significant differences for changes in alcohol consumption between the groups (P = .90).

Changes in exercise habits due to the pandemic were more common among patients in urban counties (51% vs. 39% rural; P < .001), though similar percentages of patients reported exercising less (44% urban vs. 45% rural) or more frequently (24% urban vs. 20% rural).

In terms of infection mitigation measures, urban patients were more likely to use face masks “very often” (83% vs. 66% rural; P < .001), while hand sanitizer was used “very often” among 66% of urban and 57% of rural participants (P = .05).

Urban participants were more likely than were their rural counterparts to think themselves “somewhat” or “very” likely to develop COVID-19 (22% vs. 14%; P = .04).

It might be short-sighted for oncology and public health specialists to be dismissive of differences in infection mitigation behaviors and perceptions of vulnerability to SARS-CoV-2 infection. Those behaviors and perceptions of risk could lead to lower vaccination rates in rural areas. If that occurs, there would be major negative consequences for the long-term health of rural communities and their medically vulnerable residents.
 

Future directions

Although the first 6 months of the COVID-19 pandemic had disparate effects on cancer patients living in rural and urban counties, the reasons for the disparities are complex and not easily explained by this study.

It is possible that sequential administration of the survey during the pandemic would have uncovered greater variances in attitude and health-related behaviors.

As Ms. Daniels noted, when the survey was performed, Utah had not experienced a high frequency of COVID-19 cases. Furthermore, different levels of restrictions were implemented on a county-by-county basis, potentially influencing patients’ behaviors, psychosocial adjustment, and perceptions of risk.

In addition, there may have been differences in unmeasured endpoints (infection rates, medical care utilization via telemedicine, hospitalization rates, late effects, and mortality) between the urban and rural populations.

As the investigators concluded, further research is needed to better characterize the pandemic’s short- and long-term effects on cancer patients in rural and urban settings and appropriate interventions. Such studies may yield insights into the various facets of the well-documented “rural health gap” in cancer outcomes and interventions that could narrow the gap in spheres beyond the COVID-19 pandemic.

Ms. Daniels reported having no relevant disclosures.
 

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Artificial intelligence (AI) is expected to one day affect the entire continuum of cancer care – from screening and risk prediction to diagnosis, risk stratification, treatment selection, and follow-up, according to an expert in the field.

Hugo J.W.L. Aerts, PhD, director of the AI in Medicine Program at Brigham and Women’s Hospital in Boston, described studies using AI for some of these purposes during a presentation at the AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging (Abstract IA-06).

In one study, Dr. Aerts and colleagues set out to determine whether a convolutional neural network (CNN) could extract prognostic information from chest radiographs. The researchers tested this theory using patients from two trials – the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and the National Lung Screening Trial (NLST).

The team developed a CNN, called CXR-risk, and tested whether it could predict the longevity and prognosis of patients in the PLCO (n = 52,320) and NLST (n = 5,493) trials over a 12-year time period, based only on chest radiographs. No clinical information, demographics, radiographic interpretations, duration of follow-up, or censoring were provided to the deep-learning system.

CXR-risk output was stratified into five categories of radiographic risk scores for probability of death, from 0 (very low likelihood of mortality) to 1 (very high likelihood of mortality).

The investigators found a graded association between radiographic risk score and mortality. The very-high-risk group had mortality rates of 53.0% (PLCO) and 33.9% (NLST). In both trials, this was significantly higher than for the very-low-risk group. The unadjusted hazard ratio was 18.3 in the PCLO data set and 15.2 in the NLST data set (P < .001 for both).

This association was maintained after adjustment for radiologists’ findings (e.g., a lung nodule) and risk factors such as age, gender, and comorbid illnesses like diabetes. The adjusted HR was 4.8 in the PCLO data set and 7.0 in the NLST data set (P < .001 for both).

In both data sets, individuals in the very-high-risk group were significantly more likely to die of lung cancer. The aHR was 11.1 in the PCLO data set and 8.4 in the NSLT data set (P < .001 for both).

This might be expected for people who were interested in being screened for lung cancer. However, patients in the very-high-risk group were also more likely to die of cardiovascular illness (aHR, 3.6 for PLCO and 47.8 for NSLT; P < .001 for both) and respiratory illness (aHR, 27.5 for PLCO and 31.9 for NLST; P ≤ .001 for both).

With this information, a clinician could initiate additional testing and/or utilize more aggressive surveillance measures. If an oncologist considered therapy for a patient with newly diagnosed cancer, treatment choices and stratification for adverse events would be more intelligently planned.
 

Using AI to predict the risk of lung cancer

In another study, Dr. Aerts and colleagues developed and validated a CNN called CXR-LC, which was based on CXR-risk. The goal of this study was to see if CXR-LC could predict long-term incident lung cancer using data available in the EHR, including chest radiographs, age, sex, and smoking status.

The CXR-LC model was developed using data from the PLCO trial (n = 41,856) and was validated in smokers from the PLCO trial (n = 5,615; 12-year follow-up) as well as heavy smokers from the NLST trial (n = 5,493; 6-year follow-up).

Results showed that CXR-LC was able to predict which patients were at highest risk for developing lung cancer.

CXR-LC had better discrimination for incident lung cancer than did Medicare eligibility in the PLCO data set (area under the curve, 0.755 vs. 0.634; P < .001). And the performance of CXR-LC was similar to that of the PLCO_M2012 risk score in both the PLCO data set (AUC, 0.755 vs. 0.751) and the NLST data set (AUC, 0.659 vs. 0.650).

When they were compared in screening populations of equal size, CXR-LC was more sensitive than Medicare eligibility criteria in the PLCO data set (74.9% vs. 63.8%; P = .012) and missed 30.7% fewer incident lung cancer diagnoses.
 

AI as a substitute for specialized testing and consultation

In a third study, Dr. Aerts and colleagues used a CNN to predict cardiovascular risk by assessing coronary artery calcium (CAC) from clinically obtained, readily available CT scans.

Ordinarily, identifying CAC – an accurate predictor of cardiovascular events – requires specialized expertise (manual measurement and cardiologist interpretation), time (estimated at 20 minutes/scan), and equipment (ECG-gated cardiac CT scan and special software).

In this study, the researchers used a fully end-to-end automated system with analytic time measured in less than 2 seconds.

The team trained and tuned their CNN using the Framingham Heart Study Offspring and Third Generation cohorts (n = 1,636), which included asymptomatic patients with high-quality, cardiac-gated CT scans for CAC quantification.

The researchers then tested the CNN on two asymptomatic and two symptomatic cohorts:

• Asymptomatic Framingham Heart Study participants (n = 663) in whom the outcome measures were cardiovascular disease and death.
• Asymptomatic NLST participants (n = 14,959) in whom the outcome measure was atherosclerotic cardiovascular death.
• Symptomatic PROMISE study participants with stable chest pain (n = 4,021) in whom the outcome measures were all-cause mortality, MI, and hospitalization for unstable angina.
• Symptomatic ROMICAT-II study patients with acute chest pain (n = 441) in whom the outcome measure was acute coronary syndrome at 28 days.

Among 5,521 subjects across all testing cohorts with cardiac-gated and nongated chest CT scans, the CNN and expert reader interpretations agreed on the CAC risk scores with a high level of concordance (kappa, 0.71; concordance rate, 0.79).

There was a very high Spearman’s correlation of 0.92 (P < .0001) and substantial agreement between automatically and manually calculated CAC risk groups, substantiating robust risk prediction for cardiovascular disease across multiple clinical scenarios.

Dr. Aerts commented that, among the NLST participants who had the highest risk of developing lung cancer, the risk of cardiovascular death was as high as the risk of death from lung cancer.
 

Using AI to assess patient outcomes

In an unpublished study, Dr. Aerts and colleagues used AI in an attempt to determine whether changes in measurements of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle mass would provide clues about treatment outcomes in lung cancer patients.

The researchers developed a deep learning model using data from 1,129 patients at Massachusetts General and Brigham and Women’s Hospitals, measuring SAT, VAT, and muscle mass. The team applied the measurement system to a population of 12,128 outpatients and calculated z scores for SAT, VAT, and muscle mass to determine “normal” values.

When they applied the norms to surgical lung cancer data sets from the Boston Lung Cancer Study (n = 437) and TRACERx study (n = 394), the researchers found that smokers had lower adiposity and lower muscle mass than never-smokers.

More importantly, over time, among lung cancer patients who lost greater than 5% of VAT, SAT, and muscle mass, those patients with the greatest SAT loss (P < .0001) or VAT loss (P = .0015) had the lowest lung cancer–specific survival in the TRACERx study. There was no significant impairment of lung cancer-specific survival for patients who experienced skeletal muscle loss (P = .23).

The same observation was made for overall survival among patients enrolled in the Boston Lung Cancer Study, using the 5% threshold. Overall survival was significantly worse with increasing VAT loss (P = .0023) and SAT loss (P = .0082) but not with increasing skeletal muscle loss (P = .3).

The investigators speculated about whether the correlation between body composition and clinical outcome could yield clues about tumor biology. To test this, the researchers used the RNA sequencing–based ORACLE risk score in lung cancer patients from TRACERx. There was a high correlation between higher ORACLE risk scores and lower VAT and SAT, suggesting that measures of adiposity on CT were reflected in tumor biology patterns on an RNA level in lung cancer patients. There was no such correlation between ORACLE risk scores and skeletal muscle mass.
 

Wonderment ... tempered by concern and challenges

AI has awe-inspiring potential to yield actionable and prognostically important information from data mining the EHR and extracting the vast quantities of information from images. In some cases (like CAC), it is information that is “hiding in plain sight.” However, Dr. Aerts expressed several cautions, some of which have already plagued AI.

He referenced the Gartner Hype Cycle, which provides a graphic representation of five phases in the life cycle of emerging technologies. The “innovation trigger” is followed by a “peak of inflated expectations,” a “trough of disillusionment,” a “slope of enlightenment,” and a “plateau of productivity.”

Dr. Aerts noted that, in recent years, AI has seemed to fall into the trough of disillusionment, but it may be entering the slope of enlightenment on the way to the plateau of productivity.

His research highlighted several examples of productivity in radiomics in cancer patients and those who are at high risk of developing cancer.

In Dr. Aerts’s opinion, a second concern is replication of AI research results. He noted that, among 400 published studies, only 6% of authors shared the codes that would enable their findings to be corroborated. About 30% shared test data, and 54% shared “pseudocodes,” but transparency and reproducibility are problems for the acceptance and broad implementation of AI.

Dr. Aerts endorsed the Modelhub initiative (www.modelhub.ai), a multi-institutional initiative to advance reproducibility in the AI field and advance its full potential.

However, there are additional concerns about the implementation of radiomics and, more generally, data mining from clinicians’ EHRs to personalize care.

Firstly, it may be laborious and difficult to explain complex, computer-based risk stratification models to patients. Hereditary cancer testing is an example of a risk assessment test that requires complicated explanations that many clinicians relegate to genetics counselors – when patients elect to see them. When a model is not explainable, it undermines the confidence of patients and their care providers, according to an editorial related to the CXR-LC study.

Another issue is that uptake of lung cancer screening, in practice, has been underutilized by individuals who meet current, relatively straightforward Medicare criteria. Despite the apparently better accuracy of the CXR-LC deep-learning model, its complexity and limited access could constitute an additional barrier for the at-risk individuals who should avail themselves of screening.

Furthermore, although age and gender are accurate in most circumstances, there is legitimate concern about the accuracy of, for example, smoking history data and comorbid conditions in current EHRs. Who performs the laborious curation of the input in an AI model to assure its accuracy for individual patients?

Finally, it is unclear how scalable and applicable AI will be to medically underserved populations (e.g., smaller, community-based, free-standing, socioeconomically disadvantaged or rural health care institutions). There are substantial initial and maintenance costs that may limit AI’s availability to some academic institutions and large health maintenance organizations.

As the concerns and challenges are addressed, it will be interesting to see where and when the plateau of productivity for AI in cancer care occurs. When it does, many cancer patients will benefit from enhanced care along the continuum of the complex disease they and their caregivers seek to master.

Dr. Aerts disclosed relationships with Onc.AI outside the presented work.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Artificial intelligence (AI) is expected to one day affect the entire continuum of cancer care – from screening and risk prediction to diagnosis, risk stratification, treatment selection, and follow-up, according to an expert in the field.

Hugo J.W.L. Aerts, PhD, director of the AI in Medicine Program at Brigham and Women’s Hospital in Boston, described studies using AI for some of these purposes during a presentation at the AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging (Abstract IA-06).

In one study, Dr. Aerts and colleagues set out to determine whether a convolutional neural network (CNN) could extract prognostic information from chest radiographs. The researchers tested this theory using patients from two trials – the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and the National Lung Screening Trial (NLST).

The team developed a CNN, called CXR-risk, and tested whether it could predict the longevity and prognosis of patients in the PLCO (n = 52,320) and NLST (n = 5,493) trials over a 12-year time period, based only on chest radiographs. No clinical information, demographics, radiographic interpretations, duration of follow-up, or censoring were provided to the deep-learning system.

CXR-risk output was stratified into five categories of radiographic risk scores for probability of death, from 0 (very low likelihood of mortality) to 1 (very high likelihood of mortality).

The investigators found a graded association between radiographic risk score and mortality. The very-high-risk group had mortality rates of 53.0% (PLCO) and 33.9% (NLST). In both trials, this was significantly higher than for the very-low-risk group. The unadjusted hazard ratio was 18.3 in the PCLO data set and 15.2 in the NLST data set (P < .001 for both).

This association was maintained after adjustment for radiologists’ findings (e.g., a lung nodule) and risk factors such as age, gender, and comorbid illnesses like diabetes. The adjusted HR was 4.8 in the PCLO data set and 7.0 in the NLST data set (P < .001 for both).

In both data sets, individuals in the very-high-risk group were significantly more likely to die of lung cancer. The aHR was 11.1 in the PCLO data set and 8.4 in the NSLT data set (P < .001 for both).

This might be expected for people who were interested in being screened for lung cancer. However, patients in the very-high-risk group were also more likely to die of cardiovascular illness (aHR, 3.6 for PLCO and 47.8 for NSLT; P < .001 for both) and respiratory illness (aHR, 27.5 for PLCO and 31.9 for NLST; P ≤ .001 for both).

With this information, a clinician could initiate additional testing and/or utilize more aggressive surveillance measures. If an oncologist considered therapy for a patient with newly diagnosed cancer, treatment choices and stratification for adverse events would be more intelligently planned.
 

Using AI to predict the risk of lung cancer

In another study, Dr. Aerts and colleagues developed and validated a CNN called CXR-LC, which was based on CXR-risk. The goal of this study was to see if CXR-LC could predict long-term incident lung cancer using data available in the EHR, including chest radiographs, age, sex, and smoking status.

The CXR-LC model was developed using data from the PLCO trial (n = 41,856) and was validated in smokers from the PLCO trial (n = 5,615; 12-year follow-up) as well as heavy smokers from the NLST trial (n = 5,493; 6-year follow-up).

Results showed that CXR-LC was able to predict which patients were at highest risk for developing lung cancer.

CXR-LC had better discrimination for incident lung cancer than did Medicare eligibility in the PLCO data set (area under the curve, 0.755 vs. 0.634; P < .001). And the performance of CXR-LC was similar to that of the PLCO_M2012 risk score in both the PLCO data set (AUC, 0.755 vs. 0.751) and the NLST data set (AUC, 0.659 vs. 0.650).

When they were compared in screening populations of equal size, CXR-LC was more sensitive than Medicare eligibility criteria in the PLCO data set (74.9% vs. 63.8%; P = .012) and missed 30.7% fewer incident lung cancer diagnoses.
 

AI as a substitute for specialized testing and consultation

In a third study, Dr. Aerts and colleagues used a CNN to predict cardiovascular risk by assessing coronary artery calcium (CAC) from clinically obtained, readily available CT scans.

Ordinarily, identifying CAC – an accurate predictor of cardiovascular events – requires specialized expertise (manual measurement and cardiologist interpretation), time (estimated at 20 minutes/scan), and equipment (ECG-gated cardiac CT scan and special software).

In this study, the researchers used a fully end-to-end automated system with analytic time measured in less than 2 seconds.

The team trained and tuned their CNN using the Framingham Heart Study Offspring and Third Generation cohorts (n = 1,636), which included asymptomatic patients with high-quality, cardiac-gated CT scans for CAC quantification.

The researchers then tested the CNN on two asymptomatic and two symptomatic cohorts:

• Asymptomatic Framingham Heart Study participants (n = 663) in whom the outcome measures were cardiovascular disease and death.
• Asymptomatic NLST participants (n = 14,959) in whom the outcome measure was atherosclerotic cardiovascular death.
• Symptomatic PROMISE study participants with stable chest pain (n = 4,021) in whom the outcome measures were all-cause mortality, MI, and hospitalization for unstable angina.
• Symptomatic ROMICAT-II study patients with acute chest pain (n = 441) in whom the outcome measure was acute coronary syndrome at 28 days.

Among 5,521 subjects across all testing cohorts with cardiac-gated and nongated chest CT scans, the CNN and expert reader interpretations agreed on the CAC risk scores with a high level of concordance (kappa, 0.71; concordance rate, 0.79).

There was a very high Spearman’s correlation of 0.92 (P < .0001) and substantial agreement between automatically and manually calculated CAC risk groups, substantiating robust risk prediction for cardiovascular disease across multiple clinical scenarios.

Dr. Aerts commented that, among the NLST participants who had the highest risk of developing lung cancer, the risk of cardiovascular death was as high as the risk of death from lung cancer.
 

Using AI to assess patient outcomes

In an unpublished study, Dr. Aerts and colleagues used AI in an attempt to determine whether changes in measurements of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle mass would provide clues about treatment outcomes in lung cancer patients.

The researchers developed a deep learning model using data from 1,129 patients at Massachusetts General and Brigham and Women’s Hospitals, measuring SAT, VAT, and muscle mass. The team applied the measurement system to a population of 12,128 outpatients and calculated z scores for SAT, VAT, and muscle mass to determine “normal” values.

When they applied the norms to surgical lung cancer data sets from the Boston Lung Cancer Study (n = 437) and TRACERx study (n = 394), the researchers found that smokers had lower adiposity and lower muscle mass than never-smokers.

More importantly, over time, among lung cancer patients who lost greater than 5% of VAT, SAT, and muscle mass, those patients with the greatest SAT loss (P < .0001) or VAT loss (P = .0015) had the lowest lung cancer–specific survival in the TRACERx study. There was no significant impairment of lung cancer-specific survival for patients who experienced skeletal muscle loss (P = .23).

The same observation was made for overall survival among patients enrolled in the Boston Lung Cancer Study, using the 5% threshold. Overall survival was significantly worse with increasing VAT loss (P = .0023) and SAT loss (P = .0082) but not with increasing skeletal muscle loss (P = .3).

The investigators speculated about whether the correlation between body composition and clinical outcome could yield clues about tumor biology. To test this, the researchers used the RNA sequencing–based ORACLE risk score in lung cancer patients from TRACERx. There was a high correlation between higher ORACLE risk scores and lower VAT and SAT, suggesting that measures of adiposity on CT were reflected in tumor biology patterns on an RNA level in lung cancer patients. There was no such correlation between ORACLE risk scores and skeletal muscle mass.
 

Wonderment ... tempered by concern and challenges

AI has awe-inspiring potential to yield actionable and prognostically important information from data mining the EHR and extracting the vast quantities of information from images. In some cases (like CAC), it is information that is “hiding in plain sight.” However, Dr. Aerts expressed several cautions, some of which have already plagued AI.

He referenced the Gartner Hype Cycle, which provides a graphic representation of five phases in the life cycle of emerging technologies. The “innovation trigger” is followed by a “peak of inflated expectations,” a “trough of disillusionment,” a “slope of enlightenment,” and a “plateau of productivity.”

Dr. Aerts noted that, in recent years, AI has seemed to fall into the trough of disillusionment, but it may be entering the slope of enlightenment on the way to the plateau of productivity.

His research highlighted several examples of productivity in radiomics in cancer patients and those who are at high risk of developing cancer.

In Dr. Aerts’s opinion, a second concern is replication of AI research results. He noted that, among 400 published studies, only 6% of authors shared the codes that would enable their findings to be corroborated. About 30% shared test data, and 54% shared “pseudocodes,” but transparency and reproducibility are problems for the acceptance and broad implementation of AI.

Dr. Aerts endorsed the Modelhub initiative (www.modelhub.ai), a multi-institutional initiative to advance reproducibility in the AI field and advance its full potential.

However, there are additional concerns about the implementation of radiomics and, more generally, data mining from clinicians’ EHRs to personalize care.

Firstly, it may be laborious and difficult to explain complex, computer-based risk stratification models to patients. Hereditary cancer testing is an example of a risk assessment test that requires complicated explanations that many clinicians relegate to genetics counselors – when patients elect to see them. When a model is not explainable, it undermines the confidence of patients and their care providers, according to an editorial related to the CXR-LC study.

Another issue is that uptake of lung cancer screening, in practice, has been underutilized by individuals who meet current, relatively straightforward Medicare criteria. Despite the apparently better accuracy of the CXR-LC deep-learning model, its complexity and limited access could constitute an additional barrier for the at-risk individuals who should avail themselves of screening.

Furthermore, although age and gender are accurate in most circumstances, there is legitimate concern about the accuracy of, for example, smoking history data and comorbid conditions in current EHRs. Who performs the laborious curation of the input in an AI model to assure its accuracy for individual patients?

Finally, it is unclear how scalable and applicable AI will be to medically underserved populations (e.g., smaller, community-based, free-standing, socioeconomically disadvantaged or rural health care institutions). There are substantial initial and maintenance costs that may limit AI’s availability to some academic institutions and large health maintenance organizations.

As the concerns and challenges are addressed, it will be interesting to see where and when the plateau of productivity for AI in cancer care occurs. When it does, many cancer patients will benefit from enhanced care along the continuum of the complex disease they and their caregivers seek to master.

Dr. Aerts disclosed relationships with Onc.AI outside the presented work.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Artificial intelligence (AI) is expected to one day affect the entire continuum of cancer care – from screening and risk prediction to diagnosis, risk stratification, treatment selection, and follow-up, according to an expert in the field.

Hugo J.W.L. Aerts, PhD, director of the AI in Medicine Program at Brigham and Women’s Hospital in Boston, described studies using AI for some of these purposes during a presentation at the AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging (Abstract IA-06).

In one study, Dr. Aerts and colleagues set out to determine whether a convolutional neural network (CNN) could extract prognostic information from chest radiographs. The researchers tested this theory using patients from two trials – the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and the National Lung Screening Trial (NLST).

The team developed a CNN, called CXR-risk, and tested whether it could predict the longevity and prognosis of patients in the PLCO (n = 52,320) and NLST (n = 5,493) trials over a 12-year time period, based only on chest radiographs. No clinical information, demographics, radiographic interpretations, duration of follow-up, or censoring were provided to the deep-learning system.

CXR-risk output was stratified into five categories of radiographic risk scores for probability of death, from 0 (very low likelihood of mortality) to 1 (very high likelihood of mortality).

The investigators found a graded association between radiographic risk score and mortality. The very-high-risk group had mortality rates of 53.0% (PLCO) and 33.9% (NLST). In both trials, this was significantly higher than for the very-low-risk group. The unadjusted hazard ratio was 18.3 in the PCLO data set and 15.2 in the NLST data set (P < .001 for both).

This association was maintained after adjustment for radiologists’ findings (e.g., a lung nodule) and risk factors such as age, gender, and comorbid illnesses like diabetes. The adjusted HR was 4.8 in the PCLO data set and 7.0 in the NLST data set (P < .001 for both).

In both data sets, individuals in the very-high-risk group were significantly more likely to die of lung cancer. The aHR was 11.1 in the PCLO data set and 8.4 in the NSLT data set (P < .001 for both).

This might be expected for people who were interested in being screened for lung cancer. However, patients in the very-high-risk group were also more likely to die of cardiovascular illness (aHR, 3.6 for PLCO and 47.8 for NSLT; P < .001 for both) and respiratory illness (aHR, 27.5 for PLCO and 31.9 for NLST; P ≤ .001 for both).

With this information, a clinician could initiate additional testing and/or utilize more aggressive surveillance measures. If an oncologist considered therapy for a patient with newly diagnosed cancer, treatment choices and stratification for adverse events would be more intelligently planned.
 

Using AI to predict the risk of lung cancer

In another study, Dr. Aerts and colleagues developed and validated a CNN called CXR-LC, which was based on CXR-risk. The goal of this study was to see if CXR-LC could predict long-term incident lung cancer using data available in the EHR, including chest radiographs, age, sex, and smoking status.

The CXR-LC model was developed using data from the PLCO trial (n = 41,856) and was validated in smokers from the PLCO trial (n = 5,615; 12-year follow-up) as well as heavy smokers from the NLST trial (n = 5,493; 6-year follow-up).

Results showed that CXR-LC was able to predict which patients were at highest risk for developing lung cancer.

CXR-LC had better discrimination for incident lung cancer than did Medicare eligibility in the PLCO data set (area under the curve, 0.755 vs. 0.634; P < .001). And the performance of CXR-LC was similar to that of the PLCO_M2012 risk score in both the PLCO data set (AUC, 0.755 vs. 0.751) and the NLST data set (AUC, 0.659 vs. 0.650).

When they were compared in screening populations of equal size, CXR-LC was more sensitive than Medicare eligibility criteria in the PLCO data set (74.9% vs. 63.8%; P = .012) and missed 30.7% fewer incident lung cancer diagnoses.
 

AI as a substitute for specialized testing and consultation

In a third study, Dr. Aerts and colleagues used a CNN to predict cardiovascular risk by assessing coronary artery calcium (CAC) from clinically obtained, readily available CT scans.

Ordinarily, identifying CAC – an accurate predictor of cardiovascular events – requires specialized expertise (manual measurement and cardiologist interpretation), time (estimated at 20 minutes/scan), and equipment (ECG-gated cardiac CT scan and special software).

In this study, the researchers used a fully end-to-end automated system with analytic time measured in less than 2 seconds.

The team trained and tuned their CNN using the Framingham Heart Study Offspring and Third Generation cohorts (n = 1,636), which included asymptomatic patients with high-quality, cardiac-gated CT scans for CAC quantification.

The researchers then tested the CNN on two asymptomatic and two symptomatic cohorts:

• Asymptomatic Framingham Heart Study participants (n = 663) in whom the outcome measures were cardiovascular disease and death.
• Asymptomatic NLST participants (n = 14,959) in whom the outcome measure was atherosclerotic cardiovascular death.
• Symptomatic PROMISE study participants with stable chest pain (n = 4,021) in whom the outcome measures were all-cause mortality, MI, and hospitalization for unstable angina.
• Symptomatic ROMICAT-II study patients with acute chest pain (n = 441) in whom the outcome measure was acute coronary syndrome at 28 days.

Among 5,521 subjects across all testing cohorts with cardiac-gated and nongated chest CT scans, the CNN and expert reader interpretations agreed on the CAC risk scores with a high level of concordance (kappa, 0.71; concordance rate, 0.79).

There was a very high Spearman’s correlation of 0.92 (P < .0001) and substantial agreement between automatically and manually calculated CAC risk groups, substantiating robust risk prediction for cardiovascular disease across multiple clinical scenarios.

Dr. Aerts commented that, among the NLST participants who had the highest risk of developing lung cancer, the risk of cardiovascular death was as high as the risk of death from lung cancer.
 

Using AI to assess patient outcomes

In an unpublished study, Dr. Aerts and colleagues used AI in an attempt to determine whether changes in measurements of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle mass would provide clues about treatment outcomes in lung cancer patients.

The researchers developed a deep learning model using data from 1,129 patients at Massachusetts General and Brigham and Women’s Hospitals, measuring SAT, VAT, and muscle mass. The team applied the measurement system to a population of 12,128 outpatients and calculated z scores for SAT, VAT, and muscle mass to determine “normal” values.

When they applied the norms to surgical lung cancer data sets from the Boston Lung Cancer Study (n = 437) and TRACERx study (n = 394), the researchers found that smokers had lower adiposity and lower muscle mass than never-smokers.

More importantly, over time, among lung cancer patients who lost greater than 5% of VAT, SAT, and muscle mass, those patients with the greatest SAT loss (P < .0001) or VAT loss (P = .0015) had the lowest lung cancer–specific survival in the TRACERx study. There was no significant impairment of lung cancer-specific survival for patients who experienced skeletal muscle loss (P = .23).

The same observation was made for overall survival among patients enrolled in the Boston Lung Cancer Study, using the 5% threshold. Overall survival was significantly worse with increasing VAT loss (P = .0023) and SAT loss (P = .0082) but not with increasing skeletal muscle loss (P = .3).

The investigators speculated about whether the correlation between body composition and clinical outcome could yield clues about tumor biology. To test this, the researchers used the RNA sequencing–based ORACLE risk score in lung cancer patients from TRACERx. There was a high correlation between higher ORACLE risk scores and lower VAT and SAT, suggesting that measures of adiposity on CT were reflected in tumor biology patterns on an RNA level in lung cancer patients. There was no such correlation between ORACLE risk scores and skeletal muscle mass.
 

Wonderment ... tempered by concern and challenges

AI has awe-inspiring potential to yield actionable and prognostically important information from data mining the EHR and extracting the vast quantities of information from images. In some cases (like CAC), it is information that is “hiding in plain sight.” However, Dr. Aerts expressed several cautions, some of which have already plagued AI.

He referenced the Gartner Hype Cycle, which provides a graphic representation of five phases in the life cycle of emerging technologies. The “innovation trigger” is followed by a “peak of inflated expectations,” a “trough of disillusionment,” a “slope of enlightenment,” and a “plateau of productivity.”

Dr. Aerts noted that, in recent years, AI has seemed to fall into the trough of disillusionment, but it may be entering the slope of enlightenment on the way to the plateau of productivity.

His research highlighted several examples of productivity in radiomics in cancer patients and those who are at high risk of developing cancer.

In Dr. Aerts’s opinion, a second concern is replication of AI research results. He noted that, among 400 published studies, only 6% of authors shared the codes that would enable their findings to be corroborated. About 30% shared test data, and 54% shared “pseudocodes,” but transparency and reproducibility are problems for the acceptance and broad implementation of AI.

Dr. Aerts endorsed the Modelhub initiative (www.modelhub.ai), a multi-institutional initiative to advance reproducibility in the AI field and advance its full potential.

However, there are additional concerns about the implementation of radiomics and, more generally, data mining from clinicians’ EHRs to personalize care.

Firstly, it may be laborious and difficult to explain complex, computer-based risk stratification models to patients. Hereditary cancer testing is an example of a risk assessment test that requires complicated explanations that many clinicians relegate to genetics counselors – when patients elect to see them. When a model is not explainable, it undermines the confidence of patients and their care providers, according to an editorial related to the CXR-LC study.

Another issue is that uptake of lung cancer screening, in practice, has been underutilized by individuals who meet current, relatively straightforward Medicare criteria. Despite the apparently better accuracy of the CXR-LC deep-learning model, its complexity and limited access could constitute an additional barrier for the at-risk individuals who should avail themselves of screening.

Furthermore, although age and gender are accurate in most circumstances, there is legitimate concern about the accuracy of, for example, smoking history data and comorbid conditions in current EHRs. Who performs the laborious curation of the input in an AI model to assure its accuracy for individual patients?

Finally, it is unclear how scalable and applicable AI will be to medically underserved populations (e.g., smaller, community-based, free-standing, socioeconomically disadvantaged or rural health care institutions). There are substantial initial and maintenance costs that may limit AI’s availability to some academic institutions and large health maintenance organizations.

As the concerns and challenges are addressed, it will be interesting to see where and when the plateau of productivity for AI in cancer care occurs. When it does, many cancer patients will benefit from enhanced care along the continuum of the complex disease they and their caregivers seek to master.

Dr. Aerts disclosed relationships with Onc.AI outside the presented work.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

A novel drug that offers multilineage protection from chemotherapy-induced myelosuppression has been approved by the Food and Drug Administration.

The drug, trilaciclib (Cosela, G1 Therapeutics) is administered intravenously as a 30-minute infusion within 4 hours prior to the start of chemotherapy. It is indicated specifically for use in adults with extensive-stage small-cell lung cancer (ES-SCLC) who are receiving chemotherapy.

Trilaciclib is a CDK4/6 inhibitor, and this action appears to protect normal bone marrow cells from the harmful effects of chemotherapy.

“For patients with extensive-stage small-cell lung cancer, protecting bone marrow function may help make their chemotherapy safer and allow them to complete their course of treatment on time and according to plan,” Albert Deisseroth, MD, PhD, of the FDA’s Center for Drug Evaluation and Research, said in an FDA press release.
 

First drug of its type

Trilaciclib “is the first and only therapy designed to help protect bone marrow (myeloprotection) when administered prior to treatment with chemotherapy,” according to the drug’s manufacturer.

Myelosuppression is one of the most severe adverse effects of chemotherapy, and it can be life-threatening. It can increase the risk of infection and lead to severe anemia and/or bleeding.

“These complications impact patients’ quality of life and may also result in chemotherapy dose reductions and delays,” Jeffrey Crawford, MD, of Duke Cancer Institute, Durham, N.C., said in a company press release.

“To date, approaches have included the use of growth factor agents to accelerate blood cell recovery after the bone marrow injury has occurred, along with antibiotics and transfusions as needed. By contrast, trilaciclib provides the first proactive approach to myelosuppression through a unique mechanism of action that helps protect the bone marrow from damage by chemotherapy.”
 

Approval based on randomized, placebo-controlled trials

The approval of trilaciclib is based on data from three randomized, double-blind, placebo-controlled studies, involving a total of 245 patients with ES-SCLC.

These patients were being treated with chemotherapy regimens that were based on the combination of carboplatin and etoposide (with or without the immunotherapy atezolizumab) or regimens that were based on topotecan.

Before receiving the chemotherapy, patients were randomly assigned to receive trilaciclib or placebo.

Results showed that patients who had received an infusion of trilaciclib before receiving chemotherapy had a lower chance of developing severe neutropenia compared with patients who received a placebo, the FDA noted. In addition, among the patients who did develop severe neutropenia, this had a shorter duration among patients who received trilaciclib than among those who received placebo.

The most common side effects of trilaciclib were fatigue; low levels of calcium, potassium, and phosphate in the blood; increased levels of aspartate aminotransferase; headache; and pneumonia.

The FDA noted that patients should also be advised about injection site reactions, acute drug hypersensitivity, interstitial lung disease/pneumonitis, and embryo-fetal toxicity.

The approval received a priority review, based on the drug’s breakthrough therapy designation. As is common for such products, the company plans postmarketing activities that will assess the effects of trilaciclib on disease progression or survival with at least a 2-year follow up. This clinical trial is scheduled to start in 2022.

A version of this article first appeared on Medscape.com.

A novel drug that offers multilineage protection from chemotherapy-induced myelosuppression has been approved by the Food and Drug Administration.

The drug, trilaciclib (Cosela, G1 Therapeutics) is administered intravenously as a 30-minute infusion within 4 hours prior to the start of chemotherapy. It is indicated specifically for use in adults with extensive-stage small-cell lung cancer (ES-SCLC) who are receiving chemotherapy.

Trilaciclib is a CDK4/6 inhibitor, and this action appears to protect normal bone marrow cells from the harmful effects of chemotherapy.

“For patients with extensive-stage small-cell lung cancer, protecting bone marrow function may help make their chemotherapy safer and allow them to complete their course of treatment on time and according to plan,” Albert Deisseroth, MD, PhD, of the FDA’s Center for Drug Evaluation and Research, said in an FDA press release.
 

First drug of its type

Trilaciclib “is the first and only therapy designed to help protect bone marrow (myeloprotection) when administered prior to treatment with chemotherapy,” according to the drug’s manufacturer.

Myelosuppression is one of the most severe adverse effects of chemotherapy, and it can be life-threatening. It can increase the risk of infection and lead to severe anemia and/or bleeding.

“These complications impact patients’ quality of life and may also result in chemotherapy dose reductions and delays,” Jeffrey Crawford, MD, of Duke Cancer Institute, Durham, N.C., said in a company press release.

“To date, approaches have included the use of growth factor agents to accelerate blood cell recovery after the bone marrow injury has occurred, along with antibiotics and transfusions as needed. By contrast, trilaciclib provides the first proactive approach to myelosuppression through a unique mechanism of action that helps protect the bone marrow from damage by chemotherapy.”
 

Approval based on randomized, placebo-controlled trials

The approval of trilaciclib is based on data from three randomized, double-blind, placebo-controlled studies, involving a total of 245 patients with ES-SCLC.

These patients were being treated with chemotherapy regimens that were based on the combination of carboplatin and etoposide (with or without the immunotherapy atezolizumab) or regimens that were based on topotecan.

Before receiving the chemotherapy, patients were randomly assigned to receive trilaciclib or placebo.

Results showed that patients who had received an infusion of trilaciclib before receiving chemotherapy had a lower chance of developing severe neutropenia compared with patients who received a placebo, the FDA noted. In addition, among the patients who did develop severe neutropenia, this had a shorter duration among patients who received trilaciclib than among those who received placebo.

The most common side effects of trilaciclib were fatigue; low levels of calcium, potassium, and phosphate in the blood; increased levels of aspartate aminotransferase; headache; and pneumonia.

The FDA noted that patients should also be advised about injection site reactions, acute drug hypersensitivity, interstitial lung disease/pneumonitis, and embryo-fetal toxicity.

The approval received a priority review, based on the drug’s breakthrough therapy designation. As is common for such products, the company plans postmarketing activities that will assess the effects of trilaciclib on disease progression or survival with at least a 2-year follow up. This clinical trial is scheduled to start in 2022.

A version of this article first appeared on Medscape.com.

A novel drug that offers multilineage protection from chemotherapy-induced myelosuppression has been approved by the Food and Drug Administration.

The drug, trilaciclib (Cosela, G1 Therapeutics) is administered intravenously as a 30-minute infusion within 4 hours prior to the start of chemotherapy. It is indicated specifically for use in adults with extensive-stage small-cell lung cancer (ES-SCLC) who are receiving chemotherapy.

Trilaciclib is a CDK4/6 inhibitor, and this action appears to protect normal bone marrow cells from the harmful effects of chemotherapy.

“For patients with extensive-stage small-cell lung cancer, protecting bone marrow function may help make their chemotherapy safer and allow them to complete their course of treatment on time and according to plan,” Albert Deisseroth, MD, PhD, of the FDA’s Center for Drug Evaluation and Research, said in an FDA press release.
 

First drug of its type

Trilaciclib “is the first and only therapy designed to help protect bone marrow (myeloprotection) when administered prior to treatment with chemotherapy,” according to the drug’s manufacturer.

Myelosuppression is one of the most severe adverse effects of chemotherapy, and it can be life-threatening. It can increase the risk of infection and lead to severe anemia and/or bleeding.

“These complications impact patients’ quality of life and may also result in chemotherapy dose reductions and delays,” Jeffrey Crawford, MD, of Duke Cancer Institute, Durham, N.C., said in a company press release.

“To date, approaches have included the use of growth factor agents to accelerate blood cell recovery after the bone marrow injury has occurred, along with antibiotics and transfusions as needed. By contrast, trilaciclib provides the first proactive approach to myelosuppression through a unique mechanism of action that helps protect the bone marrow from damage by chemotherapy.”
 

Approval based on randomized, placebo-controlled trials

The approval of trilaciclib is based on data from three randomized, double-blind, placebo-controlled studies, involving a total of 245 patients with ES-SCLC.

These patients were being treated with chemotherapy regimens that were based on the combination of carboplatin and etoposide (with or without the immunotherapy atezolizumab) or regimens that were based on topotecan.

Before receiving the chemotherapy, patients were randomly assigned to receive trilaciclib or placebo.

Results showed that patients who had received an infusion of trilaciclib before receiving chemotherapy had a lower chance of developing severe neutropenia compared with patients who received a placebo, the FDA noted. In addition, among the patients who did develop severe neutropenia, this had a shorter duration among patients who received trilaciclib than among those who received placebo.

The most common side effects of trilaciclib were fatigue; low levels of calcium, potassium, and phosphate in the blood; increased levels of aspartate aminotransferase; headache; and pneumonia.

The FDA noted that patients should also be advised about injection site reactions, acute drug hypersensitivity, interstitial lung disease/pneumonitis, and embryo-fetal toxicity.

The approval received a priority review, based on the drug’s breakthrough therapy designation. As is common for such products, the company plans postmarketing activities that will assess the effects of trilaciclib on disease progression or survival with at least a 2-year follow up. This clinical trial is scheduled to start in 2022.

A version of this article first appeared on Medscape.com.

Longer-term survival with immunotherapy for patients with non–small cell lung cancer (NSCLC) is once again being applauded by experts in the field.

This time, the data come from trials that tested immunotherapy in the second-line setting for patients who had experienced disease progression with platinum-based chemotherapy. The latest 5-year follow-up from two landmark trials, one with pembrolizumab, the other with nivolumab, show that the survival benefit can persist for years after treatment is stopped.

“These are unprecedented data,” Fred R. Hirsch, MD, PhD, executive director of the Center for Thoracic Oncology at the Tisch Cancer Institute, New York, said in an interview. He was not involved in either trial and was approached for comment.
 

Pembrolizumab survival data

The new longer-term data on pembrolizumab come from the KEYNOTE-010 trial, which included more than 1,000 patients with advanced NSCLC who had previously undergone treatment with platinum-based chemotherapy. The patients were randomly assigned to receive either pembrolizumab or docetaxel for 2 years.

This is the latest update on data from this trial, which has been described as “really extraordinary.”

The 5-year overall survival rates were more than doubled in the pembrolizumab groups, compared with the docetaxel group, reported Roy Herbst, MD, PhD, department of medical oncology, Yale Comprehensive Cancer Center, New Haven, Conn.. He was presenting the new data at the recent World Conference on Lung Cancer 2020.

Overall results for patients with programmed death-ligand 1 (PD-L1) Tumor Proportion Score (TPS) expression greater than 1% show that 15.6% of the pembrolizumab group were still alive at 5 years versus 6.5% of the docetaxel group.

The results were even better among patients who had high PD-L1 TPS expression (>50%): in this subgroup, 25% of the patients who received pembrolizumab were still alive versus 8.2% of those who received docetaxel.

In addition, at 5 years, 9.4% of patients who received pembrolizumab were disease free versus 0.7% of the patients who received docetaxel, Dr. Herbst reported.

Dr. Hirsch commented that the 5-year survival rate of 25% among patients with high PD-L1 expression who underwent treatment with pembrolizumab is “great progress in lung cancer treatment, there is no doubt about it.”

He noted that the results also show that “numerically,” it matters whether patients have low PD-L1 expression. “We know from first-line studies that pembrolizumab monotherapy is effective in high PD-L1–expressing tumors, so these data fit very well,” he said.

At the meeting, Dr. Herbst summarized his presentation on pembrolizumab for patients with NSCLC who had previously undergone treatment, saying that, “with 5 years of follow-up, we continue to see a clinically meaningful improvement in overall survival and PFS [progression-free survival].

“Pembrolizumab monotherapy is a standard of care in patients with immunotherapy-naive or previously treated PD-L1–positive advanced non–small cell lung cancer,” Herbst stated.

Dr. Hirsch was largely in agreement. He believes that, for patients with a PD-L1 TPS of at least 50%, the standard of care “is practically pembrolizumab monotherapy, unless there are certain circumstances where you would add chemotherapy,” such as for patients with a high tumor volume, “where you want to see a very quick response.”

Dr. Hirsch pointed out, however, that currently most patients with high PD-L1–expressing tumors are given pembrolizumab in the first line, which begs the question as to what to give those who experience disease progression after immunotherapy.

“That is an open space,” he said. “There is a lot of studies going on in what we call the immunotherapy-refractory patients.

“We don’t have clear guidance for clinical practice yet,” he commented. He noted that there are several options: “Do you continue with chemotherapy? Do you continue with chemotherapy plus another immunotherapy? Do you switch to another immunotherapy?”

Commenting on Twitter, Stephen V. Liu, MD, director of thoracic oncology at Georgetown University, Washington, said the results were “very exciting.”

However, he wondered whether the results suggest that patients with high PD-L1 expression “may be able to stop” receiving pembrolizumab, whereas those with disease of lower expression “may need longer therapy.”

H. Jack West, MD, medical director of the thoracic oncology program, Swedish Cancer Institute, Seattle, said on Twitter that, to him, the “most impressive” aspect was the “new insight about patients stopping pembro after 2 years but still having two-thirds with sustained response.”

He added that he would “love to learn which patients can stop therapy and when, or whether we can do infrequent maintenance IO [immunotherapy].”

 

Nivolumab survival data

The data on nivolumab come from a pooled analysis of 5-year data on 854 patients from CheckMate 057 and CheckMate 017. The analysis was published in the Journal of Clinical Oncology on Jan. 15, 2021.

Both of these trials compared nivolumab with docetaxel for patients with NSCLC who had experienced disease progression with platinum-based chemotherapy.

The pooled analysis showed that the 5-year overall survival rate was more than fivefold greater with nivolumab than with docetaxel, at 13.4% versus 2.6%.

Moreover, more than 80% of patients who had not experienced progression with the immunotherapy at 2 years were still alive at 5 years. The percentage rose to more than 90% among those who had not experienced progression at 3 years.

Lead author Julie R. Brahmer, MD, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, and colleagues said the results “demonstrate that nivolumab can provide long-term survival benefit with durable responses and a tolerable safety profile in patients with previously treated, advanced NSCLC.

“Furthermore, some patients appear to maintain prolonged disease control even after stopping systemic therapy,” they noted.

Dr. Hirsch commented that, although the survival rates with nivolumab were slightly lower than reported with pembrolizumab in KEYNOTE-010, they could still be “within the range.” He added that “I wouldn’t conclude that pembrolizumab is better than nivolumab.”

Many factors may account for these differences, he suggested, including differences in the patient populations or simply differences in the numbers of patients included.

For him, the “main point” of the new data from both trials is that immunotherapy has shown “tremendous progress, compared to chemotherapy.”

KEYNOTE-010 was sponsored by Merck Sharp & Dohme. CheckMate 017 and CheckMate057 were sponsored by Bristol-Myers Squibb. Dr. Herbst has relationships with Jun Shi Pharmaceuticals, AstraZeneca, Genentech, Merck, Pfizer, AbbVie, Biodesix, Bristol-Myers Squibb, Eli Lilly, EMD Serono, Heat Biologics, Loxo, Nektar, NextCure, Novartis, Sanofi, Seattle Genetics, Shire, Spectrum Pharmaceuticals, Symphogen, Tesaro, Neon Therapeutics, Infinity Pharmaceuticals, Armo Biosciences, Genmab, Halozyme, and Tocagen. Dr. Brahmer has relationships with Roche/Genentech, Bristol-Myers Squibb, Lilly, Celgene, Syndax, Janssen Oncology, Merck, Amgen, Genentech, AstraZeneca, Incyte, Spectrum Pharmaceuticals, Revolution, and Roche/Genentech.

A version of this article first appeared on Medscape.com.

Longer-term survival with immunotherapy for patients with non–small cell lung cancer (NSCLC) is once again being applauded by experts in the field.

This time, the data come from trials that tested immunotherapy in the second-line setting for patients who had experienced disease progression with platinum-based chemotherapy. The latest 5-year follow-up from two landmark trials, one with pembrolizumab, the other with nivolumab, show that the survival benefit can persist for years after treatment is stopped.

“These are unprecedented data,” Fred R. Hirsch, MD, PhD, executive director of the Center for Thoracic Oncology at the Tisch Cancer Institute, New York, said in an interview. He was not involved in either trial and was approached for comment.
 

Pembrolizumab survival data

The new longer-term data on pembrolizumab come from the KEYNOTE-010 trial, which included more than 1,000 patients with advanced NSCLC who had previously undergone treatment with platinum-based chemotherapy. The patients were randomly assigned to receive either pembrolizumab or docetaxel for 2 years.

This is the latest update on data from this trial, which has been described as “really extraordinary.”

The 5-year overall survival rates were more than doubled in the pembrolizumab groups, compared with the docetaxel group, reported Roy Herbst, MD, PhD, department of medical oncology, Yale Comprehensive Cancer Center, New Haven, Conn.. He was presenting the new data at the recent World Conference on Lung Cancer 2020.

Overall results for patients with programmed death-ligand 1 (PD-L1) Tumor Proportion Score (TPS) expression greater than 1% show that 15.6% of the pembrolizumab group were still alive at 5 years versus 6.5% of the docetaxel group.

The results were even better among patients who had high PD-L1 TPS expression (>50%): in this subgroup, 25% of the patients who received pembrolizumab were still alive versus 8.2% of those who received docetaxel.

In addition, at 5 years, 9.4% of patients who received pembrolizumab were disease free versus 0.7% of the patients who received docetaxel, Dr. Herbst reported.

Dr. Hirsch commented that the 5-year survival rate of 25% among patients with high PD-L1 expression who underwent treatment with pembrolizumab is “great progress in lung cancer treatment, there is no doubt about it.”

He noted that the results also show that “numerically,” it matters whether patients have low PD-L1 expression. “We know from first-line studies that pembrolizumab monotherapy is effective in high PD-L1–expressing tumors, so these data fit very well,” he said.

At the meeting, Dr. Herbst summarized his presentation on pembrolizumab for patients with NSCLC who had previously undergone treatment, saying that, “with 5 years of follow-up, we continue to see a clinically meaningful improvement in overall survival and PFS [progression-free survival].

“Pembrolizumab monotherapy is a standard of care in patients with immunotherapy-naive or previously treated PD-L1–positive advanced non–small cell lung cancer,” Herbst stated.

Dr. Hirsch was largely in agreement. He believes that, for patients with a PD-L1 TPS of at least 50%, the standard of care “is practically pembrolizumab monotherapy, unless there are certain circumstances where you would add chemotherapy,” such as for patients with a high tumor volume, “where you want to see a very quick response.”

Dr. Hirsch pointed out, however, that currently most patients with high PD-L1–expressing tumors are given pembrolizumab in the first line, which begs the question as to what to give those who experience disease progression after immunotherapy.

“That is an open space,” he said. “There is a lot of studies going on in what we call the immunotherapy-refractory patients.

“We don’t have clear guidance for clinical practice yet,” he commented. He noted that there are several options: “Do you continue with chemotherapy? Do you continue with chemotherapy plus another immunotherapy? Do you switch to another immunotherapy?”

Commenting on Twitter, Stephen V. Liu, MD, director of thoracic oncology at Georgetown University, Washington, said the results were “very exciting.”

However, he wondered whether the results suggest that patients with high PD-L1 expression “may be able to stop” receiving pembrolizumab, whereas those with disease of lower expression “may need longer therapy.”

H. Jack West, MD, medical director of the thoracic oncology program, Swedish Cancer Institute, Seattle, said on Twitter that, to him, the “most impressive” aspect was the “new insight about patients stopping pembro after 2 years but still having two-thirds with sustained response.”

He added that he would “love to learn which patients can stop therapy and when, or whether we can do infrequent maintenance IO [immunotherapy].”

 

Nivolumab survival data

The data on nivolumab come from a pooled analysis of 5-year data on 854 patients from CheckMate 057 and CheckMate 017. The analysis was published in the Journal of Clinical Oncology on Jan. 15, 2021.

Both of these trials compared nivolumab with docetaxel for patients with NSCLC who had experienced disease progression with platinum-based chemotherapy.

The pooled analysis showed that the 5-year overall survival rate was more than fivefold greater with nivolumab than with docetaxel, at 13.4% versus 2.6%.

Moreover, more than 80% of patients who had not experienced progression with the immunotherapy at 2 years were still alive at 5 years. The percentage rose to more than 90% among those who had not experienced progression at 3 years.

Lead author Julie R. Brahmer, MD, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, and colleagues said the results “demonstrate that nivolumab can provide long-term survival benefit with durable responses and a tolerable safety profile in patients with previously treated, advanced NSCLC.

“Furthermore, some patients appear to maintain prolonged disease control even after stopping systemic therapy,” they noted.

Dr. Hirsch commented that, although the survival rates with nivolumab were slightly lower than reported with pembrolizumab in KEYNOTE-010, they could still be “within the range.” He added that “I wouldn’t conclude that pembrolizumab is better than nivolumab.”

Many factors may account for these differences, he suggested, including differences in the patient populations or simply differences in the numbers of patients included.

For him, the “main point” of the new data from both trials is that immunotherapy has shown “tremendous progress, compared to chemotherapy.”

KEYNOTE-010 was sponsored by Merck Sharp & Dohme. CheckMate 017 and CheckMate057 were sponsored by Bristol-Myers Squibb. Dr. Herbst has relationships with Jun Shi Pharmaceuticals, AstraZeneca, Genentech, Merck, Pfizer, AbbVie, Biodesix, Bristol-Myers Squibb, Eli Lilly, EMD Serono, Heat Biologics, Loxo, Nektar, NextCure, Novartis, Sanofi, Seattle Genetics, Shire, Spectrum Pharmaceuticals, Symphogen, Tesaro, Neon Therapeutics, Infinity Pharmaceuticals, Armo Biosciences, Genmab, Halozyme, and Tocagen. Dr. Brahmer has relationships with Roche/Genentech, Bristol-Myers Squibb, Lilly, Celgene, Syndax, Janssen Oncology, Merck, Amgen, Genentech, AstraZeneca, Incyte, Spectrum Pharmaceuticals, Revolution, and Roche/Genentech.

A version of this article first appeared on Medscape.com.

Longer-term survival with immunotherapy for patients with non–small cell lung cancer (NSCLC) is once again being applauded by experts in the field.

This time, the data come from trials that tested immunotherapy in the second-line setting for patients who had experienced disease progression with platinum-based chemotherapy. The latest 5-year follow-up from two landmark trials, one with pembrolizumab, the other with nivolumab, show that the survival benefit can persist for years after treatment is stopped.

“These are unprecedented data,” Fred R. Hirsch, MD, PhD, executive director of the Center for Thoracic Oncology at the Tisch Cancer Institute, New York, said in an interview. He was not involved in either trial and was approached for comment.
 

Pembrolizumab survival data

The new longer-term data on pembrolizumab come from the KEYNOTE-010 trial, which included more than 1,000 patients with advanced NSCLC who had previously undergone treatment with platinum-based chemotherapy. The patients were randomly assigned to receive either pembrolizumab or docetaxel for 2 years.

This is the latest update on data from this trial, which has been described as “really extraordinary.”

The 5-year overall survival rates were more than doubled in the pembrolizumab groups, compared with the docetaxel group, reported Roy Herbst, MD, PhD, department of medical oncology, Yale Comprehensive Cancer Center, New Haven, Conn.. He was presenting the new data at the recent World Conference on Lung Cancer 2020.

Overall results for patients with programmed death-ligand 1 (PD-L1) Tumor Proportion Score (TPS) expression greater than 1% show that 15.6% of the pembrolizumab group were still alive at 5 years versus 6.5% of the docetaxel group.

The results were even better among patients who had high PD-L1 TPS expression (>50%): in this subgroup, 25% of the patients who received pembrolizumab were still alive versus 8.2% of those who received docetaxel.

In addition, at 5 years, 9.4% of patients who received pembrolizumab were disease free versus 0.7% of the patients who received docetaxel, Dr. Herbst reported.

Dr. Hirsch commented that the 5-year survival rate of 25% among patients with high PD-L1 expression who underwent treatment with pembrolizumab is “great progress in lung cancer treatment, there is no doubt about it.”

He noted that the results also show that “numerically,” it matters whether patients have low PD-L1 expression. “We know from first-line studies that pembrolizumab monotherapy is effective in high PD-L1–expressing tumors, so these data fit very well,” he said.

At the meeting, Dr. Herbst summarized his presentation on pembrolizumab for patients with NSCLC who had previously undergone treatment, saying that, “with 5 years of follow-up, we continue to see a clinically meaningful improvement in overall survival and PFS [progression-free survival].

“Pembrolizumab monotherapy is a standard of care in patients with immunotherapy-naive or previously treated PD-L1–positive advanced non–small cell lung cancer,” Herbst stated.

Dr. Hirsch was largely in agreement. He believes that, for patients with a PD-L1 TPS of at least 50%, the standard of care “is practically pembrolizumab monotherapy, unless there are certain circumstances where you would add chemotherapy,” such as for patients with a high tumor volume, “where you want to see a very quick response.”

Dr. Hirsch pointed out, however, that currently most patients with high PD-L1–expressing tumors are given pembrolizumab in the first line, which begs the question as to what to give those who experience disease progression after immunotherapy.

“That is an open space,” he said. “There is a lot of studies going on in what we call the immunotherapy-refractory patients.

“We don’t have clear guidance for clinical practice yet,” he commented. He noted that there are several options: “Do you continue with chemotherapy? Do you continue with chemotherapy plus another immunotherapy? Do you switch to another immunotherapy?”

Commenting on Twitter, Stephen V. Liu, MD, director of thoracic oncology at Georgetown University, Washington, said the results were “very exciting.”

However, he wondered whether the results suggest that patients with high PD-L1 expression “may be able to stop” receiving pembrolizumab, whereas those with disease of lower expression “may need longer therapy.”

H. Jack West, MD, medical director of the thoracic oncology program, Swedish Cancer Institute, Seattle, said on Twitter that, to him, the “most impressive” aspect was the “new insight about patients stopping pembro after 2 years but still having two-thirds with sustained response.”

He added that he would “love to learn which patients can stop therapy and when, or whether we can do infrequent maintenance IO [immunotherapy].”

 

Nivolumab survival data

The data on nivolumab come from a pooled analysis of 5-year data on 854 patients from CheckMate 057 and CheckMate 017. The analysis was published in the Journal of Clinical Oncology on Jan. 15, 2021.

Both of these trials compared nivolumab with docetaxel for patients with NSCLC who had experienced disease progression with platinum-based chemotherapy.

The pooled analysis showed that the 5-year overall survival rate was more than fivefold greater with nivolumab than with docetaxel, at 13.4% versus 2.6%.

Moreover, more than 80% of patients who had not experienced progression with the immunotherapy at 2 years were still alive at 5 years. The percentage rose to more than 90% among those who had not experienced progression at 3 years.

Lead author Julie R. Brahmer, MD, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, and colleagues said the results “demonstrate that nivolumab can provide long-term survival benefit with durable responses and a tolerable safety profile in patients with previously treated, advanced NSCLC.

“Furthermore, some patients appear to maintain prolonged disease control even after stopping systemic therapy,” they noted.

Dr. Hirsch commented that, although the survival rates with nivolumab were slightly lower than reported with pembrolizumab in KEYNOTE-010, they could still be “within the range.” He added that “I wouldn’t conclude that pembrolizumab is better than nivolumab.”

Many factors may account for these differences, he suggested, including differences in the patient populations or simply differences in the numbers of patients included.

For him, the “main point” of the new data from both trials is that immunotherapy has shown “tremendous progress, compared to chemotherapy.”

KEYNOTE-010 was sponsored by Merck Sharp & Dohme. CheckMate 017 and CheckMate057 were sponsored by Bristol-Myers Squibb. Dr. Herbst has relationships with Jun Shi Pharmaceuticals, AstraZeneca, Genentech, Merck, Pfizer, AbbVie, Biodesix, Bristol-Myers Squibb, Eli Lilly, EMD Serono, Heat Biologics, Loxo, Nektar, NextCure, Novartis, Sanofi, Seattle Genetics, Shire, Spectrum Pharmaceuticals, Symphogen, Tesaro, Neon Therapeutics, Infinity Pharmaceuticals, Armo Biosciences, Genmab, Halozyme, and Tocagen. Dr. Brahmer has relationships with Roche/Genentech, Bristol-Myers Squibb, Lilly, Celgene, Syndax, Janssen Oncology, Merck, Amgen, Genentech, AstraZeneca, Incyte, Spectrum Pharmaceuticals, Revolution, and Roche/Genentech.

A version of this article first appeared on Medscape.com.

New research suggests that proposed lung cancer screening guidelines could inadvertently increase racial and ethnic disparities, but adding in a risk prediction model could reduce some of these disparities by identifying people with high predicted benefit, regardless of race or ethnicity.

The draft United States Preventive Services Task Force (USPSTF) 2020 guidelines recommend annual lung cancer screening for individuals aged 50-80 who currently smoke or quit in the last 15 years, and who have a smoking history equivalent to at least one pack of cigarettes per day for 20 years or more.

This expands the age range and smoking history requirement compared to the 2013 USPSTF recommendations in an attempt to partially ameliorate racial disparities in screening eligibility. The 2013 guidelines recommend screening ever-smokers aged 55-80 with 30 or more pack-years and 15 or fewer quit-years.

However, neither the 2013 nor the 2020 USPSTF recommendations consider the higher risk of lung cancer and younger ages at diagnosis among African Americans, despite their smoking less than Whites, according to Rebecca Landy, PhD, of the National Cancer Institute in Bethesda, Md.

“For the same age and smoking history as Whites, minorities have substantially different lung cancer risk,” Dr. Landy said. “Incorporating individualized prediction models into USPSTF guidelines may reduce racial/ethnic disparities in lung cancer screening eligibility.”

Dr. Landy and colleagues set out to test that theory, and she presented the results at the 2020 World Congress on Lung Cancer (Abstract 3564), which was rescheduled for January 2021. The results were published in the Journal of the National Cancer Institute.
 

Study details

Dr. Landy and colleagues modeled the performance of National Lung Screening Trial–like screening (three annual CT screens, 5 years of follow-up) among three cohorts of ever-smokers aged 50-80 using the 2015 National Health Interview Survey.

One group was eligible by USPSTF 2013 guidelines, another by draft USPSTF 2020 guidelines, and yet another by augmenting the USPSTF 2020 guidelines using risk prediction to include individuals with 12 or more days of life gained according to the Life-Years From Screening–CT (LYFS-CT) model.

“Among each race/ethnicity, we calculated the number eligible for screening, proportion of preventable lung cancer deaths prevented, proportion of gainable life-years gained, and screening effectiveness, as well as the relative disparities in lung cancer deaths prevented and life-years gained,” Dr. Landy said.
 

Results

Under the 2013 guidelines, 8 million ever-smokers were eligible. The disparities in lung cancer death sensitivity, compared to Whites, were 15% for African Americans, 15% for Asian Americans, and 24% for Hispanic Americans. Disparities for life-year gained sensitivity were 15%, 13%, and 24%, respectively.

Under the 2020 draft guidelines, 14.5 million ever-smokers were eligible, but racial/ethnic disparities persisted. Disparities in lung cancer death sensitivity were 13% for African Americans, 19% for Asian Americans, and 27% for Hispanic Americans. Disparities for life-year gained sensitivity were 16%, 19%, and 27%, respectively.

Using the LYFS-CT predictive-risk model added an additional 3.5 million people and “nearly eliminated” disparities for African Americans, Dr. Landy noted. However, disparities persisted for Asian Americans and Hispanic Americans.

Disparities in lung cancer death sensitivity were 0% for African Americans, 19% for Asian Americans, and 23% for Hispanic Americans. Disparities for life-year gained sensitivity were 1%, 19%, and 24%, respectively.
 

More and widening disparity

The results showed that augmenting USPSTF criteria to include high-benefit people selected significantly more African Americans than Whites and could therefore reduce or even eliminate disparities between Whites and African Americans.

“The 2020 USPSTF draft recommendations would make 6.5 million more people eligible to be screened, in addition to the 8 million from the 2013 criteria,” said Gerard Silvestri, MD, of the Medical University of South Carolina, Charleston, who was not involved in this study.

“But there will be more White people than African American people added, and the disparity between them may widen. Using the risk prediction model outlined in this well-researched study could close the gap in disparity. It’s important to identify individual risk and life expectancy.”

Dr. Silvestri pointed out that, compared to Whites, African Americans develop lung cancer at an earlier age with fewer pack-years history of smoking and have worse outcomes.

“We can’t just focus on one aspect of disparity,” he said. “African Americans are much less likely to be insured or to identify a primary care provider for integrated care. We know that screening works. The 2020 USPSTF draft recommendations will enlarge the pool of eligible African Americans and reduce disparities if the other part of the equation holds; that is, they get access to care and screening.”

This study was funded by the National Institutes of Health/National Cancer Institute. Dr. Landy and Dr. Silvestri have no disclosures.

New research suggests that proposed lung cancer screening guidelines could inadvertently increase racial and ethnic disparities, but adding in a risk prediction model could reduce some of these disparities by identifying people with high predicted benefit, regardless of race or ethnicity.

The draft United States Preventive Services Task Force (USPSTF) 2020 guidelines recommend annual lung cancer screening for individuals aged 50-80 who currently smoke or quit in the last 15 years, and who have a smoking history equivalent to at least one pack of cigarettes per day for 20 years or more.

This expands the age range and smoking history requirement compared to the 2013 USPSTF recommendations in an attempt to partially ameliorate racial disparities in screening eligibility. The 2013 guidelines recommend screening ever-smokers aged 55-80 with 30 or more pack-years and 15 or fewer quit-years.

However, neither the 2013 nor the 2020 USPSTF recommendations consider the higher risk of lung cancer and younger ages at diagnosis among African Americans, despite their smoking less than Whites, according to Rebecca Landy, PhD, of the National Cancer Institute in Bethesda, Md.

“For the same age and smoking history as Whites, minorities have substantially different lung cancer risk,” Dr. Landy said. “Incorporating individualized prediction models into USPSTF guidelines may reduce racial/ethnic disparities in lung cancer screening eligibility.”

Dr. Landy and colleagues set out to test that theory, and she presented the results at the 2020 World Congress on Lung Cancer (Abstract 3564), which was rescheduled for January 2021. The results were published in the Journal of the National Cancer Institute.
 

Study details

Dr. Landy and colleagues modeled the performance of National Lung Screening Trial–like screening (three annual CT screens, 5 years of follow-up) among three cohorts of ever-smokers aged 50-80 using the 2015 National Health Interview Survey.

One group was eligible by USPSTF 2013 guidelines, another by draft USPSTF 2020 guidelines, and yet another by augmenting the USPSTF 2020 guidelines using risk prediction to include individuals with 12 or more days of life gained according to the Life-Years From Screening–CT (LYFS-CT) model.

“Among each race/ethnicity, we calculated the number eligible for screening, proportion of preventable lung cancer deaths prevented, proportion of gainable life-years gained, and screening effectiveness, as well as the relative disparities in lung cancer deaths prevented and life-years gained,” Dr. Landy said.
 

Results

Under the 2013 guidelines, 8 million ever-smokers were eligible. The disparities in lung cancer death sensitivity, compared to Whites, were 15% for African Americans, 15% for Asian Americans, and 24% for Hispanic Americans. Disparities for life-year gained sensitivity were 15%, 13%, and 24%, respectively.

Under the 2020 draft guidelines, 14.5 million ever-smokers were eligible, but racial/ethnic disparities persisted. Disparities in lung cancer death sensitivity were 13% for African Americans, 19% for Asian Americans, and 27% for Hispanic Americans. Disparities for life-year gained sensitivity were 16%, 19%, and 27%, respectively.

Using the LYFS-CT predictive-risk model added an additional 3.5 million people and “nearly eliminated” disparities for African Americans, Dr. Landy noted. However, disparities persisted for Asian Americans and Hispanic Americans.

Disparities in lung cancer death sensitivity were 0% for African Americans, 19% for Asian Americans, and 23% for Hispanic Americans. Disparities for life-year gained sensitivity were 1%, 19%, and 24%, respectively.
 

More and widening disparity

The results showed that augmenting USPSTF criteria to include high-benefit people selected significantly more African Americans than Whites and could therefore reduce or even eliminate disparities between Whites and African Americans.

“The 2020 USPSTF draft recommendations would make 6.5 million more people eligible to be screened, in addition to the 8 million from the 2013 criteria,” said Gerard Silvestri, MD, of the Medical University of South Carolina, Charleston, who was not involved in this study.

“But there will be more White people than African American people added, and the disparity between them may widen. Using the risk prediction model outlined in this well-researched study could close the gap in disparity. It’s important to identify individual risk and life expectancy.”

Dr. Silvestri pointed out that, compared to Whites, African Americans develop lung cancer at an earlier age with fewer pack-years history of smoking and have worse outcomes.

“We can’t just focus on one aspect of disparity,” he said. “African Americans are much less likely to be insured or to identify a primary care provider for integrated care. We know that screening works. The 2020 USPSTF draft recommendations will enlarge the pool of eligible African Americans and reduce disparities if the other part of the equation holds; that is, they get access to care and screening.”

This study was funded by the National Institutes of Health/National Cancer Institute. Dr. Landy and Dr. Silvestri have no disclosures.

New research suggests that proposed lung cancer screening guidelines could inadvertently increase racial and ethnic disparities, but adding in a risk prediction model could reduce some of these disparities by identifying people with high predicted benefit, regardless of race or ethnicity.

The draft United States Preventive Services Task Force (USPSTF) 2020 guidelines recommend annual lung cancer screening for individuals aged 50-80 who currently smoke or quit in the last 15 years, and who have a smoking history equivalent to at least one pack of cigarettes per day for 20 years or more.

This expands the age range and smoking history requirement compared to the 2013 USPSTF recommendations in an attempt to partially ameliorate racial disparities in screening eligibility. The 2013 guidelines recommend screening ever-smokers aged 55-80 with 30 or more pack-years and 15 or fewer quit-years.

However, neither the 2013 nor the 2020 USPSTF recommendations consider the higher risk of lung cancer and younger ages at diagnosis among African Americans, despite their smoking less than Whites, according to Rebecca Landy, PhD, of the National Cancer Institute in Bethesda, Md.

“For the same age and smoking history as Whites, minorities have substantially different lung cancer risk,” Dr. Landy said. “Incorporating individualized prediction models into USPSTF guidelines may reduce racial/ethnic disparities in lung cancer screening eligibility.”

Dr. Landy and colleagues set out to test that theory, and she presented the results at the 2020 World Congress on Lung Cancer (Abstract 3564), which was rescheduled for January 2021. The results were published in the Journal of the National Cancer Institute.
 

Study details

Dr. Landy and colleagues modeled the performance of National Lung Screening Trial–like screening (three annual CT screens, 5 years of follow-up) among three cohorts of ever-smokers aged 50-80 using the 2015 National Health Interview Survey.

One group was eligible by USPSTF 2013 guidelines, another by draft USPSTF 2020 guidelines, and yet another by augmenting the USPSTF 2020 guidelines using risk prediction to include individuals with 12 or more days of life gained according to the Life-Years From Screening–CT (LYFS-CT) model.

“Among each race/ethnicity, we calculated the number eligible for screening, proportion of preventable lung cancer deaths prevented, proportion of gainable life-years gained, and screening effectiveness, as well as the relative disparities in lung cancer deaths prevented and life-years gained,” Dr. Landy said.
 

Results

Under the 2013 guidelines, 8 million ever-smokers were eligible. The disparities in lung cancer death sensitivity, compared to Whites, were 15% for African Americans, 15% for Asian Americans, and 24% for Hispanic Americans. Disparities for life-year gained sensitivity were 15%, 13%, and 24%, respectively.

Under the 2020 draft guidelines, 14.5 million ever-smokers were eligible, but racial/ethnic disparities persisted. Disparities in lung cancer death sensitivity were 13% for African Americans, 19% for Asian Americans, and 27% for Hispanic Americans. Disparities for life-year gained sensitivity were 16%, 19%, and 27%, respectively.

Using the LYFS-CT predictive-risk model added an additional 3.5 million people and “nearly eliminated” disparities for African Americans, Dr. Landy noted. However, disparities persisted for Asian Americans and Hispanic Americans.

Disparities in lung cancer death sensitivity were 0% for African Americans, 19% for Asian Americans, and 23% for Hispanic Americans. Disparities for life-year gained sensitivity were 1%, 19%, and 24%, respectively.
 

More and widening disparity

The results showed that augmenting USPSTF criteria to include high-benefit people selected significantly more African Americans than Whites and could therefore reduce or even eliminate disparities between Whites and African Americans.

“The 2020 USPSTF draft recommendations would make 6.5 million more people eligible to be screened, in addition to the 8 million from the 2013 criteria,” said Gerard Silvestri, MD, of the Medical University of South Carolina, Charleston, who was not involved in this study.

“But there will be more White people than African American people added, and the disparity between them may widen. Using the risk prediction model outlined in this well-researched study could close the gap in disparity. It’s important to identify individual risk and life expectancy.”

Dr. Silvestri pointed out that, compared to Whites, African Americans develop lung cancer at an earlier age with fewer pack-years history of smoking and have worse outcomes.

“We can’t just focus on one aspect of disparity,” he said. “African Americans are much less likely to be insured or to identify a primary care provider for integrated care. We know that screening works. The 2020 USPSTF draft recommendations will enlarge the pool of eligible African Americans and reduce disparities if the other part of the equation holds; that is, they get access to care and screening.”

This study was funded by the National Institutes of Health/National Cancer Institute. Dr. Landy and Dr. Silvestri have no disclosures.

Tailoring adjuvant chemotherapy based on the expression of two molecular markers did not confer a survival advantage in patients with completely resected stage II-III non–small cell lung cancer (NSCLC) in a phase 3 trial.

The patients were randomized to receive investigator’s choice of platinum-based chemotherapy or treatment tailored according to messenger RNA (mRNA) expression of two molecular markers – excision repair cross complementation 1 (ERCC1) and thymidylate synthase (TS).

There was no significant difference in overall survival or recurrence-free survival between the treatment approaches. However, toxicity was less common among patients who received customized treatment.

These results, from the phase 3 ITACA trial, were presented at the 2020 World Conference on Lung Cancer (Abstract 1820), which was rescheduled to January 2021.

“There is a clear need to define patients most likely to derive survival benefit from adjuvant therapy and spare patients who do not need adjuvant chemotherapy due to the toxicity of such therapy,” said presenter Silvia Novello, MD, PhD, of the University of Turin in Italy. “mRNA expression of different genes has been correlated with the sensitivity or resistance to specific anticancer agents.”

With this in mind, Dr. Novello and colleagues conducted the ITACA trial. The researchers’ primary goal was to determine whether an adjuvant pharmacogenomic-driven approach was able to improve overall survival in completely resected NSCLC.
 

Patients and treatment

The researchers randomized 773 NSCLC patients within 5-8 weeks after radical surgery. Genomic analyses were performed soon after surgery, and patients were randomly assigned to investigator’s choice of platinum-based chemotherapy or to tailored treatments defined by mRNA levels of ERCC1 and TS.

Patients with high ERCC1 mRNA expression who were randomized to tailored treatment received single-agent docetaxel if their TS level was high or pemetrexed monotherapy if their TS level was low.

Patients with low ERCC1 mRNA expression who were randomized to tailored treatment received cisplatin-gemcitabine if their TS level was high or cisplatin-pemetrexed if their TS was low.

The most frequent doublets used in control patients were cisplatin-gemcitabine and cisplatin-vinorelbine.

The demographic characteristics of the 384 patients randomized to tailored therapy and the 389 control subjects were well-balanced, Dr. Novello said. Two-thirds of patients had stage II disease, 11% were never smokers, and the vast majority had a lobectomy as the resection method.
 

Results

At a median follow-up of 28.2 months, the median overall survival was 96.4 months in the tailored therapy arm and 83.5 months in the control arm. The median recurrence-free survival was 64.4 months and 41.5 months, respectively.

“Adjuvant chemotherapy customization based on the primary tumor tissue mRNA expression of ERCC1 and TS did not significantly improve overall survival or recurrence-free survival,” Dr. Novello said. “There was a non–statistically significant trend for overall survival favoring the customized arm.”

Dr. Novello noted that, when the final analysis was performed, the study was underpowered, as only 46% of expected events were collected. Assuming the same hazard ratio point estimate and that the expected 336 events were collected, the hazard ratio estimate would be 0.76 (P = .012).

Grade 3/4 toxicities occurred in 32.6% of patients in the tailored therapy arm and 45.9% of those in the control arm (P < .001).

“It is important to underline that the treatment customization significantly improved the toxicity profile without compromising the efficacy,” Dr. Novello said.

She added that “more comprehensive and high-throughput diagnostic techniques will be needed in order to tailor adjuvant chemotherapy, with or without immunotherapy, in completely resected NSCLC.”

“The ITACA study is the largest adjuvant study tailored to ERCC1/TS status, and the results have been long-awaited,” said Tetsuya Mitsudomi, MD, a professor at Kindai University in Japan and president of the International Association for the Study of Lung Cancer.

“This trial should be praised for the mandated genomic analysis that was accomplished within a reasonably short time frame before random assignment. In addition, this trial confirmed that there is no biomarker strong enough to predict the efficacy of cytotoxic chemotherapy. However, the concept of customizing adjuvant therapy according to the genomic status of patients’ tumors is valid, leading to the recent demonstration in the ADAURA study of the superiority of osimertinib in delaying the postoperative recurrence of disease in patients with EGFR-mutated NSCLC.”

The ITACA study was funded by University of Turin and Eli Lilly. Dr. Novello disclosed relationships with Eli Lilly, Amgen, AstraZeneca, Bohringer Ingelheim, Beigene, Pfizer, Roche, Merck, Bristol-Myers Squibb, Takeda, and Sanofi. Dr. Mitsudomi disclosed relationships with Eli Lilly, AstraZeneca, Boehringer-Ingelheim, Chugai, Pfizer, Merck, Ono Pharmaceutical, Bristol-Myers Squibb, Novartis, ThermoFisher, Guardant, Eisai, Amgen, and Johnson & Johnson.

Tailoring adjuvant chemotherapy based on the expression of two molecular markers did not confer a survival advantage in patients with completely resected stage II-III non–small cell lung cancer (NSCLC) in a phase 3 trial.

The patients were randomized to receive investigator’s choice of platinum-based chemotherapy or treatment tailored according to messenger RNA (mRNA) expression of two molecular markers – excision repair cross complementation 1 (ERCC1) and thymidylate synthase (TS).

There was no significant difference in overall survival or recurrence-free survival between the treatment approaches. However, toxicity was less common among patients who received customized treatment.

These results, from the phase 3 ITACA trial, were presented at the 2020 World Conference on Lung Cancer (Abstract 1820), which was rescheduled to January 2021.

“There is a clear need to define patients most likely to derive survival benefit from adjuvant therapy and spare patients who do not need adjuvant chemotherapy due to the toxicity of such therapy,” said presenter Silvia Novello, MD, PhD, of the University of Turin in Italy. “mRNA expression of different genes has been correlated with the sensitivity or resistance to specific anticancer agents.”

With this in mind, Dr. Novello and colleagues conducted the ITACA trial. The researchers’ primary goal was to determine whether an adjuvant pharmacogenomic-driven approach was able to improve overall survival in completely resected NSCLC.
 

Patients and treatment

The researchers randomized 773 NSCLC patients within 5-8 weeks after radical surgery. Genomic analyses were performed soon after surgery, and patients were randomly assigned to investigator’s choice of platinum-based chemotherapy or to tailored treatments defined by mRNA levels of ERCC1 and TS.

Patients with high ERCC1 mRNA expression who were randomized to tailored treatment received single-agent docetaxel if their TS level was high or pemetrexed monotherapy if their TS level was low.

Patients with low ERCC1 mRNA expression who were randomized to tailored treatment received cisplatin-gemcitabine if their TS level was high or cisplatin-pemetrexed if their TS was low.

The most frequent doublets used in control patients were cisplatin-gemcitabine and cisplatin-vinorelbine.

The demographic characteristics of the 384 patients randomized to tailored therapy and the 389 control subjects were well-balanced, Dr. Novello said. Two-thirds of patients had stage II disease, 11% were never smokers, and the vast majority had a lobectomy as the resection method.
 

Results

At a median follow-up of 28.2 months, the median overall survival was 96.4 months in the tailored therapy arm and 83.5 months in the control arm. The median recurrence-free survival was 64.4 months and 41.5 months, respectively.

“Adjuvant chemotherapy customization based on the primary tumor tissue mRNA expression of ERCC1 and TS did not significantly improve overall survival or recurrence-free survival,” Dr. Novello said. “There was a non–statistically significant trend for overall survival favoring the customized arm.”

Dr. Novello noted that, when the final analysis was performed, the study was underpowered, as only 46% of expected events were collected. Assuming the same hazard ratio point estimate and that the expected 336 events were collected, the hazard ratio estimate would be 0.76 (P = .012).

Grade 3/4 toxicities occurred in 32.6% of patients in the tailored therapy arm and 45.9% of those in the control arm (P < .001).

“It is important to underline that the treatment customization significantly improved the toxicity profile without compromising the efficacy,” Dr. Novello said.

She added that “more comprehensive and high-throughput diagnostic techniques will be needed in order to tailor adjuvant chemotherapy, with or without immunotherapy, in completely resected NSCLC.”

“The ITACA study is the largest adjuvant study tailored to ERCC1/TS status, and the results have been long-awaited,” said Tetsuya Mitsudomi, MD, a professor at Kindai University in Japan and president of the International Association for the Study of Lung Cancer.

“This trial should be praised for the mandated genomic analysis that was accomplished within a reasonably short time frame before random assignment. In addition, this trial confirmed that there is no biomarker strong enough to predict the efficacy of cytotoxic chemotherapy. However, the concept of customizing adjuvant therapy according to the genomic status of patients’ tumors is valid, leading to the recent demonstration in the ADAURA study of the superiority of osimertinib in delaying the postoperative recurrence of disease in patients with EGFR-mutated NSCLC.”

The ITACA study was funded by University of Turin and Eli Lilly. Dr. Novello disclosed relationships with Eli Lilly, Amgen, AstraZeneca, Bohringer Ingelheim, Beigene, Pfizer, Roche, Merck, Bristol-Myers Squibb, Takeda, and Sanofi. Dr. Mitsudomi disclosed relationships with Eli Lilly, AstraZeneca, Boehringer-Ingelheim, Chugai, Pfizer, Merck, Ono Pharmaceutical, Bristol-Myers Squibb, Novartis, ThermoFisher, Guardant, Eisai, Amgen, and Johnson & Johnson.

Tailoring adjuvant chemotherapy based on the expression of two molecular markers did not confer a survival advantage in patients with completely resected stage II-III non–small cell lung cancer (NSCLC) in a phase 3 trial.

The patients were randomized to receive investigator’s choice of platinum-based chemotherapy or treatment tailored according to messenger RNA (mRNA) expression of two molecular markers – excision repair cross complementation 1 (ERCC1) and thymidylate synthase (TS).

There was no significant difference in overall survival or recurrence-free survival between the treatment approaches. However, toxicity was less common among patients who received customized treatment.

These results, from the phase 3 ITACA trial, were presented at the 2020 World Conference on Lung Cancer (Abstract 1820), which was rescheduled to January 2021.

“There is a clear need to define patients most likely to derive survival benefit from adjuvant therapy and spare patients who do not need adjuvant chemotherapy due to the toxicity of such therapy,” said presenter Silvia Novello, MD, PhD, of the University of Turin in Italy. “mRNA expression of different genes has been correlated with the sensitivity or resistance to specific anticancer agents.”

With this in mind, Dr. Novello and colleagues conducted the ITACA trial. The researchers’ primary goal was to determine whether an adjuvant pharmacogenomic-driven approach was able to improve overall survival in completely resected NSCLC.
 

Patients and treatment

The researchers randomized 773 NSCLC patients within 5-8 weeks after radical surgery. Genomic analyses were performed soon after surgery, and patients were randomly assigned to investigator’s choice of platinum-based chemotherapy or to tailored treatments defined by mRNA levels of ERCC1 and TS.

Patients with high ERCC1 mRNA expression who were randomized to tailored treatment received single-agent docetaxel if their TS level was high or pemetrexed monotherapy if their TS level was low.

Patients with low ERCC1 mRNA expression who were randomized to tailored treatment received cisplatin-gemcitabine if their TS level was high or cisplatin-pemetrexed if their TS was low.

The most frequent doublets used in control patients were cisplatin-gemcitabine and cisplatin-vinorelbine.

The demographic characteristics of the 384 patients randomized to tailored therapy and the 389 control subjects were well-balanced, Dr. Novello said. Two-thirds of patients had stage II disease, 11% were never smokers, and the vast majority had a lobectomy as the resection method.
 

Results

At a median follow-up of 28.2 months, the median overall survival was 96.4 months in the tailored therapy arm and 83.5 months in the control arm. The median recurrence-free survival was 64.4 months and 41.5 months, respectively.

“Adjuvant chemotherapy customization based on the primary tumor tissue mRNA expression of ERCC1 and TS did not significantly improve overall survival or recurrence-free survival,” Dr. Novello said. “There was a non–statistically significant trend for overall survival favoring the customized arm.”

Dr. Novello noted that, when the final analysis was performed, the study was underpowered, as only 46% of expected events were collected. Assuming the same hazard ratio point estimate and that the expected 336 events were collected, the hazard ratio estimate would be 0.76 (P = .012).

Grade 3/4 toxicities occurred in 32.6% of patients in the tailored therapy arm and 45.9% of those in the control arm (P < .001).

“It is important to underline that the treatment customization significantly improved the toxicity profile without compromising the efficacy,” Dr. Novello said.

She added that “more comprehensive and high-throughput diagnostic techniques will be needed in order to tailor adjuvant chemotherapy, with or without immunotherapy, in completely resected NSCLC.”

“The ITACA study is the largest adjuvant study tailored to ERCC1/TS status, and the results have been long-awaited,” said Tetsuya Mitsudomi, MD, a professor at Kindai University in Japan and president of the International Association for the Study of Lung Cancer.

“This trial should be praised for the mandated genomic analysis that was accomplished within a reasonably short time frame before random assignment. In addition, this trial confirmed that there is no biomarker strong enough to predict the efficacy of cytotoxic chemotherapy. However, the concept of customizing adjuvant therapy according to the genomic status of patients’ tumors is valid, leading to the recent demonstration in the ADAURA study of the superiority of osimertinib in delaying the postoperative recurrence of disease in patients with EGFR-mutated NSCLC.”

The ITACA study was funded by University of Turin and Eli Lilly. Dr. Novello disclosed relationships with Eli Lilly, Amgen, AstraZeneca, Bohringer Ingelheim, Beigene, Pfizer, Roche, Merck, Bristol-Myers Squibb, Takeda, and Sanofi. Dr. Mitsudomi disclosed relationships with Eli Lilly, AstraZeneca, Boehringer-Ingelheim, Chugai, Pfizer, Merck, Ono Pharmaceutical, Bristol-Myers Squibb, Novartis, ThermoFisher, Guardant, Eisai, Amgen, and Johnson & Johnson.