Colorectal Cancer Characteristics and Mortality From Propensity Score-Matched Cohorts of Urban and Rural Veterans

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Colorectal Cancer Characteristics and Mortality From Propensity Score-Matched Cohorts of Urban and Rural Veterans

Author(s)
Minh Anh Le, MD
Po-Hong Liu, MD
Amar Mandalia, MD
Sergio Romero, PhD
Ishak A. Mansi, MD
Moheb Boktor, MD

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths in the United States, with an estimated 52,550 deaths in 2023.1 However, the disease burden varies among different segments of the population.2 While both CRC incidence and mortality have been decreasing due to screening and advances in treatment, there are disparities in incidence and mortality across the sociodemographic spectrum including race, ethnicity, education, and income.1-4 While CRC incidence is decreasing for older adults, it is increasing among those aged < 55 years.5 The incidence of CRC in adults aged 40 to 54 years has increased by 0.5% to 1.3% annually since the mid-1990s.6 The US Preventive Services Task Force now recommends starting CRC screening at age 45 years for asymptomatic adults with average risk.7

Disparities also exist across geographical boundaries and living environment. Rural Americans faces additional challenges in health and lifestyle that can affect CRC outcomes. Compared to their urban counterparts, rural residents are more likely to be older, have lower levels of education, higher levels of poverty, lack health insurance, and less access to health care practitioners (HCPs).8-10 Geographic proximity, defined as travel time or physical distance to a health facility, has been recognized as a predictor of inferior outcomes.11 These aspects of rural living may pose challenges for accessing care for CRC screening and treatment.11-13 National and local studies have shown disparities in CRC screening rates, incidence, and mortality between rural and urban populations.14-16

It is unclear whether rural/urban disparities persist under the Veterans Health Administration (VHA) health care delivery model. This study examined differences in baseline characteristics and mortality between rural and urban veterans newly diagnosed with CRC. We also focused on a subpopulation aged ≤ 45 years.

Methods

This study extracted national data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) hosted in the VA Informatics and Computing Infrastructure (VINCI) environment. VINCI is an initiative to improve access to VA data and facilitate the analysis of these data while ensuring veterans’ privacy and data security.17 CDW is the VHA business intelligence information repository, which extracts data from clinical and nonclinical sources following prescribed and validated protocols. Data extracted included demographics, diagnosis, and procedure codes for both inpatient and outpatient encounters, vital signs, and vital status. This study used data previously extracted from a national cohort of veterans that encompassed all patients who received a group of commonly prescribed medications, such as statins, proton pump inhibitors, histamine-2 blockers, acetaminophen-containing products, and hydrocortisone-containing skin applications. This cohort encompassed 8,648,754 veterans, from whom 2,460,727 had encounters during fiscal years (FY) 2016 to 2021 (study period). The cohort was used to ensure that subjects were VHA patients, allowing them to adequately capture their clinical profiles.

Patients were identified as rural or urban based on their residence address at the date of their first diagnosis of CRC. The Geospatial Service Support Center (GSSC) aggregates and updates veterans’ residence address records for all enrolled veterans from the National Change of Address database. The data contain 1 record per enrollee. GSSC Geocoded Enrollee File contains enrollee addresses and their rurality indicators, categorized as urban, rural, or highly rural.18 Rurality is defined by the Rural Urban Commuting Area (RUCA) categories developed by the Department of Agriculture and the Health Resources and Services Administration of the US Department of Health and Human Services.19 Urban areas had RUCA codes of 1.0 to 1.1, and highly rural areas had RUCA scores of 10.0. All other areas were classified as rural. Since the proportion of veterans from highly rural areas was small, we included residents from highly rural areas in the rural residents’ group.

Inclusion and Exclusion Criteria

All veterans newly diagnosed with CRC from FY 2016 to 2021 were included. We used the ninth and tenth clinical modification revisions of the International Classification of Diseases (ICD-9-CM and ICD-10-CM) to define CRC diagnosis (Supplemental materials).4,20 To ensure that patients were newly diagnosed with CRC, this study excluded patients with a previous ICD-9-CM code for CRC diagnosis since FY 2003.

Comorbidities were identified using diagnosis and procedure codes from inpatient and outpatient encounters, which were used to calculate the Charlson Comorbidity Index (CCI) at the time of CRC diagnosis using the weighted method described by Schneeweiss et al.21 We defined CRC high-risk conditions and CRC screening tests, including flexible sigmoidoscopy and stool tests, as described in previous studies (Supplemental materials).20

The main outcome was total mortality. The date of death was extracted from the VHA Death Ascertainment File, which contains mortality data from the Master Person Index file in CDW and the Social Security Administration Death Master File. We used the date of death from any cause, as cause of death was not available.

A propensity score (PS) was created to match rural (including highly rural) and urban residents at a ratio of 1:1. Using a standard procedure described in prior publications, multivariable logistic regression used all baseline characteristics to estimate the PS and perform nearest-number matching without replacement.22,23 A caliper of 0.01 maximized the matched cohort size and achieved balance (Supplemental materials). We then examined the balance of baseline characteristics between PS-matched groups.

Analyses

Cox proportional hazards regression analysis estimated the hazard ratio (HR) of death in rural residents compared to urban residents in the PS-matched cohort. The outcome event was the date of death during the study’s follow-up period (defined as period from first CRC diagnosis to death or study end), with censoring at the study’s end date (September 30, 2021). The proportional hazards assumption was assessed by inspecting the Kaplan-Meier curves. Multiple analyses examined the HR of total mortality in the PS-matched cohort, stratified by sex, race, and ethnicity. We also examined the HR of total mortality stratified by duration of follow-up.

Another PS-matching analysis among veterans aged ≤ 45 years was performed using the same techniques described earlier in this article. We performed a Cox proportional hazards regression analysis to compare mortality in PS-matched urban and rural veterans aged ≤ 45 years. The HR of death in all veterans aged ≤ 45 years (before PS-matching) was estimated using Cox proportional hazard regression analysis, adjusting for PS.

Dichotomous variables were compared using X2 tests and continuous variables were compared using t tests. Baseline characteristics with missing values were converted into categorical variables and the proportion of subjects with missing values was equalized between treatment groups after PS-matching. For subgroup analysis, we examined the HR of total mortality in each subgroup using separate Cox proportional hazards regression models similar to the primary analysis but adjusted for PS. Due to multiple comparisons in the subgroup analysis, the findings should be considered exploratory. Statistical tests were 2-tailed, and significance was defined as P < .05. Data management and statistical analyses were conducted from June 2022 to January 2023 using STATA, Version 17. The VA Orlando Healthcare System Institutional Review Board approved the study and waived requirements for informed consent because only deidentified data were used.

Results

After excluding 49 patients (Supplemental materials, available at doi:10.12788/fp.0560), we identified 30,219 veterans with newly diagnosed CRC between FY 2016 to 2021 (Table 1). Of these, 19,422 (64.3%) resided in urban areas and 10,797 (35.7%) resided in rural areas (Table 2). The mean (SD) duration from the first CRC diagnosis to death or study end was 832 (640) days, and the median (IQR) was 723 (246–1330) days. Overall, incident CRC diagnoses were numerically highest in FY 2016 and lowest in FY 2020 (Figure 1). Patients with CRC in rural areas vs urban areas were significantly older (mean, 71.2 years vs 70.8 years, respectively; P < .001), more likely to be male (96.7% vs 95.7%, respectively; P < .001), more likely to be White (83.6% vs 67.8%, respectively; P < .001) and more likely to be non-Hispanic (92.2% vs 87.5%, respectively; P < .001). In terms of general health, rural veterans with CRC were more likely to be overweight or obese (81.5% rural vs 78.5% urban; P < .001) but had fewer mean comorbidities as measured by CCI (5.66 rural vs 5.90 urban; P < .001). A higher proportion of rural veterans with CRC had received stool-based (fecal occult blood test or fecal immunochemical test) CRC screening tests (61.6% rural vs 57.2% urban; P < .001). Fewer rural patients presented with systemic symptoms or signs within 1 year of CRC diagnosis (54.4% rural vs 57.5% urban, P < .001). Among urban patients with CRC, 6959 (35.8%) deaths were observed, compared with 3766 (34.9%) among rural patients (P = .10).

0525FED-AVAHO-CRC_T10525FED-AVAHO-CRC_T20525FED-AVAHO-CRC_F1

There were 21,568 PS-matched veterans: 10,784 in each group. In the PS-matched cohort, baseline characteristics were similar between veterans in urban and rural communities, including age, sex, race/ethnicity, body mass index, and comorbidities. Among rural patients with CRC, 3763 deaths (34.9%) were observed compared with 3702 (34.3%) among urban veterans. There was no significant difference in the HR of mortality between rural and urban CRC residents (HR, 1.01; 95% CI, 0.97-1.06; P = .53) (Figure 2).

0525FED-AVAHO-CRC_F20525FED-AVAHO-CRC_F30525FED-AVAHO-CRC_F4

Among veterans aged ≤ 45 years, 551 were diagnosed with CRC (391 urban and 160 rural). We PS-matched 142 pairs of urban and rural veterans without residual differences in baseline characteristics (eAppendix 1). There was no significant difference in the HR of mortality between rural and urban veterans aged ≤ 45 years (HR, 0.97; 95% CI, 0.57-1.63; P = .90) (Figure 2). Similarly, no difference in mortality was observed adjusting for PS between all rural and urban veterans aged ≤ 45 years (HR, 1.03; 95% CI, 0.67-1.59; P = .88).

0525FED-AVAHO-CRC_eApp1

There was no difference in total mortality between rural and urban veterans in any subgroup except for American Indian or Alaska Native veterans (HR, 2.41; 95% CI, 1.29-4.50; P = .006) (eAppendix 2).

0525FED-AVAHO-CRC_eApp2

Discussion

This study examined characteristics of patients with CRC between urban and rural areas among veterans who were VHA patients. Similar to other studies, rural veterans with CRC were older, more likely to be White, and were obese, but exhibited fewer comorbidities (lower CCI and lower incidence of congestive heart failure, dementia, hemiplegia, kidney diseases, liver diseases and AIDS, but higher incidence of chronic obstructive lung disease).8,16 The incidence of CRC in this study population was lowest in FY 2020, which was reported by the Centers for Disease Control and Prevention and is attributed to COVID-19 pandemic disruption of health services.24 The overall mortality in this study was similar to rates reported in other studies from the VA Central Cancer Registry.4 In the PS-matched cohort, where baseline characteristics were similar between urban and rural patients with CRC, we found no disparities in CRC-specific mortality between veterans in rural and urban areas. Additionally, when analysis was restricted to veterans aged ≤ 45 years, the results remained consistent.

Subgroup analyses showed no significant difference in mortality between rural and urban areas by sex, race or ethnicity, except rural American Indian or Alaska Native veterans who had double the mortality of their urban counterparts (HR, 2.41; 95% CI, 1.29-4.50; P = .006). This finding is difficult to interpret due to the small number of events and the wide CI. While with a Bonferroni correction the adjusted P value was .08, which is not statistically significant, a previous study found that although CRC incidence was lower overall in American Indian or Alaska Native populations compared to non-Hispanic White populations, CRC incidence was higher among American Indian or Alaska Native individuals in some areas such as Alaska and the Northern Plains.25,26 Studies have noted that rural American Indian/Alaska Native populations experience greater poverty, less access to broadband internet, and limited access to care, contributing to poorer cancer outcomes and lower survival.27 Thus, the finding of disparity in mortality between rural and urban American Indian or Alaska Native veterans warrants further study.

Other studies have raised concerns that CRC disproportionately affects adults in rural areas with higher mortality rates.14-16 These disparities arise from sociodemographic factors and modifiable risk factors, including physical activity, dietary patterns, access to cancer screening, and gaps in quality treatment resources.16,28 These factors operate at multiple levels: from individual, local health system, to community and policy.2,27 For example, a South Carolina study (1996–2016) found that residents in rural areas were more likely to be diagnosed with advanced CRC, possibly indicating lower rates of CRC screening in rural areas. They also had higher likelihood of death from CRC.15 However, the study did not include any clinical parameters, such as comorbidities or obesity. A statewide, population-based study in Utah showed that rural men experienced a lower CRC survival in their unadjusted analysis.16 However, the study was small, with only 3948 urban and 712 rural residents. Additionally, there was no difference in total mortality in the whole cohort (HR, 0.96; 95% CI, 0.86-1.07) or in CRC-specific death (HR, 0.93; 95% CI, 0.81-1.08). A nationwide study also showed that CRC mortality rates were 8% higher in nonmetropolitan or rural areas than in the most urbanized areas containing large metropolitan counties.29 However, this study did not include descriptions of clinical confounders, such as comorbidities, making it difficult to ascertain whether the difference in CRC mortality was due to rurality or differences in baseline risk characteristics.

In this study, the lack of CRC-specific mortality disparities may be attributed to the structures and practices of VHA health care. Recent studies have noted that mortality of several chronic medical conditions treated at the VHA was lower than at non-VHA hospitals.30,31 One study that measured the quality of nonmetastatic CRC care based on National Comprehensive Cancer Network guidelines showed that > 72% of VHA patients received guideline-concordant care for each diagnostic and therapeutic measure, except for follow-up colonoscopy timing, which appear to be similar or superior to that of the private sector.30,32,33 Some of the VA initiative for CRC screening may bypass the urban-rurality divide such as the mailed fecal immunochemical test program for CRC. This program was implemented at the onset of the COVID-19 pandemic to avoid disruptions of medical care.34 Rural patients are more likely to undergo fecal immunochemical testing when compared to urban patients in this data. Beyond clinical care, the VHA uses processes to tackle social determinants of health such as housing, food security, and transportation, promoting equal access to health care, and promoting cultural competency among HCPs.35-37

The results suggest that solutions to CRC disparities between rural and urban areas need to consider known barriers to rural health care, including transportation, diminished rural health care workforce, and other social determinants of health.9,10,27,38 VHA makes considerable efforts to provide equitable care to all enrolled veterans, including specific programs for rural veterans, including ongoing outreach.39 This study demonstrated lack of disparity in CRC-specific mortality in veterans receiving VHA care, highlighting the importance of these efforts.

Strengths and Limitations

This study used the VHA cohort to compare patient characteristics and mortality between patients with CRC residing in rural and urban areas. The study provides nationwide perspectives on CRC across the geographical spectrum and used a longitudinal cohort with prolonged follow-up to account for comorbidities.

However, the study compared a cohort of rural and urban veterans enrolled in the VHA; hence, the results may not reflect CRC outcomes in veterans without access to VHA care. Rurality has been independently associated with decreased likelihood of meeting CRC screening guidelines among veterans and military service members.38 This study lacked sufficient information to compare CRC staging or treatment modalities among veterans. Although the data cannot identify CRC stage, the proportions of patients with metastatic CRC at diagnosis and CRC location were similar between groups. The study did not have information on their care outside of VHA setting.

This study could not ascertain whether disparities existed in CRC treatment modality since rural residence may result in referral to community-based CRC care, which did not appear in the data. To address these limitations, we used death from any cause as the primary outcome, since death is a hard outcome and is not subject to ascertainment bias. The relatively short follow-up time is another limitation, though subgroup analysis by follow-up did not show significant differences. Despite PS matching, residual unmeasured confounding may exist between urban and rural groups. The predominantly White, male VHA population with high CCI may limit the generalizability of the results.

Conclusions

Rural VHA enrollees had similar survival rates after CRC diagnosis compared to their urban counterparts in a PS-matched analysis. The VHA models of care—including mailed CRC screening tools, several socioeconomic determinants of health (housing, food security, and transportation), and promoting equal access to health care, as well as cultural competency among HCPs—HCPs—may help alleviate disparities across the rural-urban spectrum. The VHA should continue efforts to enroll veterans and provide comprehensive coordinated care in community partnerships.

References
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  11. Aboagye JK, Kaiser HE, Hayanga AJ. Rural-urban differences in access to specialist providers of colorectal cancer care in the United States: a physician workforce issue. JAMA Surg. 2014;149(6):537-543. doi:10.1001/jamasurg.2013.5062
  12. Lyckholm LJ, Hackney MH, Smith TJ. Ethics of rural health care. Crit Rev Oncol Hematol. 2001;40(2):131-138. doi:10.1016/s1040-8428(01)00139-1
  13. Krieger N, Williams DR, Moss NE. Measuring social class in US public health research: concepts, methodologies, and guidelines. Annu Rev Public Health. 1997;18:341-378. doi:10.1146/annurev.publhealth.18.1.341
  14. Singh GK, Jemal A. Socioeconomic and racial/ethnic disparities in cancer mortality, incidence, and survival in the United States, 1950-2014: over six decades of changing patterns and widening inequalities. J Environ Public Health. 2017;2017:2819372. doi:10.1155/2017/2819372
  15. Adams SA, Zahnd WE, Ranganathan R, et al. Rural and racial disparities in colorectal cancer incidence and mortality in South Carolina, 1996 - 2016. J Rural Health. 2022;38(1):34-39. doi:10.1111/jrh.12580
  16. Rogers CR, Blackburn BE, Huntington M, et al. Rural- urban disparities in colorectal cancer survival and risk among men in Utah: a statewide population-based study. Cancer Causes Control. 2020;31(3):241-253. doi:10.1007/s10552-020-01268-2
  17. US Department of Veterans Affairs. VA Informatics and Computing Infrastructure (VINCI), VA HSR RES 13-457. https://vincicentral.vinci.med.va.gov [Source not verified]
  18. US Department of Veterans Affairs Information Resource Center. VIReC Research User Guide: PSSG Geocoded Enrollee Files, 2015 Edition. US Department of Veterans Affairs, Health Services Research & Development Service, Information Resource Center; May. 2016. [source not verified]
  19. Goldsmith HF, Puskin DS, Stiles DJ. Improving the operational definition of “rural areas” for federal programs. US Department of Health and Human Services; 1993. Accessed February 27, 2025. https://www.ruralhealthinfo.org/pdf/improving-the-operational-definition-of-rural-areas.pdf
  20. Adams MA, Kerr EA, Dominitz JA, et al. Development and validation of a new ICD-10-based screening colonoscopy overuse measure in a large integrated healthcare system: a retrospective observational study. BMJ Qual Saf. 2023;32(7):414-424. doi:10.1136/bmjqs-2021-014236
  21. Schneeweiss S, Wang PS, Avorn J, Glynn RJ. Improved comorbidity adjustment for predicting mortality in Medicare populations. Health Serv Res. 2003;38(4):1103-1120. doi:10.1111/1475-6773.00165
  22. Becker S, Ichino A. Estimation of average treatment effects based on propensity scores. The Stata Journal. 2002;2(4):358-377.
  23. Leuven E, Sianesi B. PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical software components. Revised February 1, 2018. Accessed February 27, 2025. https://ideas.repec.org/c/boc/bocode/s432001.html.
  24. US Cancer Statistics Working Group. US cancer statistics data visualizations tool. Centers for Disease Control and Prevention. June 2024. Accessed February 27, 2025. https://www.cdc.gov/cancer/dataviz
  25. Cao J, Zhang S. Multiple Comparison Procedures. JAMA. 2014;312(5):543-544. doi:10.1001/jama.2014.9440
  26. Gopalani SV, Janitz AE, Martinez SA, et al. Trends in cancer incidence among American Indians and Alaska Natives and Non-Hispanic Whites in the United States, 1999-2015. Epidemiology. 2020;31(2):205-213. doi:10.1097/EDE.0000000000001140
  27. Zahnd WE, Murphy C, Knoll M, et al. The intersection of rural residence and minority race/ethnicity in cancer disparities in the United States. Int J Environ Res Public Health. 2021;18(4). doi:10.3390/ijerph18041384
  28. Blake KD, Moss JL, Gaysynsky A, Srinivasan S, Croyle RT. Making the case for investment in rural cancer control: an analysis of rural cancer incidence, mortality, and funding trends. Cancer Epidemiol Biomarkers Prev. 2017;26(7):992-997. doi:10.1158/1055-9965.EPI-17-0092
  29. Singh GK, Williams SD, Siahpush M, Mulhollen A. Socioeconomic, rural-urban, and racial inequalities in US cancer mortality: part i-all cancers and lung cancer and part iicolorectal, prostate, breast, and cervical cancers. J Cancer Epidemiol. 2011;2011:107497. doi:10.1155/2011/107497
  30. Jackson GL, Melton LD, Abbott DH, et al. Quality of nonmetastatic colorectal cancer care in the Department of Veterans Affairs. J Clin Oncol. 2010;28(19):3176-3181. doi:10.1200/JCO.2009.26.7948
  31. Yoon J, Phibbs CS, Ong MK, et al. Outcomes of veterans treated in Veterans Affairs hospitals vs non-Veterans Affairs hospitals. JAMA Netw Open. 2023;6(12):e2345898. doi:10.1001/jamanetworkopen.2023.45898
  32. Malin JL, Schneider EC, Epstein AM, Adams J, Emanuel EJ, Kahn KL. Results of the National Initiative for Cancer Care Quality: how can we improve the quality of cancer care in the United States? J Clin Oncol. 2006;24(4):626-634. doi:10.1200/JCO.2005.03.3365
  33. Levin B, Lieberman DA, McFarland B, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. Gastroenterology. 2008;134(5):1570-1595. doi:10.1053/j.gastro.2008.02.002
  34. Deeds SA, Moore CB, Gunnink EJ, et al. Implementation of a mailed faecal immunochemical test programme for colorectal cancer screening among Veterans. BMJ Open Qual. 2022;11(4). doi:10.1136/bmjoq-2022-001927
  35. Yehia BR, Greenstone CL, Hosenfeld CB, Matthews KL, Zephyrin LC. The role of VA community care in addressing health and health care disparities. Med Care. 2017;55(Suppl 9 suppl 2):S4-S5. doi:10.1097/MLR.0000000000000768
  36. Wright BN, MacDermid Wadsworth S, Wellnitz A, Eicher- Miller HA. Reaching rural veterans: a new mechanism to connect rural, low-income US Veterans with resources and improve food security. J Public Health (Oxf). 2019;41(4):714-723. doi:10.1093/pubmed/fdy203
  37. Nelson RE, Byrne TH, Suo Y, et al. Association of temporary financial assistance with housing stability among US veterans in the supportive services for veteran families program. JAMA Netw Open. 2021;4(2):e2037047. doi:10.1001/jamanetworkopen.2020.37047
  38. McDaniel JT, Albright D, Lee HY, et al. Rural–urban disparities in colorectal cancer screening among military service members and Veterans. J Mil Veteran Fam Health. 2019;5(1):40-48. doi:10.3138/jmvfh.2018-0013
  39. US Department of Veterans Affairs, Office of Rural Health. The rural veteran outreach toolkit. Updated February 12, 2025. Accessed February 18, 2025. https://www.ruralhealth.va.gov/partners/toolkit.asp
Article PDF
0525FED AVAHO Colorectal Cancer_0.pdf
Author and Disclosure Information

Minh Anh Le, MDa; Po-Hong Liu, MDb; Amar Mandalia, MDc; Sergio Romero, MDd; Ishak A. Mansi, MDa,c; Moheb Boktor, MDb

Author affiliations: 
aUniversity of Central Florida, Orlando 
bUniversity of Texas Southwestern Medical Center, Dallas 
cOrlando Veterans Affairs Medical Center, Florida 
dNorth Florida/South Georgia Veterans Health System, Gainesville

Author disclosures: The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ishak Mansi (ishak.mansi@va.gov)

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0560

Issue
Federal Practitioner - 42(5)s
Publications
Federal Practitioner
AVAHO
Topics
Colorectal Cancer
Oncology
Page Number
S22-S31
Sections
Original Research
Author(s)
Minh Anh Le, MD
Po-Hong Liu, MD
Amar Mandalia, MD
Sergio Romero, PhD
Ishak A. Mansi, MD
Moheb Boktor, MD
Author(s)
Minh Anh Le, MD
Po-Hong Liu, MD
Amar Mandalia, MD
Sergio Romero, PhD
Ishak A. Mansi, MD
Moheb Boktor, MD
Author and Disclosure Information

Minh Anh Le, MDa; Po-Hong Liu, MDb; Amar Mandalia, MDc; Sergio Romero, MDd; Ishak A. Mansi, MDa,c; Moheb Boktor, MDb

Author affiliations: 
aUniversity of Central Florida, Orlando 
bUniversity of Texas Southwestern Medical Center, Dallas 
cOrlando Veterans Affairs Medical Center, Florida 
dNorth Florida/South Georgia Veterans Health System, Gainesville

Author disclosures: The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ishak Mansi (ishak.mansi@va.gov)

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0560

Author and Disclosure Information

Minh Anh Le, MDa; Po-Hong Liu, MDb; Amar Mandalia, MDc; Sergio Romero, MDd; Ishak A. Mansi, MDa,c; Moheb Boktor, MDb

Author affiliations: 
aUniversity of Central Florida, Orlando 
bUniversity of Texas Southwestern Medical Center, Dallas 
cOrlando Veterans Affairs Medical Center, Florida 
dNorth Florida/South Georgia Veterans Health System, Gainesville

Author disclosures: The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ishak Mansi (ishak.mansi@va.gov)

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0560

Article PDF
0525FED AVAHO Colorectal Cancer_0.pdf
Article PDF
0525FED AVAHO Colorectal Cancer_0.pdf

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths in the United States, with an estimated 52,550 deaths in 2023.1 However, the disease burden varies among different segments of the population.2 While both CRC incidence and mortality have been decreasing due to screening and advances in treatment, there are disparities in incidence and mortality across the sociodemographic spectrum including race, ethnicity, education, and income.1-4 While CRC incidence is decreasing for older adults, it is increasing among those aged < 55 years.5 The incidence of CRC in adults aged 40 to 54 years has increased by 0.5% to 1.3% annually since the mid-1990s.6 The US Preventive Services Task Force now recommends starting CRC screening at age 45 years for asymptomatic adults with average risk.7

Disparities also exist across geographical boundaries and living environment. Rural Americans faces additional challenges in health and lifestyle that can affect CRC outcomes. Compared to their urban counterparts, rural residents are more likely to be older, have lower levels of education, higher levels of poverty, lack health insurance, and less access to health care practitioners (HCPs).8-10 Geographic proximity, defined as travel time or physical distance to a health facility, has been recognized as a predictor of inferior outcomes.11 These aspects of rural living may pose challenges for accessing care for CRC screening and treatment.11-13 National and local studies have shown disparities in CRC screening rates, incidence, and mortality between rural and urban populations.14-16

It is unclear whether rural/urban disparities persist under the Veterans Health Administration (VHA) health care delivery model. This study examined differences in baseline characteristics and mortality between rural and urban veterans newly diagnosed with CRC. We also focused on a subpopulation aged ≤ 45 years.

Methods

This study extracted national data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) hosted in the VA Informatics and Computing Infrastructure (VINCI) environment. VINCI is an initiative to improve access to VA data and facilitate the analysis of these data while ensuring veterans’ privacy and data security.17 CDW is the VHA business intelligence information repository, which extracts data from clinical and nonclinical sources following prescribed and validated protocols. Data extracted included demographics, diagnosis, and procedure codes for both inpatient and outpatient encounters, vital signs, and vital status. This study used data previously extracted from a national cohort of veterans that encompassed all patients who received a group of commonly prescribed medications, such as statins, proton pump inhibitors, histamine-2 blockers, acetaminophen-containing products, and hydrocortisone-containing skin applications. This cohort encompassed 8,648,754 veterans, from whom 2,460,727 had encounters during fiscal years (FY) 2016 to 2021 (study period). The cohort was used to ensure that subjects were VHA patients, allowing them to adequately capture their clinical profiles.

Patients were identified as rural or urban based on their residence address at the date of their first diagnosis of CRC. The Geospatial Service Support Center (GSSC) aggregates and updates veterans’ residence address records for all enrolled veterans from the National Change of Address database. The data contain 1 record per enrollee. GSSC Geocoded Enrollee File contains enrollee addresses and their rurality indicators, categorized as urban, rural, or highly rural.18 Rurality is defined by the Rural Urban Commuting Area (RUCA) categories developed by the Department of Agriculture and the Health Resources and Services Administration of the US Department of Health and Human Services.19 Urban areas had RUCA codes of 1.0 to 1.1, and highly rural areas had RUCA scores of 10.0. All other areas were classified as rural. Since the proportion of veterans from highly rural areas was small, we included residents from highly rural areas in the rural residents’ group.

Inclusion and Exclusion Criteria

All veterans newly diagnosed with CRC from FY 2016 to 2021 were included. We used the ninth and tenth clinical modification revisions of the International Classification of Diseases (ICD-9-CM and ICD-10-CM) to define CRC diagnosis (Supplemental materials).4,20 To ensure that patients were newly diagnosed with CRC, this study excluded patients with a previous ICD-9-CM code for CRC diagnosis since FY 2003.

Comorbidities were identified using diagnosis and procedure codes from inpatient and outpatient encounters, which were used to calculate the Charlson Comorbidity Index (CCI) at the time of CRC diagnosis using the weighted method described by Schneeweiss et al.21 We defined CRC high-risk conditions and CRC screening tests, including flexible sigmoidoscopy and stool tests, as described in previous studies (Supplemental materials).20

The main outcome was total mortality. The date of death was extracted from the VHA Death Ascertainment File, which contains mortality data from the Master Person Index file in CDW and the Social Security Administration Death Master File. We used the date of death from any cause, as cause of death was not available.

A propensity score (PS) was created to match rural (including highly rural) and urban residents at a ratio of 1:1. Using a standard procedure described in prior publications, multivariable logistic regression used all baseline characteristics to estimate the PS and perform nearest-number matching without replacement.22,23 A caliper of 0.01 maximized the matched cohort size and achieved balance (Supplemental materials). We then examined the balance of baseline characteristics between PS-matched groups.

Analyses

Cox proportional hazards regression analysis estimated the hazard ratio (HR) of death in rural residents compared to urban residents in the PS-matched cohort. The outcome event was the date of death during the study’s follow-up period (defined as period from first CRC diagnosis to death or study end), with censoring at the study’s end date (September 30, 2021). The proportional hazards assumption was assessed by inspecting the Kaplan-Meier curves. Multiple analyses examined the HR of total mortality in the PS-matched cohort, stratified by sex, race, and ethnicity. We also examined the HR of total mortality stratified by duration of follow-up.

Another PS-matching analysis among veterans aged ≤ 45 years was performed using the same techniques described earlier in this article. We performed a Cox proportional hazards regression analysis to compare mortality in PS-matched urban and rural veterans aged ≤ 45 years. The HR of death in all veterans aged ≤ 45 years (before PS-matching) was estimated using Cox proportional hazard regression analysis, adjusting for PS.

Dichotomous variables were compared using X2 tests and continuous variables were compared using t tests. Baseline characteristics with missing values were converted into categorical variables and the proportion of subjects with missing values was equalized between treatment groups after PS-matching. For subgroup analysis, we examined the HR of total mortality in each subgroup using separate Cox proportional hazards regression models similar to the primary analysis but adjusted for PS. Due to multiple comparisons in the subgroup analysis, the findings should be considered exploratory. Statistical tests were 2-tailed, and significance was defined as P < .05. Data management and statistical analyses were conducted from June 2022 to January 2023 using STATA, Version 17. The VA Orlando Healthcare System Institutional Review Board approved the study and waived requirements for informed consent because only deidentified data were used.

Results

After excluding 49 patients (Supplemental materials, available at doi:10.12788/fp.0560), we identified 30,219 veterans with newly diagnosed CRC between FY 2016 to 2021 (Table 1). Of these, 19,422 (64.3%) resided in urban areas and 10,797 (35.7%) resided in rural areas (Table 2). The mean (SD) duration from the first CRC diagnosis to death or study end was 832 (640) days, and the median (IQR) was 723 (246–1330) days. Overall, incident CRC diagnoses were numerically highest in FY 2016 and lowest in FY 2020 (Figure 1). Patients with CRC in rural areas vs urban areas were significantly older (mean, 71.2 years vs 70.8 years, respectively; P < .001), more likely to be male (96.7% vs 95.7%, respectively; P < .001), more likely to be White (83.6% vs 67.8%, respectively; P < .001) and more likely to be non-Hispanic (92.2% vs 87.5%, respectively; P < .001). In terms of general health, rural veterans with CRC were more likely to be overweight or obese (81.5% rural vs 78.5% urban; P < .001) but had fewer mean comorbidities as measured by CCI (5.66 rural vs 5.90 urban; P < .001). A higher proportion of rural veterans with CRC had received stool-based (fecal occult blood test or fecal immunochemical test) CRC screening tests (61.6% rural vs 57.2% urban; P < .001). Fewer rural patients presented with systemic symptoms or signs within 1 year of CRC diagnosis (54.4% rural vs 57.5% urban, P < .001). Among urban patients with CRC, 6959 (35.8%) deaths were observed, compared with 3766 (34.9%) among rural patients (P = .10).

0525FED-AVAHO-CRC_T10525FED-AVAHO-CRC_T20525FED-AVAHO-CRC_F1

There were 21,568 PS-matched veterans: 10,784 in each group. In the PS-matched cohort, baseline characteristics were similar between veterans in urban and rural communities, including age, sex, race/ethnicity, body mass index, and comorbidities. Among rural patients with CRC, 3763 deaths (34.9%) were observed compared with 3702 (34.3%) among urban veterans. There was no significant difference in the HR of mortality between rural and urban CRC residents (HR, 1.01; 95% CI, 0.97-1.06; P = .53) (Figure 2).

0525FED-AVAHO-CRC_F20525FED-AVAHO-CRC_F30525FED-AVAHO-CRC_F4

Among veterans aged ≤ 45 years, 551 were diagnosed with CRC (391 urban and 160 rural). We PS-matched 142 pairs of urban and rural veterans without residual differences in baseline characteristics (eAppendix 1). There was no significant difference in the HR of mortality between rural and urban veterans aged ≤ 45 years (HR, 0.97; 95% CI, 0.57-1.63; P = .90) (Figure 2). Similarly, no difference in mortality was observed adjusting for PS between all rural and urban veterans aged ≤ 45 years (HR, 1.03; 95% CI, 0.67-1.59; P = .88).

0525FED-AVAHO-CRC_eApp1

There was no difference in total mortality between rural and urban veterans in any subgroup except for American Indian or Alaska Native veterans (HR, 2.41; 95% CI, 1.29-4.50; P = .006) (eAppendix 2).

0525FED-AVAHO-CRC_eApp2

Discussion

This study examined characteristics of patients with CRC between urban and rural areas among veterans who were VHA patients. Similar to other studies, rural veterans with CRC were older, more likely to be White, and were obese, but exhibited fewer comorbidities (lower CCI and lower incidence of congestive heart failure, dementia, hemiplegia, kidney diseases, liver diseases and AIDS, but higher incidence of chronic obstructive lung disease).8,16 The incidence of CRC in this study population was lowest in FY 2020, which was reported by the Centers for Disease Control and Prevention and is attributed to COVID-19 pandemic disruption of health services.24 The overall mortality in this study was similar to rates reported in other studies from the VA Central Cancer Registry.4 In the PS-matched cohort, where baseline characteristics were similar between urban and rural patients with CRC, we found no disparities in CRC-specific mortality between veterans in rural and urban areas. Additionally, when analysis was restricted to veterans aged ≤ 45 years, the results remained consistent.

Subgroup analyses showed no significant difference in mortality between rural and urban areas by sex, race or ethnicity, except rural American Indian or Alaska Native veterans who had double the mortality of their urban counterparts (HR, 2.41; 95% CI, 1.29-4.50; P = .006). This finding is difficult to interpret due to the small number of events and the wide CI. While with a Bonferroni correction the adjusted P value was .08, which is not statistically significant, a previous study found that although CRC incidence was lower overall in American Indian or Alaska Native populations compared to non-Hispanic White populations, CRC incidence was higher among American Indian or Alaska Native individuals in some areas such as Alaska and the Northern Plains.25,26 Studies have noted that rural American Indian/Alaska Native populations experience greater poverty, less access to broadband internet, and limited access to care, contributing to poorer cancer outcomes and lower survival.27 Thus, the finding of disparity in mortality between rural and urban American Indian or Alaska Native veterans warrants further study.

Other studies have raised concerns that CRC disproportionately affects adults in rural areas with higher mortality rates.14-16 These disparities arise from sociodemographic factors and modifiable risk factors, including physical activity, dietary patterns, access to cancer screening, and gaps in quality treatment resources.16,28 These factors operate at multiple levels: from individual, local health system, to community and policy.2,27 For example, a South Carolina study (1996–2016) found that residents in rural areas were more likely to be diagnosed with advanced CRC, possibly indicating lower rates of CRC screening in rural areas. They also had higher likelihood of death from CRC.15 However, the study did not include any clinical parameters, such as comorbidities or obesity. A statewide, population-based study in Utah showed that rural men experienced a lower CRC survival in their unadjusted analysis.16 However, the study was small, with only 3948 urban and 712 rural residents. Additionally, there was no difference in total mortality in the whole cohort (HR, 0.96; 95% CI, 0.86-1.07) or in CRC-specific death (HR, 0.93; 95% CI, 0.81-1.08). A nationwide study also showed that CRC mortality rates were 8% higher in nonmetropolitan or rural areas than in the most urbanized areas containing large metropolitan counties.29 However, this study did not include descriptions of clinical confounders, such as comorbidities, making it difficult to ascertain whether the difference in CRC mortality was due to rurality or differences in baseline risk characteristics.

In this study, the lack of CRC-specific mortality disparities may be attributed to the structures and practices of VHA health care. Recent studies have noted that mortality of several chronic medical conditions treated at the VHA was lower than at non-VHA hospitals.30,31 One study that measured the quality of nonmetastatic CRC care based on National Comprehensive Cancer Network guidelines showed that > 72% of VHA patients received guideline-concordant care for each diagnostic and therapeutic measure, except for follow-up colonoscopy timing, which appear to be similar or superior to that of the private sector.30,32,33 Some of the VA initiative for CRC screening may bypass the urban-rurality divide such as the mailed fecal immunochemical test program for CRC. This program was implemented at the onset of the COVID-19 pandemic to avoid disruptions of medical care.34 Rural patients are more likely to undergo fecal immunochemical testing when compared to urban patients in this data. Beyond clinical care, the VHA uses processes to tackle social determinants of health such as housing, food security, and transportation, promoting equal access to health care, and promoting cultural competency among HCPs.35-37

The results suggest that solutions to CRC disparities between rural and urban areas need to consider known barriers to rural health care, including transportation, diminished rural health care workforce, and other social determinants of health.9,10,27,38 VHA makes considerable efforts to provide equitable care to all enrolled veterans, including specific programs for rural veterans, including ongoing outreach.39 This study demonstrated lack of disparity in CRC-specific mortality in veterans receiving VHA care, highlighting the importance of these efforts.

Strengths and Limitations

This study used the VHA cohort to compare patient characteristics and mortality between patients with CRC residing in rural and urban areas. The study provides nationwide perspectives on CRC across the geographical spectrum and used a longitudinal cohort with prolonged follow-up to account for comorbidities.

However, the study compared a cohort of rural and urban veterans enrolled in the VHA; hence, the results may not reflect CRC outcomes in veterans without access to VHA care. Rurality has been independently associated with decreased likelihood of meeting CRC screening guidelines among veterans and military service members.38 This study lacked sufficient information to compare CRC staging or treatment modalities among veterans. Although the data cannot identify CRC stage, the proportions of patients with metastatic CRC at diagnosis and CRC location were similar between groups. The study did not have information on their care outside of VHA setting.

This study could not ascertain whether disparities existed in CRC treatment modality since rural residence may result in referral to community-based CRC care, which did not appear in the data. To address these limitations, we used death from any cause as the primary outcome, since death is a hard outcome and is not subject to ascertainment bias. The relatively short follow-up time is another limitation, though subgroup analysis by follow-up did not show significant differences. Despite PS matching, residual unmeasured confounding may exist between urban and rural groups. The predominantly White, male VHA population with high CCI may limit the generalizability of the results.

Conclusions

Rural VHA enrollees had similar survival rates after CRC diagnosis compared to their urban counterparts in a PS-matched analysis. The VHA models of care—including mailed CRC screening tools, several socioeconomic determinants of health (housing, food security, and transportation), and promoting equal access to health care, as well as cultural competency among HCPs—HCPs—may help alleviate disparities across the rural-urban spectrum. The VHA should continue efforts to enroll veterans and provide comprehensive coordinated care in community partnerships.

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths in the United States, with an estimated 52,550 deaths in 2023.1 However, the disease burden varies among different segments of the population.2 While both CRC incidence and mortality have been decreasing due to screening and advances in treatment, there are disparities in incidence and mortality across the sociodemographic spectrum including race, ethnicity, education, and income.1-4 While CRC incidence is decreasing for older adults, it is increasing among those aged < 55 years.5 The incidence of CRC in adults aged 40 to 54 years has increased by 0.5% to 1.3% annually since the mid-1990s.6 The US Preventive Services Task Force now recommends starting CRC screening at age 45 years for asymptomatic adults with average risk.7

Disparities also exist across geographical boundaries and living environment. Rural Americans faces additional challenges in health and lifestyle that can affect CRC outcomes. Compared to their urban counterparts, rural residents are more likely to be older, have lower levels of education, higher levels of poverty, lack health insurance, and less access to health care practitioners (HCPs).8-10 Geographic proximity, defined as travel time or physical distance to a health facility, has been recognized as a predictor of inferior outcomes.11 These aspects of rural living may pose challenges for accessing care for CRC screening and treatment.11-13 National and local studies have shown disparities in CRC screening rates, incidence, and mortality between rural and urban populations.14-16

It is unclear whether rural/urban disparities persist under the Veterans Health Administration (VHA) health care delivery model. This study examined differences in baseline characteristics and mortality between rural and urban veterans newly diagnosed with CRC. We also focused on a subpopulation aged ≤ 45 years.

Methods

This study extracted national data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) hosted in the VA Informatics and Computing Infrastructure (VINCI) environment. VINCI is an initiative to improve access to VA data and facilitate the analysis of these data while ensuring veterans’ privacy and data security.17 CDW is the VHA business intelligence information repository, which extracts data from clinical and nonclinical sources following prescribed and validated protocols. Data extracted included demographics, diagnosis, and procedure codes for both inpatient and outpatient encounters, vital signs, and vital status. This study used data previously extracted from a national cohort of veterans that encompassed all patients who received a group of commonly prescribed medications, such as statins, proton pump inhibitors, histamine-2 blockers, acetaminophen-containing products, and hydrocortisone-containing skin applications. This cohort encompassed 8,648,754 veterans, from whom 2,460,727 had encounters during fiscal years (FY) 2016 to 2021 (study period). The cohort was used to ensure that subjects were VHA patients, allowing them to adequately capture their clinical profiles.

Patients were identified as rural or urban based on their residence address at the date of their first diagnosis of CRC. The Geospatial Service Support Center (GSSC) aggregates and updates veterans’ residence address records for all enrolled veterans from the National Change of Address database. The data contain 1 record per enrollee. GSSC Geocoded Enrollee File contains enrollee addresses and their rurality indicators, categorized as urban, rural, or highly rural.18 Rurality is defined by the Rural Urban Commuting Area (RUCA) categories developed by the Department of Agriculture and the Health Resources and Services Administration of the US Department of Health and Human Services.19 Urban areas had RUCA codes of 1.0 to 1.1, and highly rural areas had RUCA scores of 10.0. All other areas were classified as rural. Since the proportion of veterans from highly rural areas was small, we included residents from highly rural areas in the rural residents’ group.

Inclusion and Exclusion Criteria

All veterans newly diagnosed with CRC from FY 2016 to 2021 were included. We used the ninth and tenth clinical modification revisions of the International Classification of Diseases (ICD-9-CM and ICD-10-CM) to define CRC diagnosis (Supplemental materials).4,20 To ensure that patients were newly diagnosed with CRC, this study excluded patients with a previous ICD-9-CM code for CRC diagnosis since FY 2003.

Comorbidities were identified using diagnosis and procedure codes from inpatient and outpatient encounters, which were used to calculate the Charlson Comorbidity Index (CCI) at the time of CRC diagnosis using the weighted method described by Schneeweiss et al.21 We defined CRC high-risk conditions and CRC screening tests, including flexible sigmoidoscopy and stool tests, as described in previous studies (Supplemental materials).20

The main outcome was total mortality. The date of death was extracted from the VHA Death Ascertainment File, which contains mortality data from the Master Person Index file in CDW and the Social Security Administration Death Master File. We used the date of death from any cause, as cause of death was not available.

A propensity score (PS) was created to match rural (including highly rural) and urban residents at a ratio of 1:1. Using a standard procedure described in prior publications, multivariable logistic regression used all baseline characteristics to estimate the PS and perform nearest-number matching without replacement.22,23 A caliper of 0.01 maximized the matched cohort size and achieved balance (Supplemental materials). We then examined the balance of baseline characteristics between PS-matched groups.

Analyses

Cox proportional hazards regression analysis estimated the hazard ratio (HR) of death in rural residents compared to urban residents in the PS-matched cohort. The outcome event was the date of death during the study’s follow-up period (defined as period from first CRC diagnosis to death or study end), with censoring at the study’s end date (September 30, 2021). The proportional hazards assumption was assessed by inspecting the Kaplan-Meier curves. Multiple analyses examined the HR of total mortality in the PS-matched cohort, stratified by sex, race, and ethnicity. We also examined the HR of total mortality stratified by duration of follow-up.

Another PS-matching analysis among veterans aged ≤ 45 years was performed using the same techniques described earlier in this article. We performed a Cox proportional hazards regression analysis to compare mortality in PS-matched urban and rural veterans aged ≤ 45 years. The HR of death in all veterans aged ≤ 45 years (before PS-matching) was estimated using Cox proportional hazard regression analysis, adjusting for PS.

Dichotomous variables were compared using X2 tests and continuous variables were compared using t tests. Baseline characteristics with missing values were converted into categorical variables and the proportion of subjects with missing values was equalized between treatment groups after PS-matching. For subgroup analysis, we examined the HR of total mortality in each subgroup using separate Cox proportional hazards regression models similar to the primary analysis but adjusted for PS. Due to multiple comparisons in the subgroup analysis, the findings should be considered exploratory. Statistical tests were 2-tailed, and significance was defined as P < .05. Data management and statistical analyses were conducted from June 2022 to January 2023 using STATA, Version 17. The VA Orlando Healthcare System Institutional Review Board approved the study and waived requirements for informed consent because only deidentified data were used.

Results

After excluding 49 patients (Supplemental materials, available at doi:10.12788/fp.0560), we identified 30,219 veterans with newly diagnosed CRC between FY 2016 to 2021 (Table 1). Of these, 19,422 (64.3%) resided in urban areas and 10,797 (35.7%) resided in rural areas (Table 2). The mean (SD) duration from the first CRC diagnosis to death or study end was 832 (640) days, and the median (IQR) was 723 (246–1330) days. Overall, incident CRC diagnoses were numerically highest in FY 2016 and lowest in FY 2020 (Figure 1). Patients with CRC in rural areas vs urban areas were significantly older (mean, 71.2 years vs 70.8 years, respectively; P < .001), more likely to be male (96.7% vs 95.7%, respectively; P < .001), more likely to be White (83.6% vs 67.8%, respectively; P < .001) and more likely to be non-Hispanic (92.2% vs 87.5%, respectively; P < .001). In terms of general health, rural veterans with CRC were more likely to be overweight or obese (81.5% rural vs 78.5% urban; P < .001) but had fewer mean comorbidities as measured by CCI (5.66 rural vs 5.90 urban; P < .001). A higher proportion of rural veterans with CRC had received stool-based (fecal occult blood test or fecal immunochemical test) CRC screening tests (61.6% rural vs 57.2% urban; P < .001). Fewer rural patients presented with systemic symptoms or signs within 1 year of CRC diagnosis (54.4% rural vs 57.5% urban, P < .001). Among urban patients with CRC, 6959 (35.8%) deaths were observed, compared with 3766 (34.9%) among rural patients (P = .10).

0525FED-AVAHO-CRC_T10525FED-AVAHO-CRC_T20525FED-AVAHO-CRC_F1

There were 21,568 PS-matched veterans: 10,784 in each group. In the PS-matched cohort, baseline characteristics were similar between veterans in urban and rural communities, including age, sex, race/ethnicity, body mass index, and comorbidities. Among rural patients with CRC, 3763 deaths (34.9%) were observed compared with 3702 (34.3%) among urban veterans. There was no significant difference in the HR of mortality between rural and urban CRC residents (HR, 1.01; 95% CI, 0.97-1.06; P = .53) (Figure 2).

0525FED-AVAHO-CRC_F20525FED-AVAHO-CRC_F30525FED-AVAHO-CRC_F4

Among veterans aged ≤ 45 years, 551 were diagnosed with CRC (391 urban and 160 rural). We PS-matched 142 pairs of urban and rural veterans without residual differences in baseline characteristics (eAppendix 1). There was no significant difference in the HR of mortality between rural and urban veterans aged ≤ 45 years (HR, 0.97; 95% CI, 0.57-1.63; P = .90) (Figure 2). Similarly, no difference in mortality was observed adjusting for PS between all rural and urban veterans aged ≤ 45 years (HR, 1.03; 95% CI, 0.67-1.59; P = .88).

0525FED-AVAHO-CRC_eApp1

There was no difference in total mortality between rural and urban veterans in any subgroup except for American Indian or Alaska Native veterans (HR, 2.41; 95% CI, 1.29-4.50; P = .006) (eAppendix 2).

0525FED-AVAHO-CRC_eApp2

Discussion

This study examined characteristics of patients with CRC between urban and rural areas among veterans who were VHA patients. Similar to other studies, rural veterans with CRC were older, more likely to be White, and were obese, but exhibited fewer comorbidities (lower CCI and lower incidence of congestive heart failure, dementia, hemiplegia, kidney diseases, liver diseases and AIDS, but higher incidence of chronic obstructive lung disease).8,16 The incidence of CRC in this study population was lowest in FY 2020, which was reported by the Centers for Disease Control and Prevention and is attributed to COVID-19 pandemic disruption of health services.24 The overall mortality in this study was similar to rates reported in other studies from the VA Central Cancer Registry.4 In the PS-matched cohort, where baseline characteristics were similar between urban and rural patients with CRC, we found no disparities in CRC-specific mortality between veterans in rural and urban areas. Additionally, when analysis was restricted to veterans aged ≤ 45 years, the results remained consistent.

Subgroup analyses showed no significant difference in mortality between rural and urban areas by sex, race or ethnicity, except rural American Indian or Alaska Native veterans who had double the mortality of their urban counterparts (HR, 2.41; 95% CI, 1.29-4.50; P = .006). This finding is difficult to interpret due to the small number of events and the wide CI. While with a Bonferroni correction the adjusted P value was .08, which is not statistically significant, a previous study found that although CRC incidence was lower overall in American Indian or Alaska Native populations compared to non-Hispanic White populations, CRC incidence was higher among American Indian or Alaska Native individuals in some areas such as Alaska and the Northern Plains.25,26 Studies have noted that rural American Indian/Alaska Native populations experience greater poverty, less access to broadband internet, and limited access to care, contributing to poorer cancer outcomes and lower survival.27 Thus, the finding of disparity in mortality between rural and urban American Indian or Alaska Native veterans warrants further study.

Other studies have raised concerns that CRC disproportionately affects adults in rural areas with higher mortality rates.14-16 These disparities arise from sociodemographic factors and modifiable risk factors, including physical activity, dietary patterns, access to cancer screening, and gaps in quality treatment resources.16,28 These factors operate at multiple levels: from individual, local health system, to community and policy.2,27 For example, a South Carolina study (1996–2016) found that residents in rural areas were more likely to be diagnosed with advanced CRC, possibly indicating lower rates of CRC screening in rural areas. They also had higher likelihood of death from CRC.15 However, the study did not include any clinical parameters, such as comorbidities or obesity. A statewide, population-based study in Utah showed that rural men experienced a lower CRC survival in their unadjusted analysis.16 However, the study was small, with only 3948 urban and 712 rural residents. Additionally, there was no difference in total mortality in the whole cohort (HR, 0.96; 95% CI, 0.86-1.07) or in CRC-specific death (HR, 0.93; 95% CI, 0.81-1.08). A nationwide study also showed that CRC mortality rates were 8% higher in nonmetropolitan or rural areas than in the most urbanized areas containing large metropolitan counties.29 However, this study did not include descriptions of clinical confounders, such as comorbidities, making it difficult to ascertain whether the difference in CRC mortality was due to rurality or differences in baseline risk characteristics.

In this study, the lack of CRC-specific mortality disparities may be attributed to the structures and practices of VHA health care. Recent studies have noted that mortality of several chronic medical conditions treated at the VHA was lower than at non-VHA hospitals.30,31 One study that measured the quality of nonmetastatic CRC care based on National Comprehensive Cancer Network guidelines showed that > 72% of VHA patients received guideline-concordant care for each diagnostic and therapeutic measure, except for follow-up colonoscopy timing, which appear to be similar or superior to that of the private sector.30,32,33 Some of the VA initiative for CRC screening may bypass the urban-rurality divide such as the mailed fecal immunochemical test program for CRC. This program was implemented at the onset of the COVID-19 pandemic to avoid disruptions of medical care.34 Rural patients are more likely to undergo fecal immunochemical testing when compared to urban patients in this data. Beyond clinical care, the VHA uses processes to tackle social determinants of health such as housing, food security, and transportation, promoting equal access to health care, and promoting cultural competency among HCPs.35-37

The results suggest that solutions to CRC disparities between rural and urban areas need to consider known barriers to rural health care, including transportation, diminished rural health care workforce, and other social determinants of health.9,10,27,38 VHA makes considerable efforts to provide equitable care to all enrolled veterans, including specific programs for rural veterans, including ongoing outreach.39 This study demonstrated lack of disparity in CRC-specific mortality in veterans receiving VHA care, highlighting the importance of these efforts.

Strengths and Limitations

This study used the VHA cohort to compare patient characteristics and mortality between patients with CRC residing in rural and urban areas. The study provides nationwide perspectives on CRC across the geographical spectrum and used a longitudinal cohort with prolonged follow-up to account for comorbidities.

However, the study compared a cohort of rural and urban veterans enrolled in the VHA; hence, the results may not reflect CRC outcomes in veterans without access to VHA care. Rurality has been independently associated with decreased likelihood of meeting CRC screening guidelines among veterans and military service members.38 This study lacked sufficient information to compare CRC staging or treatment modalities among veterans. Although the data cannot identify CRC stage, the proportions of patients with metastatic CRC at diagnosis and CRC location were similar between groups. The study did not have information on their care outside of VHA setting.

This study could not ascertain whether disparities existed in CRC treatment modality since rural residence may result in referral to community-based CRC care, which did not appear in the data. To address these limitations, we used death from any cause as the primary outcome, since death is a hard outcome and is not subject to ascertainment bias. The relatively short follow-up time is another limitation, though subgroup analysis by follow-up did not show significant differences. Despite PS matching, residual unmeasured confounding may exist between urban and rural groups. The predominantly White, male VHA population with high CCI may limit the generalizability of the results.

Conclusions

Rural VHA enrollees had similar survival rates after CRC diagnosis compared to their urban counterparts in a PS-matched analysis. The VHA models of care—including mailed CRC screening tools, several socioeconomic determinants of health (housing, food security, and transportation), and promoting equal access to health care, as well as cultural competency among HCPs—HCPs—may help alleviate disparities across the rural-urban spectrum. The VHA should continue efforts to enroll veterans and provide comprehensive coordinated care in community partnerships.

References
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  2. Carethers JM, Doubeni CA. Causes of socioeconomic disparities in colorectal cancer and intervention framework and strategies. Gastroenterology. 2020;158(2):354-367. doi:10.1053/j.gastro.2019.10.029
  3. Murphy G, Devesa SS, Cross AJ, Inskip PD, McGlynn KA, Cook MB. Sex disparities in colorectal cancer incidence by anatomic subsite, race and age. Int J Cancer. 2011;128(7):1668-75. doi:10.1002/ijc.25481
  4. Zullig LL, Smith VA, Jackson GL, et al. Colorectal cancer statistics from the Veterans Affairs central cancer registry. Clin Colorectal Cancer. 2016;15(4):e199-e204. doi:10.1016/j.clcc.2016.04.005
  5. Lin JS, Perdue LA, Henrikson NB, Bean SI, Blasi PR. Screening for Colorectal Cancer: An Evidence Update for the US Preventive Services Task Force. 2021. U.S. Preventive Services Task Force Evidence Syntheses, formerly Systematic Evidence Reviews:Chapter 1. Agency for Healthcare Research and Quality (US); 2021. Accessed February 18, 2025. https://www.ncbi.nlm.nih.gov/books/NBK570917/
  6. Siegel RL, Fedewa SA, Anderson WF, et al. Colorectal cancer incidence patterns in the United States, 1974-2013. J Natl Cancer Inst. 2017;109(8). doi:10.1093/jnci/djw322
  7. Davidson KW, Barry MJ, Mangione CM, et al. Screening for colorectal cancer: US Preventive Services Task Force recommendation statement. JAMA. 2021;325(19):1965-1977. doi:10.1001/jama.2021.6238
  8. Hines R, Markossian T, Johnson A, Dong F, Bayakly R. Geographic residency status and census tract socioeconomic status as determinants of colorectal cancer outcomes. Am J Public Health. 2014;104(3):e63-e71. doi:10.2105/AJPH.2013.301572
  9. Cauwels J. The many barriers to high-quality rural health care. 2022;(9):1-32. NEJM Catal Innov Care Deliv. Accessed April 24, 2025. https://catalyst.nejm.org/doi/pdf/10.1056/CAT.22.0254
  10. Gong G, Phillips SG, Hudson C, Curti D, Philips BU. Higher US rural mortality rates linked to socioeconomic status, physician shortages, and lack of health insurance. Health Aff (Millwood);38(12):2003-2010. doi:10.1377/hlthaff.2019.00722
  11. Aboagye JK, Kaiser HE, Hayanga AJ. Rural-urban differences in access to specialist providers of colorectal cancer care in the United States: a physician workforce issue. JAMA Surg. 2014;149(6):537-543. doi:10.1001/jamasurg.2013.5062
  12. Lyckholm LJ, Hackney MH, Smith TJ. Ethics of rural health care. Crit Rev Oncol Hematol. 2001;40(2):131-138. doi:10.1016/s1040-8428(01)00139-1
  13. Krieger N, Williams DR, Moss NE. Measuring social class in US public health research: concepts, methodologies, and guidelines. Annu Rev Public Health. 1997;18:341-378. doi:10.1146/annurev.publhealth.18.1.341
  14. Singh GK, Jemal A. Socioeconomic and racial/ethnic disparities in cancer mortality, incidence, and survival in the United States, 1950-2014: over six decades of changing patterns and widening inequalities. J Environ Public Health. 2017;2017:2819372. doi:10.1155/2017/2819372
  15. Adams SA, Zahnd WE, Ranganathan R, et al. Rural and racial disparities in colorectal cancer incidence and mortality in South Carolina, 1996 - 2016. J Rural Health. 2022;38(1):34-39. doi:10.1111/jrh.12580
  16. Rogers CR, Blackburn BE, Huntington M, et al. Rural- urban disparities in colorectal cancer survival and risk among men in Utah: a statewide population-based study. Cancer Causes Control. 2020;31(3):241-253. doi:10.1007/s10552-020-01268-2
  17. US Department of Veterans Affairs. VA Informatics and Computing Infrastructure (VINCI), VA HSR RES 13-457. https://vincicentral.vinci.med.va.gov [Source not verified]
  18. US Department of Veterans Affairs Information Resource Center. VIReC Research User Guide: PSSG Geocoded Enrollee Files, 2015 Edition. US Department of Veterans Affairs, Health Services Research & Development Service, Information Resource Center; May. 2016. [source not verified]
  19. Goldsmith HF, Puskin DS, Stiles DJ. Improving the operational definition of “rural areas” for federal programs. US Department of Health and Human Services; 1993. Accessed February 27, 2025. https://www.ruralhealthinfo.org/pdf/improving-the-operational-definition-of-rural-areas.pdf
  20. Adams MA, Kerr EA, Dominitz JA, et al. Development and validation of a new ICD-10-based screening colonoscopy overuse measure in a large integrated healthcare system: a retrospective observational study. BMJ Qual Saf. 2023;32(7):414-424. doi:10.1136/bmjqs-2021-014236
  21. Schneeweiss S, Wang PS, Avorn J, Glynn RJ. Improved comorbidity adjustment for predicting mortality in Medicare populations. Health Serv Res. 2003;38(4):1103-1120. doi:10.1111/1475-6773.00165
  22. Becker S, Ichino A. Estimation of average treatment effects based on propensity scores. The Stata Journal. 2002;2(4):358-377.
  23. Leuven E, Sianesi B. PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical software components. Revised February 1, 2018. Accessed February 27, 2025. https://ideas.repec.org/c/boc/bocode/s432001.html.
  24. US Cancer Statistics Working Group. US cancer statistics data visualizations tool. Centers for Disease Control and Prevention. June 2024. Accessed February 27, 2025. https://www.cdc.gov/cancer/dataviz
  25. Cao J, Zhang S. Multiple Comparison Procedures. JAMA. 2014;312(5):543-544. doi:10.1001/jama.2014.9440
  26. Gopalani SV, Janitz AE, Martinez SA, et al. Trends in cancer incidence among American Indians and Alaska Natives and Non-Hispanic Whites in the United States, 1999-2015. Epidemiology. 2020;31(2):205-213. doi:10.1097/EDE.0000000000001140
  27. Zahnd WE, Murphy C, Knoll M, et al. The intersection of rural residence and minority race/ethnicity in cancer disparities in the United States. Int J Environ Res Public Health. 2021;18(4). doi:10.3390/ijerph18041384
  28. Blake KD, Moss JL, Gaysynsky A, Srinivasan S, Croyle RT. Making the case for investment in rural cancer control: an analysis of rural cancer incidence, mortality, and funding trends. Cancer Epidemiol Biomarkers Prev. 2017;26(7):992-997. doi:10.1158/1055-9965.EPI-17-0092
  29. Singh GK, Williams SD, Siahpush M, Mulhollen A. Socioeconomic, rural-urban, and racial inequalities in US cancer mortality: part i-all cancers and lung cancer and part iicolorectal, prostate, breast, and cervical cancers. J Cancer Epidemiol. 2011;2011:107497. doi:10.1155/2011/107497
  30. Jackson GL, Melton LD, Abbott DH, et al. Quality of nonmetastatic colorectal cancer care in the Department of Veterans Affairs. J Clin Oncol. 2010;28(19):3176-3181. doi:10.1200/JCO.2009.26.7948
  31. Yoon J, Phibbs CS, Ong MK, et al. Outcomes of veterans treated in Veterans Affairs hospitals vs non-Veterans Affairs hospitals. JAMA Netw Open. 2023;6(12):e2345898. doi:10.1001/jamanetworkopen.2023.45898
  32. Malin JL, Schneider EC, Epstein AM, Adams J, Emanuel EJ, Kahn KL. Results of the National Initiative for Cancer Care Quality: how can we improve the quality of cancer care in the United States? J Clin Oncol. 2006;24(4):626-634. doi:10.1200/JCO.2005.03.3365
  33. Levin B, Lieberman DA, McFarland B, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. Gastroenterology. 2008;134(5):1570-1595. doi:10.1053/j.gastro.2008.02.002
  34. Deeds SA, Moore CB, Gunnink EJ, et al. Implementation of a mailed faecal immunochemical test programme for colorectal cancer screening among Veterans. BMJ Open Qual. 2022;11(4). doi:10.1136/bmjoq-2022-001927
  35. Yehia BR, Greenstone CL, Hosenfeld CB, Matthews KL, Zephyrin LC. The role of VA community care in addressing health and health care disparities. Med Care. 2017;55(Suppl 9 suppl 2):S4-S5. doi:10.1097/MLR.0000000000000768
  36. Wright BN, MacDermid Wadsworth S, Wellnitz A, Eicher- Miller HA. Reaching rural veterans: a new mechanism to connect rural, low-income US Veterans with resources and improve food security. J Public Health (Oxf). 2019;41(4):714-723. doi:10.1093/pubmed/fdy203
  37. Nelson RE, Byrne TH, Suo Y, et al. Association of temporary financial assistance with housing stability among US veterans in the supportive services for veteran families program. JAMA Netw Open. 2021;4(2):e2037047. doi:10.1001/jamanetworkopen.2020.37047
  38. McDaniel JT, Albright D, Lee HY, et al. Rural–urban disparities in colorectal cancer screening among military service members and Veterans. J Mil Veteran Fam Health. 2019;5(1):40-48. doi:10.3138/jmvfh.2018-0013
  39. US Department of Veterans Affairs, Office of Rural Health. The rural veteran outreach toolkit. Updated February 12, 2025. Accessed February 18, 2025. https://www.ruralhealth.va.gov/partners/toolkit.asp
References
  1. Siegel RL, Wagle NS, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2023. CA Cancer J Clin. 2023;73(3):233-254. doi:10.3322/caac.21772
  2. Carethers JM, Doubeni CA. Causes of socioeconomic disparities in colorectal cancer and intervention framework and strategies. Gastroenterology. 2020;158(2):354-367. doi:10.1053/j.gastro.2019.10.029
  3. Murphy G, Devesa SS, Cross AJ, Inskip PD, McGlynn KA, Cook MB. Sex disparities in colorectal cancer incidence by anatomic subsite, race and age. Int J Cancer. 2011;128(7):1668-75. doi:10.1002/ijc.25481
  4. Zullig LL, Smith VA, Jackson GL, et al. Colorectal cancer statistics from the Veterans Affairs central cancer registry. Clin Colorectal Cancer. 2016;15(4):e199-e204. doi:10.1016/j.clcc.2016.04.005
  5. Lin JS, Perdue LA, Henrikson NB, Bean SI, Blasi PR. Screening for Colorectal Cancer: An Evidence Update for the US Preventive Services Task Force. 2021. U.S. Preventive Services Task Force Evidence Syntheses, formerly Systematic Evidence Reviews:Chapter 1. Agency for Healthcare Research and Quality (US); 2021. Accessed February 18, 2025. https://www.ncbi.nlm.nih.gov/books/NBK570917/
  6. Siegel RL, Fedewa SA, Anderson WF, et al. Colorectal cancer incidence patterns in the United States, 1974-2013. J Natl Cancer Inst. 2017;109(8). doi:10.1093/jnci/djw322
  7. Davidson KW, Barry MJ, Mangione CM, et al. Screening for colorectal cancer: US Preventive Services Task Force recommendation statement. JAMA. 2021;325(19):1965-1977. doi:10.1001/jama.2021.6238
  8. Hines R, Markossian T, Johnson A, Dong F, Bayakly R. Geographic residency status and census tract socioeconomic status as determinants of colorectal cancer outcomes. Am J Public Health. 2014;104(3):e63-e71. doi:10.2105/AJPH.2013.301572
  9. Cauwels J. The many barriers to high-quality rural health care. 2022;(9):1-32. NEJM Catal Innov Care Deliv. Accessed April 24, 2025. https://catalyst.nejm.org/doi/pdf/10.1056/CAT.22.0254
  10. Gong G, Phillips SG, Hudson C, Curti D, Philips BU. Higher US rural mortality rates linked to socioeconomic status, physician shortages, and lack of health insurance. Health Aff (Millwood);38(12):2003-2010. doi:10.1377/hlthaff.2019.00722
  11. Aboagye JK, Kaiser HE, Hayanga AJ. Rural-urban differences in access to specialist providers of colorectal cancer care in the United States: a physician workforce issue. JAMA Surg. 2014;149(6):537-543. doi:10.1001/jamasurg.2013.5062
  12. Lyckholm LJ, Hackney MH, Smith TJ. Ethics of rural health care. Crit Rev Oncol Hematol. 2001;40(2):131-138. doi:10.1016/s1040-8428(01)00139-1
  13. Krieger N, Williams DR, Moss NE. Measuring social class in US public health research: concepts, methodologies, and guidelines. Annu Rev Public Health. 1997;18:341-378. doi:10.1146/annurev.publhealth.18.1.341
  14. Singh GK, Jemal A. Socioeconomic and racial/ethnic disparities in cancer mortality, incidence, and survival in the United States, 1950-2014: over six decades of changing patterns and widening inequalities. J Environ Public Health. 2017;2017:2819372. doi:10.1155/2017/2819372
  15. Adams SA, Zahnd WE, Ranganathan R, et al. Rural and racial disparities in colorectal cancer incidence and mortality in South Carolina, 1996 - 2016. J Rural Health. 2022;38(1):34-39. doi:10.1111/jrh.12580
  16. Rogers CR, Blackburn BE, Huntington M, et al. Rural- urban disparities in colorectal cancer survival and risk among men in Utah: a statewide population-based study. Cancer Causes Control. 2020;31(3):241-253. doi:10.1007/s10552-020-01268-2
  17. US Department of Veterans Affairs. VA Informatics and Computing Infrastructure (VINCI), VA HSR RES 13-457. https://vincicentral.vinci.med.va.gov [Source not verified]
  18. US Department of Veterans Affairs Information Resource Center. VIReC Research User Guide: PSSG Geocoded Enrollee Files, 2015 Edition. US Department of Veterans Affairs, Health Services Research & Development Service, Information Resource Center; May. 2016. [source not verified]
  19. Goldsmith HF, Puskin DS, Stiles DJ. Improving the operational definition of “rural areas” for federal programs. US Department of Health and Human Services; 1993. Accessed February 27, 2025. https://www.ruralhealthinfo.org/pdf/improving-the-operational-definition-of-rural-areas.pdf
  20. Adams MA, Kerr EA, Dominitz JA, et al. Development and validation of a new ICD-10-based screening colonoscopy overuse measure in a large integrated healthcare system: a retrospective observational study. BMJ Qual Saf. 2023;32(7):414-424. doi:10.1136/bmjqs-2021-014236
  21. Schneeweiss S, Wang PS, Avorn J, Glynn RJ. Improved comorbidity adjustment for predicting mortality in Medicare populations. Health Serv Res. 2003;38(4):1103-1120. doi:10.1111/1475-6773.00165
  22. Becker S, Ichino A. Estimation of average treatment effects based on propensity scores. The Stata Journal. 2002;2(4):358-377.
  23. Leuven E, Sianesi B. PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical software components. Revised February 1, 2018. Accessed February 27, 2025. https://ideas.repec.org/c/boc/bocode/s432001.html.
  24. US Cancer Statistics Working Group. US cancer statistics data visualizations tool. Centers for Disease Control and Prevention. June 2024. Accessed February 27, 2025. https://www.cdc.gov/cancer/dataviz
  25. Cao J, Zhang S. Multiple Comparison Procedures. JAMA. 2014;312(5):543-544. doi:10.1001/jama.2014.9440
  26. Gopalani SV, Janitz AE, Martinez SA, et al. Trends in cancer incidence among American Indians and Alaska Natives and Non-Hispanic Whites in the United States, 1999-2015. Epidemiology. 2020;31(2):205-213. doi:10.1097/EDE.0000000000001140
  27. Zahnd WE, Murphy C, Knoll M, et al. The intersection of rural residence and minority race/ethnicity in cancer disparities in the United States. Int J Environ Res Public Health. 2021;18(4). doi:10.3390/ijerph18041384
  28. Blake KD, Moss JL, Gaysynsky A, Srinivasan S, Croyle RT. Making the case for investment in rural cancer control: an analysis of rural cancer incidence, mortality, and funding trends. Cancer Epidemiol Biomarkers Prev. 2017;26(7):992-997. doi:10.1158/1055-9965.EPI-17-0092
  29. Singh GK, Williams SD, Siahpush M, Mulhollen A. Socioeconomic, rural-urban, and racial inequalities in US cancer mortality: part i-all cancers and lung cancer and part iicolorectal, prostate, breast, and cervical cancers. J Cancer Epidemiol. 2011;2011:107497. doi:10.1155/2011/107497
  30. Jackson GL, Melton LD, Abbott DH, et al. Quality of nonmetastatic colorectal cancer care in the Department of Veterans Affairs. J Clin Oncol. 2010;28(19):3176-3181. doi:10.1200/JCO.2009.26.7948
  31. Yoon J, Phibbs CS, Ong MK, et al. Outcomes of veterans treated in Veterans Affairs hospitals vs non-Veterans Affairs hospitals. JAMA Netw Open. 2023;6(12):e2345898. doi:10.1001/jamanetworkopen.2023.45898
  32. Malin JL, Schneider EC, Epstein AM, Adams J, Emanuel EJ, Kahn KL. Results of the National Initiative for Cancer Care Quality: how can we improve the quality of cancer care in the United States? J Clin Oncol. 2006;24(4):626-634. doi:10.1200/JCO.2005.03.3365
  33. Levin B, Lieberman DA, McFarland B, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. Gastroenterology. 2008;134(5):1570-1595. doi:10.1053/j.gastro.2008.02.002
  34. Deeds SA, Moore CB, Gunnink EJ, et al. Implementation of a mailed faecal immunochemical test programme for colorectal cancer screening among Veterans. BMJ Open Qual. 2022;11(4). doi:10.1136/bmjoq-2022-001927
  35. Yehia BR, Greenstone CL, Hosenfeld CB, Matthews KL, Zephyrin LC. The role of VA community care in addressing health and health care disparities. Med Care. 2017;55(Suppl 9 suppl 2):S4-S5. doi:10.1097/MLR.0000000000000768
  36. Wright BN, MacDermid Wadsworth S, Wellnitz A, Eicher- Miller HA. Reaching rural veterans: a new mechanism to connect rural, low-income US Veterans with resources and improve food security. J Public Health (Oxf). 2019;41(4):714-723. doi:10.1093/pubmed/fdy203
  37. Nelson RE, Byrne TH, Suo Y, et al. Association of temporary financial assistance with housing stability among US veterans in the supportive services for veteran families program. JAMA Netw Open. 2021;4(2):e2037047. doi:10.1001/jamanetworkopen.2020.37047
  38. McDaniel JT, Albright D, Lee HY, et al. Rural–urban disparities in colorectal cancer screening among military service members and Veterans. J Mil Veteran Fam Health. 2019;5(1):40-48. doi:10.3138/jmvfh.2018-0013
  39. US Department of Veterans Affairs, Office of Rural Health. The rural veteran outreach toolkit. Updated February 12, 2025. Accessed February 18, 2025. https://www.ruralhealth.va.gov/partners/toolkit.asp
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Colorectal Cancer Characteristics and Mortality From Propensity Score-Matched Cohorts of Urban and Rural Veterans

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New concepts in the management of acute pancreatitis

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Author(s)
Amar Mandalia, MD
Matthew J. Dimagno, MD, AGAF

 

Introduction

Acute pancreatitis (AP) is a major clinical and financial burden in the United States. Several major clinical guidelines provide evidence-based recommendations for the clinical management decisions in AP, including those from the American College of Gastroenterology (ACG; 2013),1 and the International Association of Pancreatology (IAP; 2013).2 More recently, the American Gastroenterological Association (AGA) released their own set of guidelines.3,4 In this update on AP, we review these guidelines and reference recent literature focused on epidemiology, risk factors, etiology, diagnosis, risk stratification, and recent advances in the early medical management of AP. Regarding the latter, we review six treatment interventions (pain management, intravenous fluid resuscitation, feeding, prophylactic antibiotics, probiotics, and timing of endoscopic retrograde cholangiopancreatography (ERCP) in acute biliary pancreatitis) and four preventive interventions (alcohol and smoking cessation, same-admission cholecystectomy for acute biliary pancreatitis, and chemoprevention and fluid administration for post-ERCP pancreatitis [PEP]). Updates on multidisciplinary management of (infected) pancreatic necrosis is beyond the scope of this review. Table 1 summarizes the concepts discussed in this article.

 

Recent advances in epidemiology and evaluation of AP

Epidemiology

AP is the third most common cause of gastrointestinal-related hospitalizations and fourth most common cause of readmission in 2014.5 Recent epidemiologic studies show conflicting trends for the incidence of AP, both increasing6 and decreasing,7 likely attributable to significant differences in study designs. Importantly, multiple studies have demonstrated that hospital length of stay, costs, and mortality have declined since 2009.6,8-10

Dr. Amar Mandalia

Persistent organ failure (POF), defined as organ failure lasting more than 48 hours, is the major cause of death in AP. POF, if only a single organ during AP, is associated with 27%-36% mortality; if it is multiorgan, it is associated with 47% mortality.1,11 Other factors associated with increased hospital mortality include infected pancreatic necrosis,12-14 diabetes mellitus,15 hospital-acquired infection,16 advanced age (70 years and older),17 and obesity.18 Predictive factors of 1-year mortality include readmission within 30 days, higher Charlson Comorbidity Index, and longer hospitalization.19

Risk factors

We briefly highlight recent insights into risk factors for AP (Table 1) and refer to a recent review for further discussion.20 Current and former tobacco use are independent risk factors for AP.21 The dose-response relationship of alcohol to the risk of pancreatitis is complex,22 but five standard drinks per day for 5 years is a commonly used cut-off.1,23 New evidence suggests that the relationship between the dose of alcohol and risk of AP differs by sex, linearly in men but nonlinearly (J-shaped) in women.24 Risk of AP in women was decreased with alcohol consumption of up to 40 g/day (one standard drink contains 14 g of alcohol) and increased above this amount. Cannabis is a possible risk factor for toxin-induced AP and abstinence appears to abolish risk of recurrent attacks.25

 

 

Patients with inflammatory bowel disease (IBD) have a 2.9-fold higher risk for AP versus non-IBD cohorts26 with the most common etiologies are from gallstones and medications.27 In patients with end-stage renal disease (ESRD), the risk of AP is higher in those who receive peritoneal dialysis, compared with hemodialysis28-33 and who are women, older, or have cholelithiasis or liver disease.34As recently reviewed,35 pancreatic cancer appears to be associated with first-attack pancreatitis with few exceptions.36 In this setting, the overall incidence of pancreatic cancer is low (1.5%). The risk is greatest within the first year of the attack of AP, negligible below age 40 years but steadily rising through the fifth to eighth decades.37 Pancreatic cancer screening is a conditional recommendation of the ACG guidelines in patients with unexplained AP, particularly those aged 40 years or older.1

Etiology and diagnosis


Alcohol and gallstones remain the most prevalent etiologies for AP.1 While hypertriglyceridemia accounted for 9% of AP in a systematic review of acute pancreatitis in 15 different countries,38 it is the second most common cause of acute pancreatitis in Asia (especially China).39 Figure 1 provides a breakdown of the etiologies and risk factors of pancreatitis. Importantly, it remains challenging to assign several toxic-metabolic etiologies as either a cause or risk factor for AP, particularly with regards to alcohol, smoking, and cannabis to name a few.

Guidelines and recent studies of AP raise questions about the threshold above which hypertriglyceridemia causes or poses as an important cofactor for AP. American and European societies define the threshold for triglycerides at 885-1,000 mg/dL.1,42,43 Pedersen et al. provide evidence of a graded risk of AP with hypertriglyceridemia: In multivariable analysis, adjusted hazard ratios for AP were much higher with nonfasting mild to moderately elevated plasma triglycerides (177-885 mg/dL), compared with normal values (below 89 mg/dL).44 Moreover, the risk of severe AP (developing POF) increases in proportion to triglyceride value, independent of the underlying cause of AP.45

Vidyard Video

Diagnosis of AP is derived from the revised Atlanta classification.46 The recommended timing and indications for offering cross-sectional imaging are after 48-72 hours in patients with no improvement to initial care.1 Endoscopic ultrasonography (EUS) has better diagnostic accuracy and sensitivity, compared with magnetic resonance cholangiopancreatography (MRCP) for choledocholithiasis, and has comparable specificity.47,48 Among noninvasive imaging modalities, MRCP is more sensitive than computed tomography (CT) for diagnosing choledocholithiasis.49 Despite guideline recommendations for more selective use of pancreatic imaging in the early assessment of AP, utilization of early CT or MRCP imaging (within the first 24 hours of care) remained high during 2014-2015, compared with 2006-2007.50

Dr. Matthew J. Di Magno

ERCP is not recommended as a pure diagnostic tool, owing to the availability of other diagnostic tests and a complication rate of 5%-10% with risks involving PEP, cholangitis, perforation, and hemorrhage.51 A recent systematic review of EUS and ERCP in acute biliary pancreatitis concluded that EUS had lower failure rates and had no complications, and the use of EUS avoided ERCP in 71.2% of cases.52

 

 

 

Risk stratification

The goals of using risk stratification tools in AP are to identify patients at risk for developing major outcomes, including POF, infected pancreatic necrosis, and death, and to ensure timely triaging of patients to an appropriate level of care. Existing prediction models have only moderate predictive value.53,54 Examples include simple risk stratification tools such as blood urea nitrogen (BUN) and hemoconcentration,55,56 disease-modifying patient variables (age, obesity, etc.), biomarkers (i.e., angiopoietin 2),57 and more complex clinical scoring systems such as Acute Physiology and Chronic Health Evaluation II (APACHE II), BISAP (BUN, impaired mental status, SIRS criteria, age, pleural effusion) score, early warning system (EWS), Glasgow-Imrie score, Japanese severity score, and recently the Pancreatitis Activity Scoring System (PASS).58 Two recent guidelines affirmed the importance of predicting the severity of AP, using one or more predictive tools.1,2 The recent 2018 AGA technical review does not debate this commonsense approach, but does highlight that there is no published observational study or randomized, controlled trial (RCT) investigating whether prediction tools affect clinical outcomes.4

Recent advances in early treatment of AP

Literature review and definitions

The AP literature contains heterogeneous definitions of severe AP and of what constitutes a major outcome in AP. Based on definitions of the 2013 revised Atlanta Criteria, the 2018 AGA technical review and clinical guidelines emphasized precise definitions of primary outcomes of clinical importance in AP, including death, persistent single organ failure, or persistent multiple organ failure, each requiring a duration of more than 48 hours, and infected pancreatic or peripancreatic necrosis or both (Table 2).3,4

 

Pain management

Management of pain in AP is complex and requires a detailed discussion beyond the scope of this review, but recent clinical and translational studies raise questions about the current practice of using opioids for pain management in AP. A provocative, multicenter, retrospective cohort study reported lower 30-day mortality among critically ill patients who received epidural analgesia versus standard care without epidural analgesia.59 The possible mechanism of protection and the drugs administered are unclear. An interesting hypothesis is that the epidural cohort may have received lower exposure to morphine, which may increase gut permeability, the risk of infectious complications, and severity of AP, based on a translational study in mice.60

Intravenous fluid administration

Supportive care with the use of IV fluid hydration is a mainstay of treatment for AP in the first 12-24 hours. Table 3 summarizes the guidelines in regards to IV fluid administration as delineated by the ACG and AGA guidelines on the management of pancreatitis.1,3 Guidelines advocate for early fluid resuscitation to correct intravascular depletion in order to reduce morbidity and mortality associated with AP.1,2,4 The 2018 AGA guidelines endorse a conditional recommendation for using goal-directed therapy for initial fluid management,3 do not recommend for or against normal saline versus lactated Ringer’s (LR), but do advise against the use of hydroxyethyl starch fluids.3 Consistent with these recommendations, two recent RCTs published subsequent to the prespecified time periods of the AGA technical review and guideline, observed no significant differences between LR and normal saline on clinically meaningful outcomes.61,62 The AGA guidelines acknowledge that evidence was of very-low quality in support of goal-directed therapy,3,4 which has not been shown to have a significant reduction in persistent multiple organ failure, mortality, or pancreatic necrosis, compared with usual care. As the authors noted, interpretation of the data was limited by the absence of other critical outcomes in these trials (infected pancreatic necrosis), lack of uniformity of specific outcomes and definitions of transient and POF, few trials, and risk of bias. There is a clear need for a large RCT to provide evidence to guide decision making with fluid resuscitation in AP, particularly in regard to fluid type, volume, rate, duration, endpoints, and clinical outcomes.

 

 

Feeding

More recently, the focus of nutrition in the management of AP has shifted away from patients remaining nil per os (NPO). Current guidelines advocate for early oral feeding (within 24 hours) in mild AP,3,4 in order to protect the gut-mucosal barrier. Remaining NPO when compared with early oral feeding has a 2.5-fold higher risk for interventions for necrosis.4 The recently published AGA technical review identified no significant impact on outcomes of early versus delayed oral feeding, which is consistent with observations of a landmark Dutch PYTHON trial entitled “Early versus on-demand nasoenteric tube feeding in acute pancreatitis.”4,63 There is no clear cutoff point for initiating feeding for those with severe AP. A suggested practical approach is to initiate feeding within 24-72 hours and offer enteral nutrition for those intolerant to oral feeds. In severe AP and moderately severe AP, enteral nutrition is recommended over parenteral nutrition.3,4 Enteral nutrition significantly reduces the risk of infected peripancreatic necrosis, single organ failure, and multiorgan failure.4 Finally, the AGA guidelines provide a conditional recommendation for providing enteral nutrition support through either the nasogastric or nasoenteric route.3 Further studies are required to determine the optimal timing, rate, and formulation of enteral nutrition in severe AP.

 

Antibiotics and probiotics

Current guidelines do not support the use of prophylactic antibiotics to prevent infection in necrotizing AP and severe AP.1-3 The AGA technical review reported that prophylactic antibiotics did not reduce infected pancreatic or peripancreatic necrosis, persistent single organ failure, or mortality.4 Guidelines advocate against the use of probiotics for severe AP, because of increased mortality risk.1

Figure 2: Urgent ERCP for acute biliary pancreatitis with cholangitis.

Timing of ERCP in acute biliary pancreatitis

There is universal agreement for offering urgent ERCP (within 24 hours) in biliary AP complicated by cholangitis.1-3,64 Figure 2 demonstrates an example of a cholangiogram completed within 24 hours of presentation of biliary AP complicated by cholangitis.

In the absence of cholangitis, the timing of ERCP for AP with persistent biliary obstruction is less clear.1-3 In line with recent guidelines, the 2018 AGA guidelines advocate against routine use of urgent ERCP for biliary AP without cholangitis,3 a conditional recommendation with overall low quality of data.4 The AGA technical review found that urgent ERCP, compared with conservative management in acute biliary pancreatitis without cholangitis had no significant effect on mortality, organ failure, infected pancreatic necrosis, and total necrotizing pancreatitis, but did significantly shorten hospital length of stay.4 There are limited data to guide decision making of when nonurgent ERCP should be performed in hospitalized patients with biliary AP with persistent obstruction and no cholangitis.3,64

 

 

Alcohol and smoking cessation

The AGA technical review advocates for brief alcohol intervention during hospitalization for alcohol-induced AP on the basis of one RCT that addresses the impact of alcohol counseling on recurrent bouts of AP4 plus evidence from a Cochrane review of alcohol-reduction strategies in primary care populations.65 Cessation of smoking – an established independent risk factor of AP – recurrent AP and chronic pancreatitis, should also be recommended as part of the management of AP.

Cholecystectomy

Evidence supports same-admission cholecystectomy for mild gallstone AP, a strong recommendation of published AGA guidelines.3 When compared with delayed cholecystectomy, same-admission cholecystectomy significantly reduced gallstone-related complications, readmissions for recurrent pancreatitis, and pancreaticobiliary complications, without having a significant impact on mortality during a 6-month follow-up period.66 Delaying cholecystectomy 6 weeks in patients with moderate-severe gallstone AP appears to reduce morbidity, including the development of infected collections, and mortality.4 An ongoing RCT, the APEC trial, aims to determine whether early ERCP with biliary sphincterotomy reduces major complications or death when compared with no intervention for biliary AP in patients at high risk of complications.67

Chemoprevention and IV fluid management of post-ERCP pancreatitis

Accumulating data support the effectiveness of chemoprevention, pancreatic stent placement, and fluid administration to prevent post-ERCP pancreatitis. Multiple RCTs, meta-analyses, and systematic reviews indicate that rectal NSAIDs) reduce post-ERCP pancreatitis onset68-71 and moderate-severe post-ERCP pancreatitis. Additionally, placement of a pancreatic duct stent may decrease the risk of severe post-ERCP pancreatitis in high-risk patients.3 Guidelines do not comment on fluid administrations for prevention of post-ERCP pancreatitis, but studies have shown that greater periprocedural IV fluid was an independent protective factor against moderate to severe PEP72 and was associated with shorter hospital length of stay.73 Recent meta-analyses and RCTs support using LR prior to ERCP to prevent PEP.74-77 Interestingly, a recent RCT shows that the combination of rectal indomethacin and LR, compared with combination placebo and normal saline reduced the risk of PEP in high-risk patients.78

Two ongoing multicenter RCTs will clarify the role of combination therapy. The Dutch FLUYT RCT aims to determine the optimal combination of rectal NSAIDs and periprocedural infusion of IV fluids to reduce the incidence of PEP and moderate-severe PEP79 and the Stent vs. Indomethacin (SVI) trial aims to determine the whether combination pancreatic stent placement plus rectal indomethacin is superior to monotherapy indomethacin for preventing post-ERCP pancreatitis in high-risk cases.80

Implications for clinical practice

The diagnosis and optimal management of AP require a systematic approach with multidisciplinary decision making. Morbidity and mortality in AP are driven by early or late POF, and the latter often is triggered by infected necrosis. Risk stratification of these patients at the point of contact is a commonsense approach to enable triaging of patients to the appropriate level of care. Regardless of pancreatitis severity, recommended treatment interventions include goal-directed IV fluid resuscitation, early feeding by mouth or enteral tube when necessary, avoidance of prophylactic antibiotics, avoidance of probiotics, and urgent ERCP for patients with acute biliary pancreatitis complicated by cholangitis. Key measures for preventing hospital readmission and pancreatitis include same-admission cholecystectomy for acute biliary pancreatitis and alcohol and smoking cessation. Preventive measures for post-ERCP pancreatitis in patients undergoing ERCP include rectal indomethacin, prophylactic pancreatic duct stent placement, and periprocedural fluid resuscitation.

Dr. Mandalia is a fellow, gastroenterology, department of internal medicine, division of gastroenterology, Michigan Medicine, Ann Arbor; Dr. DiMagno is associate professor of medicine, director, comprehensive pancreas program, department of internal medicine, division of gastroenterology, University of Michigan, Ann Arbor. Dr. Mandalia reports no conflicts of interest.

 

 

References

1. Tenner S et al. Am J Gastroenterol. 2013;108:1400.

2. Besseline M et al. Pancreatology. 2013;13(4, Supplement 2):e1-15.

3. Crockett SD et al. Gastroenterology. 2018;154(4):1096-101.

4. Vege SS et al. Gastroenterology. 2018;154(4):1103-39.

5. Peery AF et al. Gastroenterology. 2019 Jan;156(1):254-72.e11.

6. Krishna SG et al. Pancreas. 2017;46(4):482-8.

7. Sellers ZM et al. Gastroenterology. 2018;155(2):469-78.e1.

8. Brown A et al. JOP. 2008;9(4):408-14.

9. Fagenholz PJ et al. Ann Epidemiol. 2007;17(7):491.e1-.e8.

10. McNabb-Baltar J et al. Pancreas. 2014;43(5):687-91.

11. Johnson CD et al. Gut. 2004;53(9):1340-4.

12. Dellinger EP et al. Ann Surg. 2012;256(6):875-80.

13. Petrov MS et al. Gastroenterology. 2010;139(3):813-20.

14. Sternby H et al. Ann Surg. Apr 18. doi: 10.1097/SLA.0000000000002766.

15. Huh JH et al. J Clin Gastroenterol. 2018;52(2):178-83.

16. Wu BU et al. Gastroenterology. 2008;135(3):816-20.

17. Gardner TB et al. Clin Gastroenterol Hepatol. 2008;6(10):1070-6.

18. Krishna SG et al. Am J Gastroenterol. 2015;110(11):1608-19.

19. Lee PJ et al. Pancreas. 2016;45(4):561-4.

20. Mandalia A et al. F1000Research. 2018 Jun 28;7.

21. Majumder S et al. Pancreas. 2015;44(4):540-6.

22. DiMagno MJ. Clin Gastroenterol Hepatol. 2011;9(11):920-2.

23. Yadav D, Whitcomb DC. Nature Rev Gastroenterol Hepatol. 2010;7(3):131-45.

24. Samokhvalov AV et al. EBioMedicine. 2015;2(12):1996-2002.

25. Barkin JA et al. Pancreas. 2017;46(8):1035-8.

26. Chen Y-T et al. J Gastroenterol Hepatol. 2016;31(4):782-7.

27. Ramos LR et al. J Crohns Colitis. 2016;10(1):95-104.

28. Avram MM. Nephron. 1977;18(1):68-71.

29. Lankisch PG et al. Nephrol Dial Transplant. 2008;23(4):1401-5.

30. Owyang C et al. Mayo Clin Proc. 1979;54(12):769-73.

31. Owyang Cet al. Gut. 1982;23(5):357-61.

32. Quraishi ER et al. Am J Gastroenterol. 2005;100:2288.

33. Vaziri ND et al. Nephron. 1987;46(4):347-9.

34. Chen HJ et al. Nephrol Dial Transplant. 2017;32(10):1731-6.

35. Kirkegard J et al. Gastroenterology. 2018;May;154(6):1729-36.

36. Karlson BM, et al. Gastroenterology. 1997;113(2):587-92.

37. Munigala S et al. Clin Gastroenterol Hepatol. 2014;12(7):1143-50.e1.

38. Carr RA et al. Pancreatology. 2016;16(4):469-76.

39. Li X et al. BMC Gastroenterol. 2018;18(1):89.

40. Ahmed AU et al. Clin Gastroenterol Hepatol. 2016;14(5):738-46.

41. Sankaran SJ et al. Gastroenterology. 2015;149(6):1490-500.e1.

42. Berglund L et al. J Clin Endocrinol Metab. 2012;97(9):2969-89.

43. Catapano AL et al. Atherosclerosis. 2011;217(1):3-46.

44. Pedersen SB et al. JAMA Intern Med. 2016;176(12):1834-42.

45. Nawaz H et al. Am J Gastroenterol. 2015;110(10):1497-503.

46. Banks PA et al. Gut. 2013;62(1):102-11.

47. Kondo S et al. Eur J Radiol. 2005;54(2):271-5.

48. Meeralam Y et al. Gastrointest Endosc. 2017;86(6):986-93.

49. Stimac D et al. Am J Gastroenterol. 2007;102(5):997-1004.

50. Jin DX et al. Dig Dis Sci. 2017;62(10):2894-9.

51. Freeman ML. Gastrointest Endosc Clin N Am. 2012;22(3):567-86.

52. De Lisi S et al. Eur J Gastroenterol Hepatol. 2011;23(5):367-74.

53. Di MY et al. Ann Int Med. 2016;165(7):482-90.

54. Mounzer R et al. Gastroenterology. 2012;142(7):1476-82; quiz e15-6.

55. Koutroumpakis E et al. Am J Gastroenterol. 2015;110(12):1707-16.

56. Wu BU et al. Gastroenterology. 2009;137(1):129-35.

57. Buddingh KT et al. J Am Coll Surg. 2014;218(1):26-32.

58. Buxbaum J et al. Am J Gastroenterol. 2018;113(5):755-64.

59. Jabaudon M et al. Crit Car Med. 2018;46(3):e198-e205.

60. Barlass U et al. Gut. 2018;67(4):600-2.

61. Buxbaum JL et al. Am J Gastroenterol. 2017;112(5):797-803.

62. de-Madaria E et al. United Eur Gastroenterol J. 2018;6(1):63-72.

63. Bakker OJ et al. N Engl J Med. 2014;371(21):1983-93.

64. Tse F et al. Cochrane Database Syst Rev. 2012(5):Cd009779.

65. Kaner EFS et al. Cochrane Database Syst Rev. 2007(2):Cd004148.

66. da Costa DW et al. Lancet. 2015;386(10000):1261-8.

67. Schepers NJ et al. Trials. 2016;17:5.

68. Vadala di Prampero SF et al. Eur J Gastroenterol Hepatol. 2016;28(12):1415-24.

69. Kubiliun NM et al. Clin Gastroenterol Hepatol. 2015;13(7):1231-9; quiz e70-1.

70. Wan J et al. BMC Gastroenterol. 2017;17(1):43.

71. Yang C et al. Pancreatology. 2017;17(5):681-8.

72. DiMagno MJ et al. Pancreas. 2014;43(4):642-7.

73. Sagi SV et al. J Gastroenterol Hepatol. 2014;29(6):1316-20.

74. Choi JH et al. Clin Gastroenterol Hepatol. 2017;15(1):86-92.e1.

75. Wu D et al. J Clin Gastroenterol. 2017;51(8):e68-e76.

76. Zhang ZF et al. J Clin Gastroenterol. 2017;51(3):e17-e26.

77. Park CH et al. Endoscopy 2018 Apr;50(4):378-85.

78. Mok SRS et al. Gastrointest Endosc. 2017;85(5):1005-13.

79. Smeets XJN et al. Trials. 2018;19(1):207.

80. Elmunzer BJ et al. Trials. 2016;17(1):120.

 

Publications
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Topics
Pancreas and Biliary Tract
Sections
In Focus
The New Gastroenterologist
Video
Author(s)
Amar Mandalia, MD
Matthew J. Dimagno, MD, AGAF
Author(s)
Amar Mandalia, MD
Matthew J. Dimagno, MD, AGAF

 

Introduction

Acute pancreatitis (AP) is a major clinical and financial burden in the United States. Several major clinical guidelines provide evidence-based recommendations for the clinical management decisions in AP, including those from the American College of Gastroenterology (ACG; 2013),1 and the International Association of Pancreatology (IAP; 2013).2 More recently, the American Gastroenterological Association (AGA) released their own set of guidelines.3,4 In this update on AP, we review these guidelines and reference recent literature focused on epidemiology, risk factors, etiology, diagnosis, risk stratification, and recent advances in the early medical management of AP. Regarding the latter, we review six treatment interventions (pain management, intravenous fluid resuscitation, feeding, prophylactic antibiotics, probiotics, and timing of endoscopic retrograde cholangiopancreatography (ERCP) in acute biliary pancreatitis) and four preventive interventions (alcohol and smoking cessation, same-admission cholecystectomy for acute biliary pancreatitis, and chemoprevention and fluid administration for post-ERCP pancreatitis [PEP]). Updates on multidisciplinary management of (infected) pancreatic necrosis is beyond the scope of this review. Table 1 summarizes the concepts discussed in this article.

 

Recent advances in epidemiology and evaluation of AP

Epidemiology

AP is the third most common cause of gastrointestinal-related hospitalizations and fourth most common cause of readmission in 2014.5 Recent epidemiologic studies show conflicting trends for the incidence of AP, both increasing6 and decreasing,7 likely attributable to significant differences in study designs. Importantly, multiple studies have demonstrated that hospital length of stay, costs, and mortality have declined since 2009.6,8-10

Dr. Amar Mandalia

Persistent organ failure (POF), defined as organ failure lasting more than 48 hours, is the major cause of death in AP. POF, if only a single organ during AP, is associated with 27%-36% mortality; if it is multiorgan, it is associated with 47% mortality.1,11 Other factors associated with increased hospital mortality include infected pancreatic necrosis,12-14 diabetes mellitus,15 hospital-acquired infection,16 advanced age (70 years and older),17 and obesity.18 Predictive factors of 1-year mortality include readmission within 30 days, higher Charlson Comorbidity Index, and longer hospitalization.19

Risk factors

We briefly highlight recent insights into risk factors for AP (Table 1) and refer to a recent review for further discussion.20 Current and former tobacco use are independent risk factors for AP.21 The dose-response relationship of alcohol to the risk of pancreatitis is complex,22 but five standard drinks per day for 5 years is a commonly used cut-off.1,23 New evidence suggests that the relationship between the dose of alcohol and risk of AP differs by sex, linearly in men but nonlinearly (J-shaped) in women.24 Risk of AP in women was decreased with alcohol consumption of up to 40 g/day (one standard drink contains 14 g of alcohol) and increased above this amount. Cannabis is a possible risk factor for toxin-induced AP and abstinence appears to abolish risk of recurrent attacks.25

 

 

Patients with inflammatory bowel disease (IBD) have a 2.9-fold higher risk for AP versus non-IBD cohorts26 with the most common etiologies are from gallstones and medications.27 In patients with end-stage renal disease (ESRD), the risk of AP is higher in those who receive peritoneal dialysis, compared with hemodialysis28-33 and who are women, older, or have cholelithiasis or liver disease.34As recently reviewed,35 pancreatic cancer appears to be associated with first-attack pancreatitis with few exceptions.36 In this setting, the overall incidence of pancreatic cancer is low (1.5%). The risk is greatest within the first year of the attack of AP, negligible below age 40 years but steadily rising through the fifth to eighth decades.37 Pancreatic cancer screening is a conditional recommendation of the ACG guidelines in patients with unexplained AP, particularly those aged 40 years or older.1

Etiology and diagnosis


Alcohol and gallstones remain the most prevalent etiologies for AP.1 While hypertriglyceridemia accounted for 9% of AP in a systematic review of acute pancreatitis in 15 different countries,38 it is the second most common cause of acute pancreatitis in Asia (especially China).39 Figure 1 provides a breakdown of the etiologies and risk factors of pancreatitis. Importantly, it remains challenging to assign several toxic-metabolic etiologies as either a cause or risk factor for AP, particularly with regards to alcohol, smoking, and cannabis to name a few.

Guidelines and recent studies of AP raise questions about the threshold above which hypertriglyceridemia causes or poses as an important cofactor for AP. American and European societies define the threshold for triglycerides at 885-1,000 mg/dL.1,42,43 Pedersen et al. provide evidence of a graded risk of AP with hypertriglyceridemia: In multivariable analysis, adjusted hazard ratios for AP were much higher with nonfasting mild to moderately elevated plasma triglycerides (177-885 mg/dL), compared with normal values (below 89 mg/dL).44 Moreover, the risk of severe AP (developing POF) increases in proportion to triglyceride value, independent of the underlying cause of AP.45

Vidyard Video

Diagnosis of AP is derived from the revised Atlanta classification.46 The recommended timing and indications for offering cross-sectional imaging are after 48-72 hours in patients with no improvement to initial care.1 Endoscopic ultrasonography (EUS) has better diagnostic accuracy and sensitivity, compared with magnetic resonance cholangiopancreatography (MRCP) for choledocholithiasis, and has comparable specificity.47,48 Among noninvasive imaging modalities, MRCP is more sensitive than computed tomography (CT) for diagnosing choledocholithiasis.49 Despite guideline recommendations for more selective use of pancreatic imaging in the early assessment of AP, utilization of early CT or MRCP imaging (within the first 24 hours of care) remained high during 2014-2015, compared with 2006-2007.50

Dr. Matthew J. Di Magno

ERCP is not recommended as a pure diagnostic tool, owing to the availability of other diagnostic tests and a complication rate of 5%-10% with risks involving PEP, cholangitis, perforation, and hemorrhage.51 A recent systematic review of EUS and ERCP in acute biliary pancreatitis concluded that EUS had lower failure rates and had no complications, and the use of EUS avoided ERCP in 71.2% of cases.52

 

 

 

Risk stratification

The goals of using risk stratification tools in AP are to identify patients at risk for developing major outcomes, including POF, infected pancreatic necrosis, and death, and to ensure timely triaging of patients to an appropriate level of care. Existing prediction models have only moderate predictive value.53,54 Examples include simple risk stratification tools such as blood urea nitrogen (BUN) and hemoconcentration,55,56 disease-modifying patient variables (age, obesity, etc.), biomarkers (i.e., angiopoietin 2),57 and more complex clinical scoring systems such as Acute Physiology and Chronic Health Evaluation II (APACHE II), BISAP (BUN, impaired mental status, SIRS criteria, age, pleural effusion) score, early warning system (EWS), Glasgow-Imrie score, Japanese severity score, and recently the Pancreatitis Activity Scoring System (PASS).58 Two recent guidelines affirmed the importance of predicting the severity of AP, using one or more predictive tools.1,2 The recent 2018 AGA technical review does not debate this commonsense approach, but does highlight that there is no published observational study or randomized, controlled trial (RCT) investigating whether prediction tools affect clinical outcomes.4

Recent advances in early treatment of AP

Literature review and definitions

The AP literature contains heterogeneous definitions of severe AP and of what constitutes a major outcome in AP. Based on definitions of the 2013 revised Atlanta Criteria, the 2018 AGA technical review and clinical guidelines emphasized precise definitions of primary outcomes of clinical importance in AP, including death, persistent single organ failure, or persistent multiple organ failure, each requiring a duration of more than 48 hours, and infected pancreatic or peripancreatic necrosis or both (Table 2).3,4

 

Pain management

Management of pain in AP is complex and requires a detailed discussion beyond the scope of this review, but recent clinical and translational studies raise questions about the current practice of using opioids for pain management in AP. A provocative, multicenter, retrospective cohort study reported lower 30-day mortality among critically ill patients who received epidural analgesia versus standard care without epidural analgesia.59 The possible mechanism of protection and the drugs administered are unclear. An interesting hypothesis is that the epidural cohort may have received lower exposure to morphine, which may increase gut permeability, the risk of infectious complications, and severity of AP, based on a translational study in mice.60

Intravenous fluid administration

Supportive care with the use of IV fluid hydration is a mainstay of treatment for AP in the first 12-24 hours. Table 3 summarizes the guidelines in regards to IV fluid administration as delineated by the ACG and AGA guidelines on the management of pancreatitis.1,3 Guidelines advocate for early fluid resuscitation to correct intravascular depletion in order to reduce morbidity and mortality associated with AP.1,2,4 The 2018 AGA guidelines endorse a conditional recommendation for using goal-directed therapy for initial fluid management,3 do not recommend for or against normal saline versus lactated Ringer’s (LR), but do advise against the use of hydroxyethyl starch fluids.3 Consistent with these recommendations, two recent RCTs published subsequent to the prespecified time periods of the AGA technical review and guideline, observed no significant differences between LR and normal saline on clinically meaningful outcomes.61,62 The AGA guidelines acknowledge that evidence was of very-low quality in support of goal-directed therapy,3,4 which has not been shown to have a significant reduction in persistent multiple organ failure, mortality, or pancreatic necrosis, compared with usual care. As the authors noted, interpretation of the data was limited by the absence of other critical outcomes in these trials (infected pancreatic necrosis), lack of uniformity of specific outcomes and definitions of transient and POF, few trials, and risk of bias. There is a clear need for a large RCT to provide evidence to guide decision making with fluid resuscitation in AP, particularly in regard to fluid type, volume, rate, duration, endpoints, and clinical outcomes.

 

 

Feeding

More recently, the focus of nutrition in the management of AP has shifted away from patients remaining nil per os (NPO). Current guidelines advocate for early oral feeding (within 24 hours) in mild AP,3,4 in order to protect the gut-mucosal barrier. Remaining NPO when compared with early oral feeding has a 2.5-fold higher risk for interventions for necrosis.4 The recently published AGA technical review identified no significant impact on outcomes of early versus delayed oral feeding, which is consistent with observations of a landmark Dutch PYTHON trial entitled “Early versus on-demand nasoenteric tube feeding in acute pancreatitis.”4,63 There is no clear cutoff point for initiating feeding for those with severe AP. A suggested practical approach is to initiate feeding within 24-72 hours and offer enteral nutrition for those intolerant to oral feeds. In severe AP and moderately severe AP, enteral nutrition is recommended over parenteral nutrition.3,4 Enteral nutrition significantly reduces the risk of infected peripancreatic necrosis, single organ failure, and multiorgan failure.4 Finally, the AGA guidelines provide a conditional recommendation for providing enteral nutrition support through either the nasogastric or nasoenteric route.3 Further studies are required to determine the optimal timing, rate, and formulation of enteral nutrition in severe AP.

 

Antibiotics and probiotics

Current guidelines do not support the use of prophylactic antibiotics to prevent infection in necrotizing AP and severe AP.1-3 The AGA technical review reported that prophylactic antibiotics did not reduce infected pancreatic or peripancreatic necrosis, persistent single organ failure, or mortality.4 Guidelines advocate against the use of probiotics for severe AP, because of increased mortality risk.1

Figure 2: Urgent ERCP for acute biliary pancreatitis with cholangitis.

Timing of ERCP in acute biliary pancreatitis

There is universal agreement for offering urgent ERCP (within 24 hours) in biliary AP complicated by cholangitis.1-3,64 Figure 2 demonstrates an example of a cholangiogram completed within 24 hours of presentation of biliary AP complicated by cholangitis.

In the absence of cholangitis, the timing of ERCP for AP with persistent biliary obstruction is less clear.1-3 In line with recent guidelines, the 2018 AGA guidelines advocate against routine use of urgent ERCP for biliary AP without cholangitis,3 a conditional recommendation with overall low quality of data.4 The AGA technical review found that urgent ERCP, compared with conservative management in acute biliary pancreatitis without cholangitis had no significant effect on mortality, organ failure, infected pancreatic necrosis, and total necrotizing pancreatitis, but did significantly shorten hospital length of stay.4 There are limited data to guide decision making of when nonurgent ERCP should be performed in hospitalized patients with biliary AP with persistent obstruction and no cholangitis.3,64

 

 

Alcohol and smoking cessation

The AGA technical review advocates for brief alcohol intervention during hospitalization for alcohol-induced AP on the basis of one RCT that addresses the impact of alcohol counseling on recurrent bouts of AP4 plus evidence from a Cochrane review of alcohol-reduction strategies in primary care populations.65 Cessation of smoking – an established independent risk factor of AP – recurrent AP and chronic pancreatitis, should also be recommended as part of the management of AP.

Cholecystectomy

Evidence supports same-admission cholecystectomy for mild gallstone AP, a strong recommendation of published AGA guidelines.3 When compared with delayed cholecystectomy, same-admission cholecystectomy significantly reduced gallstone-related complications, readmissions for recurrent pancreatitis, and pancreaticobiliary complications, without having a significant impact on mortality during a 6-month follow-up period.66 Delaying cholecystectomy 6 weeks in patients with moderate-severe gallstone AP appears to reduce morbidity, including the development of infected collections, and mortality.4 An ongoing RCT, the APEC trial, aims to determine whether early ERCP with biliary sphincterotomy reduces major complications or death when compared with no intervention for biliary AP in patients at high risk of complications.67

Chemoprevention and IV fluid management of post-ERCP pancreatitis

Accumulating data support the effectiveness of chemoprevention, pancreatic stent placement, and fluid administration to prevent post-ERCP pancreatitis. Multiple RCTs, meta-analyses, and systematic reviews indicate that rectal NSAIDs) reduce post-ERCP pancreatitis onset68-71 and moderate-severe post-ERCP pancreatitis. Additionally, placement of a pancreatic duct stent may decrease the risk of severe post-ERCP pancreatitis in high-risk patients.3 Guidelines do not comment on fluid administrations for prevention of post-ERCP pancreatitis, but studies have shown that greater periprocedural IV fluid was an independent protective factor against moderate to severe PEP72 and was associated with shorter hospital length of stay.73 Recent meta-analyses and RCTs support using LR prior to ERCP to prevent PEP.74-77 Interestingly, a recent RCT shows that the combination of rectal indomethacin and LR, compared with combination placebo and normal saline reduced the risk of PEP in high-risk patients.78

Two ongoing multicenter RCTs will clarify the role of combination therapy. The Dutch FLUYT RCT aims to determine the optimal combination of rectal NSAIDs and periprocedural infusion of IV fluids to reduce the incidence of PEP and moderate-severe PEP79 and the Stent vs. Indomethacin (SVI) trial aims to determine the whether combination pancreatic stent placement plus rectal indomethacin is superior to monotherapy indomethacin for preventing post-ERCP pancreatitis in high-risk cases.80

Implications for clinical practice

The diagnosis and optimal management of AP require a systematic approach with multidisciplinary decision making. Morbidity and mortality in AP are driven by early or late POF, and the latter often is triggered by infected necrosis. Risk stratification of these patients at the point of contact is a commonsense approach to enable triaging of patients to the appropriate level of care. Regardless of pancreatitis severity, recommended treatment interventions include goal-directed IV fluid resuscitation, early feeding by mouth or enteral tube when necessary, avoidance of prophylactic antibiotics, avoidance of probiotics, and urgent ERCP for patients with acute biliary pancreatitis complicated by cholangitis. Key measures for preventing hospital readmission and pancreatitis include same-admission cholecystectomy for acute biliary pancreatitis and alcohol and smoking cessation. Preventive measures for post-ERCP pancreatitis in patients undergoing ERCP include rectal indomethacin, prophylactic pancreatic duct stent placement, and periprocedural fluid resuscitation.

Dr. Mandalia is a fellow, gastroenterology, department of internal medicine, division of gastroenterology, Michigan Medicine, Ann Arbor; Dr. DiMagno is associate professor of medicine, director, comprehensive pancreas program, department of internal medicine, division of gastroenterology, University of Michigan, Ann Arbor. Dr. Mandalia reports no conflicts of interest.

 

 

References

1. Tenner S et al. Am J Gastroenterol. 2013;108:1400.

2. Besseline M et al. Pancreatology. 2013;13(4, Supplement 2):e1-15.

3. Crockett SD et al. Gastroenterology. 2018;154(4):1096-101.

4. Vege SS et al. Gastroenterology. 2018;154(4):1103-39.

5. Peery AF et al. Gastroenterology. 2019 Jan;156(1):254-72.e11.

6. Krishna SG et al. Pancreas. 2017;46(4):482-8.

7. Sellers ZM et al. Gastroenterology. 2018;155(2):469-78.e1.

8. Brown A et al. JOP. 2008;9(4):408-14.

9. Fagenholz PJ et al. Ann Epidemiol. 2007;17(7):491.e1-.e8.

10. McNabb-Baltar J et al. Pancreas. 2014;43(5):687-91.

11. Johnson CD et al. Gut. 2004;53(9):1340-4.

12. Dellinger EP et al. Ann Surg. 2012;256(6):875-80.

13. Petrov MS et al. Gastroenterology. 2010;139(3):813-20.

14. Sternby H et al. Ann Surg. Apr 18. doi: 10.1097/SLA.0000000000002766.

15. Huh JH et al. J Clin Gastroenterol. 2018;52(2):178-83.

16. Wu BU et al. Gastroenterology. 2008;135(3):816-20.

17. Gardner TB et al. Clin Gastroenterol Hepatol. 2008;6(10):1070-6.

18. Krishna SG et al. Am J Gastroenterol. 2015;110(11):1608-19.

19. Lee PJ et al. Pancreas. 2016;45(4):561-4.

20. Mandalia A et al. F1000Research. 2018 Jun 28;7.

21. Majumder S et al. Pancreas. 2015;44(4):540-6.

22. DiMagno MJ. Clin Gastroenterol Hepatol. 2011;9(11):920-2.

23. Yadav D, Whitcomb DC. Nature Rev Gastroenterol Hepatol. 2010;7(3):131-45.

24. Samokhvalov AV et al. EBioMedicine. 2015;2(12):1996-2002.

25. Barkin JA et al. Pancreas. 2017;46(8):1035-8.

26. Chen Y-T et al. J Gastroenterol Hepatol. 2016;31(4):782-7.

27. Ramos LR et al. J Crohns Colitis. 2016;10(1):95-104.

28. Avram MM. Nephron. 1977;18(1):68-71.

29. Lankisch PG et al. Nephrol Dial Transplant. 2008;23(4):1401-5.

30. Owyang C et al. Mayo Clin Proc. 1979;54(12):769-73.

31. Owyang Cet al. Gut. 1982;23(5):357-61.

32. Quraishi ER et al. Am J Gastroenterol. 2005;100:2288.

33. Vaziri ND et al. Nephron. 1987;46(4):347-9.

34. Chen HJ et al. Nephrol Dial Transplant. 2017;32(10):1731-6.

35. Kirkegard J et al. Gastroenterology. 2018;May;154(6):1729-36.

36. Karlson BM, et al. Gastroenterology. 1997;113(2):587-92.

37. Munigala S et al. Clin Gastroenterol Hepatol. 2014;12(7):1143-50.e1.

38. Carr RA et al. Pancreatology. 2016;16(4):469-76.

39. Li X et al. BMC Gastroenterol. 2018;18(1):89.

40. Ahmed AU et al. Clin Gastroenterol Hepatol. 2016;14(5):738-46.

41. Sankaran SJ et al. Gastroenterology. 2015;149(6):1490-500.e1.

42. Berglund L et al. J Clin Endocrinol Metab. 2012;97(9):2969-89.

43. Catapano AL et al. Atherosclerosis. 2011;217(1):3-46.

44. Pedersen SB et al. JAMA Intern Med. 2016;176(12):1834-42.

45. Nawaz H et al. Am J Gastroenterol. 2015;110(10):1497-503.

46. Banks PA et al. Gut. 2013;62(1):102-11.

47. Kondo S et al. Eur J Radiol. 2005;54(2):271-5.

48. Meeralam Y et al. Gastrointest Endosc. 2017;86(6):986-93.

49. Stimac D et al. Am J Gastroenterol. 2007;102(5):997-1004.

50. Jin DX et al. Dig Dis Sci. 2017;62(10):2894-9.

51. Freeman ML. Gastrointest Endosc Clin N Am. 2012;22(3):567-86.

52. De Lisi S et al. Eur J Gastroenterol Hepatol. 2011;23(5):367-74.

53. Di MY et al. Ann Int Med. 2016;165(7):482-90.

54. Mounzer R et al. Gastroenterology. 2012;142(7):1476-82; quiz e15-6.

55. Koutroumpakis E et al. Am J Gastroenterol. 2015;110(12):1707-16.

56. Wu BU et al. Gastroenterology. 2009;137(1):129-35.

57. Buddingh KT et al. J Am Coll Surg. 2014;218(1):26-32.

58. Buxbaum J et al. Am J Gastroenterol. 2018;113(5):755-64.

59. Jabaudon M et al. Crit Car Med. 2018;46(3):e198-e205.

60. Barlass U et al. Gut. 2018;67(4):600-2.

61. Buxbaum JL et al. Am J Gastroenterol. 2017;112(5):797-803.

62. de-Madaria E et al. United Eur Gastroenterol J. 2018;6(1):63-72.

63. Bakker OJ et al. N Engl J Med. 2014;371(21):1983-93.

64. Tse F et al. Cochrane Database Syst Rev. 2012(5):Cd009779.

65. Kaner EFS et al. Cochrane Database Syst Rev. 2007(2):Cd004148.

66. da Costa DW et al. Lancet. 2015;386(10000):1261-8.

67. Schepers NJ et al. Trials. 2016;17:5.

68. Vadala di Prampero SF et al. Eur J Gastroenterol Hepatol. 2016;28(12):1415-24.

69. Kubiliun NM et al. Clin Gastroenterol Hepatol. 2015;13(7):1231-9; quiz e70-1.

70. Wan J et al. BMC Gastroenterol. 2017;17(1):43.

71. Yang C et al. Pancreatology. 2017;17(5):681-8.

72. DiMagno MJ et al. Pancreas. 2014;43(4):642-7.

73. Sagi SV et al. J Gastroenterol Hepatol. 2014;29(6):1316-20.

74. Choi JH et al. Clin Gastroenterol Hepatol. 2017;15(1):86-92.e1.

75. Wu D et al. J Clin Gastroenterol. 2017;51(8):e68-e76.

76. Zhang ZF et al. J Clin Gastroenterol. 2017;51(3):e17-e26.

77. Park CH et al. Endoscopy 2018 Apr;50(4):378-85.

78. Mok SRS et al. Gastrointest Endosc. 2017;85(5):1005-13.

79. Smeets XJN et al. Trials. 2018;19(1):207.

80. Elmunzer BJ et al. Trials. 2016;17(1):120.

 

 

Introduction

Acute pancreatitis (AP) is a major clinical and financial burden in the United States. Several major clinical guidelines provide evidence-based recommendations for the clinical management decisions in AP, including those from the American College of Gastroenterology (ACG; 2013),1 and the International Association of Pancreatology (IAP; 2013).2 More recently, the American Gastroenterological Association (AGA) released their own set of guidelines.3,4 In this update on AP, we review these guidelines and reference recent literature focused on epidemiology, risk factors, etiology, diagnosis, risk stratification, and recent advances in the early medical management of AP. Regarding the latter, we review six treatment interventions (pain management, intravenous fluid resuscitation, feeding, prophylactic antibiotics, probiotics, and timing of endoscopic retrograde cholangiopancreatography (ERCP) in acute biliary pancreatitis) and four preventive interventions (alcohol and smoking cessation, same-admission cholecystectomy for acute biliary pancreatitis, and chemoprevention and fluid administration for post-ERCP pancreatitis [PEP]). Updates on multidisciplinary management of (infected) pancreatic necrosis is beyond the scope of this review. Table 1 summarizes the concepts discussed in this article.

 

Recent advances in epidemiology and evaluation of AP

Epidemiology

AP is the third most common cause of gastrointestinal-related hospitalizations and fourth most common cause of readmission in 2014.5 Recent epidemiologic studies show conflicting trends for the incidence of AP, both increasing6 and decreasing,7 likely attributable to significant differences in study designs. Importantly, multiple studies have demonstrated that hospital length of stay, costs, and mortality have declined since 2009.6,8-10

Dr. Amar Mandalia

Persistent organ failure (POF), defined as organ failure lasting more than 48 hours, is the major cause of death in AP. POF, if only a single organ during AP, is associated with 27%-36% mortality; if it is multiorgan, it is associated with 47% mortality.1,11 Other factors associated with increased hospital mortality include infected pancreatic necrosis,12-14 diabetes mellitus,15 hospital-acquired infection,16 advanced age (70 years and older),17 and obesity.18 Predictive factors of 1-year mortality include readmission within 30 days, higher Charlson Comorbidity Index, and longer hospitalization.19

Risk factors

We briefly highlight recent insights into risk factors for AP (Table 1) and refer to a recent review for further discussion.20 Current and former tobacco use are independent risk factors for AP.21 The dose-response relationship of alcohol to the risk of pancreatitis is complex,22 but five standard drinks per day for 5 years is a commonly used cut-off.1,23 New evidence suggests that the relationship between the dose of alcohol and risk of AP differs by sex, linearly in men but nonlinearly (J-shaped) in women.24 Risk of AP in women was decreased with alcohol consumption of up to 40 g/day (one standard drink contains 14 g of alcohol) and increased above this amount. Cannabis is a possible risk factor for toxin-induced AP and abstinence appears to abolish risk of recurrent attacks.25

 

 

Patients with inflammatory bowel disease (IBD) have a 2.9-fold higher risk for AP versus non-IBD cohorts26 with the most common etiologies are from gallstones and medications.27 In patients with end-stage renal disease (ESRD), the risk of AP is higher in those who receive peritoneal dialysis, compared with hemodialysis28-33 and who are women, older, or have cholelithiasis or liver disease.34As recently reviewed,35 pancreatic cancer appears to be associated with first-attack pancreatitis with few exceptions.36 In this setting, the overall incidence of pancreatic cancer is low (1.5%). The risk is greatest within the first year of the attack of AP, negligible below age 40 years but steadily rising through the fifth to eighth decades.37 Pancreatic cancer screening is a conditional recommendation of the ACG guidelines in patients with unexplained AP, particularly those aged 40 years or older.1

Etiology and diagnosis


Alcohol and gallstones remain the most prevalent etiologies for AP.1 While hypertriglyceridemia accounted for 9% of AP in a systematic review of acute pancreatitis in 15 different countries,38 it is the second most common cause of acute pancreatitis in Asia (especially China).39 Figure 1 provides a breakdown of the etiologies and risk factors of pancreatitis. Importantly, it remains challenging to assign several toxic-metabolic etiologies as either a cause or risk factor for AP, particularly with regards to alcohol, smoking, and cannabis to name a few.

Guidelines and recent studies of AP raise questions about the threshold above which hypertriglyceridemia causes or poses as an important cofactor for AP. American and European societies define the threshold for triglycerides at 885-1,000 mg/dL.1,42,43 Pedersen et al. provide evidence of a graded risk of AP with hypertriglyceridemia: In multivariable analysis, adjusted hazard ratios for AP were much higher with nonfasting mild to moderately elevated plasma triglycerides (177-885 mg/dL), compared with normal values (below 89 mg/dL).44 Moreover, the risk of severe AP (developing POF) increases in proportion to triglyceride value, independent of the underlying cause of AP.45

Vidyard Video

Diagnosis of AP is derived from the revised Atlanta classification.46 The recommended timing and indications for offering cross-sectional imaging are after 48-72 hours in patients with no improvement to initial care.1 Endoscopic ultrasonography (EUS) has better diagnostic accuracy and sensitivity, compared with magnetic resonance cholangiopancreatography (MRCP) for choledocholithiasis, and has comparable specificity.47,48 Among noninvasive imaging modalities, MRCP is more sensitive than computed tomography (CT) for diagnosing choledocholithiasis.49 Despite guideline recommendations for more selective use of pancreatic imaging in the early assessment of AP, utilization of early CT or MRCP imaging (within the first 24 hours of care) remained high during 2014-2015, compared with 2006-2007.50

Dr. Matthew J. Di Magno

ERCP is not recommended as a pure diagnostic tool, owing to the availability of other diagnostic tests and a complication rate of 5%-10% with risks involving PEP, cholangitis, perforation, and hemorrhage.51 A recent systematic review of EUS and ERCP in acute biliary pancreatitis concluded that EUS had lower failure rates and had no complications, and the use of EUS avoided ERCP in 71.2% of cases.52

 

 

 

Risk stratification

The goals of using risk stratification tools in AP are to identify patients at risk for developing major outcomes, including POF, infected pancreatic necrosis, and death, and to ensure timely triaging of patients to an appropriate level of care. Existing prediction models have only moderate predictive value.53,54 Examples include simple risk stratification tools such as blood urea nitrogen (BUN) and hemoconcentration,55,56 disease-modifying patient variables (age, obesity, etc.), biomarkers (i.e., angiopoietin 2),57 and more complex clinical scoring systems such as Acute Physiology and Chronic Health Evaluation II (APACHE II), BISAP (BUN, impaired mental status, SIRS criteria, age, pleural effusion) score, early warning system (EWS), Glasgow-Imrie score, Japanese severity score, and recently the Pancreatitis Activity Scoring System (PASS).58 Two recent guidelines affirmed the importance of predicting the severity of AP, using one or more predictive tools.1,2 The recent 2018 AGA technical review does not debate this commonsense approach, but does highlight that there is no published observational study or randomized, controlled trial (RCT) investigating whether prediction tools affect clinical outcomes.4

Recent advances in early treatment of AP

Literature review and definitions

The AP literature contains heterogeneous definitions of severe AP and of what constitutes a major outcome in AP. Based on definitions of the 2013 revised Atlanta Criteria, the 2018 AGA technical review and clinical guidelines emphasized precise definitions of primary outcomes of clinical importance in AP, including death, persistent single organ failure, or persistent multiple organ failure, each requiring a duration of more than 48 hours, and infected pancreatic or peripancreatic necrosis or both (Table 2).3,4

 

Pain management

Management of pain in AP is complex and requires a detailed discussion beyond the scope of this review, but recent clinical and translational studies raise questions about the current practice of using opioids for pain management in AP. A provocative, multicenter, retrospective cohort study reported lower 30-day mortality among critically ill patients who received epidural analgesia versus standard care without epidural analgesia.59 The possible mechanism of protection and the drugs administered are unclear. An interesting hypothesis is that the epidural cohort may have received lower exposure to morphine, which may increase gut permeability, the risk of infectious complications, and severity of AP, based on a translational study in mice.60

Intravenous fluid administration

Supportive care with the use of IV fluid hydration is a mainstay of treatment for AP in the first 12-24 hours. Table 3 summarizes the guidelines in regards to IV fluid administration as delineated by the ACG and AGA guidelines on the management of pancreatitis.1,3 Guidelines advocate for early fluid resuscitation to correct intravascular depletion in order to reduce morbidity and mortality associated with AP.1,2,4 The 2018 AGA guidelines endorse a conditional recommendation for using goal-directed therapy for initial fluid management,3 do not recommend for or against normal saline versus lactated Ringer’s (LR), but do advise against the use of hydroxyethyl starch fluids.3 Consistent with these recommendations, two recent RCTs published subsequent to the prespecified time periods of the AGA technical review and guideline, observed no significant differences between LR and normal saline on clinically meaningful outcomes.61,62 The AGA guidelines acknowledge that evidence was of very-low quality in support of goal-directed therapy,3,4 which has not been shown to have a significant reduction in persistent multiple organ failure, mortality, or pancreatic necrosis, compared with usual care. As the authors noted, interpretation of the data was limited by the absence of other critical outcomes in these trials (infected pancreatic necrosis), lack of uniformity of specific outcomes and definitions of transient and POF, few trials, and risk of bias. There is a clear need for a large RCT to provide evidence to guide decision making with fluid resuscitation in AP, particularly in regard to fluid type, volume, rate, duration, endpoints, and clinical outcomes.

 

 

Feeding

More recently, the focus of nutrition in the management of AP has shifted away from patients remaining nil per os (NPO). Current guidelines advocate for early oral feeding (within 24 hours) in mild AP,3,4 in order to protect the gut-mucosal barrier. Remaining NPO when compared with early oral feeding has a 2.5-fold higher risk for interventions for necrosis.4 The recently published AGA technical review identified no significant impact on outcomes of early versus delayed oral feeding, which is consistent with observations of a landmark Dutch PYTHON trial entitled “Early versus on-demand nasoenteric tube feeding in acute pancreatitis.”4,63 There is no clear cutoff point for initiating feeding for those with severe AP. A suggested practical approach is to initiate feeding within 24-72 hours and offer enteral nutrition for those intolerant to oral feeds. In severe AP and moderately severe AP, enteral nutrition is recommended over parenteral nutrition.3,4 Enteral nutrition significantly reduces the risk of infected peripancreatic necrosis, single organ failure, and multiorgan failure.4 Finally, the AGA guidelines provide a conditional recommendation for providing enteral nutrition support through either the nasogastric or nasoenteric route.3 Further studies are required to determine the optimal timing, rate, and formulation of enteral nutrition in severe AP.

 

Antibiotics and probiotics

Current guidelines do not support the use of prophylactic antibiotics to prevent infection in necrotizing AP and severe AP.1-3 The AGA technical review reported that prophylactic antibiotics did not reduce infected pancreatic or peripancreatic necrosis, persistent single organ failure, or mortality.4 Guidelines advocate against the use of probiotics for severe AP, because of increased mortality risk.1

Figure 2: Urgent ERCP for acute biliary pancreatitis with cholangitis.

Timing of ERCP in acute biliary pancreatitis

There is universal agreement for offering urgent ERCP (within 24 hours) in biliary AP complicated by cholangitis.1-3,64 Figure 2 demonstrates an example of a cholangiogram completed within 24 hours of presentation of biliary AP complicated by cholangitis.

In the absence of cholangitis, the timing of ERCP for AP with persistent biliary obstruction is less clear.1-3 In line with recent guidelines, the 2018 AGA guidelines advocate against routine use of urgent ERCP for biliary AP without cholangitis,3 a conditional recommendation with overall low quality of data.4 The AGA technical review found that urgent ERCP, compared with conservative management in acute biliary pancreatitis without cholangitis had no significant effect on mortality, organ failure, infected pancreatic necrosis, and total necrotizing pancreatitis, but did significantly shorten hospital length of stay.4 There are limited data to guide decision making of when nonurgent ERCP should be performed in hospitalized patients with biliary AP with persistent obstruction and no cholangitis.3,64

 

 

Alcohol and smoking cessation

The AGA technical review advocates for brief alcohol intervention during hospitalization for alcohol-induced AP on the basis of one RCT that addresses the impact of alcohol counseling on recurrent bouts of AP4 plus evidence from a Cochrane review of alcohol-reduction strategies in primary care populations.65 Cessation of smoking – an established independent risk factor of AP – recurrent AP and chronic pancreatitis, should also be recommended as part of the management of AP.

Cholecystectomy

Evidence supports same-admission cholecystectomy for mild gallstone AP, a strong recommendation of published AGA guidelines.3 When compared with delayed cholecystectomy, same-admission cholecystectomy significantly reduced gallstone-related complications, readmissions for recurrent pancreatitis, and pancreaticobiliary complications, without having a significant impact on mortality during a 6-month follow-up period.66 Delaying cholecystectomy 6 weeks in patients with moderate-severe gallstone AP appears to reduce morbidity, including the development of infected collections, and mortality.4 An ongoing RCT, the APEC trial, aims to determine whether early ERCP with biliary sphincterotomy reduces major complications or death when compared with no intervention for biliary AP in patients at high risk of complications.67

Chemoprevention and IV fluid management of post-ERCP pancreatitis

Accumulating data support the effectiveness of chemoprevention, pancreatic stent placement, and fluid administration to prevent post-ERCP pancreatitis. Multiple RCTs, meta-analyses, and systematic reviews indicate that rectal NSAIDs) reduce post-ERCP pancreatitis onset68-71 and moderate-severe post-ERCP pancreatitis. Additionally, placement of a pancreatic duct stent may decrease the risk of severe post-ERCP pancreatitis in high-risk patients.3 Guidelines do not comment on fluid administrations for prevention of post-ERCP pancreatitis, but studies have shown that greater periprocedural IV fluid was an independent protective factor against moderate to severe PEP72 and was associated with shorter hospital length of stay.73 Recent meta-analyses and RCTs support using LR prior to ERCP to prevent PEP.74-77 Interestingly, a recent RCT shows that the combination of rectal indomethacin and LR, compared with combination placebo and normal saline reduced the risk of PEP in high-risk patients.78

Two ongoing multicenter RCTs will clarify the role of combination therapy. The Dutch FLUYT RCT aims to determine the optimal combination of rectal NSAIDs and periprocedural infusion of IV fluids to reduce the incidence of PEP and moderate-severe PEP79 and the Stent vs. Indomethacin (SVI) trial aims to determine the whether combination pancreatic stent placement plus rectal indomethacin is superior to monotherapy indomethacin for preventing post-ERCP pancreatitis in high-risk cases.80

Implications for clinical practice

The diagnosis and optimal management of AP require a systematic approach with multidisciplinary decision making. Morbidity and mortality in AP are driven by early or late POF, and the latter often is triggered by infected necrosis. Risk stratification of these patients at the point of contact is a commonsense approach to enable triaging of patients to the appropriate level of care. Regardless of pancreatitis severity, recommended treatment interventions include goal-directed IV fluid resuscitation, early feeding by mouth or enteral tube when necessary, avoidance of prophylactic antibiotics, avoidance of probiotics, and urgent ERCP for patients with acute biliary pancreatitis complicated by cholangitis. Key measures for preventing hospital readmission and pancreatitis include same-admission cholecystectomy for acute biliary pancreatitis and alcohol and smoking cessation. Preventive measures for post-ERCP pancreatitis in patients undergoing ERCP include rectal indomethacin, prophylactic pancreatic duct stent placement, and periprocedural fluid resuscitation.

Dr. Mandalia is a fellow, gastroenterology, department of internal medicine, division of gastroenterology, Michigan Medicine, Ann Arbor; Dr. DiMagno is associate professor of medicine, director, comprehensive pancreas program, department of internal medicine, division of gastroenterology, University of Michigan, Ann Arbor. Dr. Mandalia reports no conflicts of interest.

 

 

References

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4. Vege SS et al. Gastroenterology. 2018;154(4):1103-39.

5. Peery AF et al. Gastroenterology. 2019 Jan;156(1):254-72.e11.

6. Krishna SG et al. Pancreas. 2017;46(4):482-8.

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8. Brown A et al. JOP. 2008;9(4):408-14.

9. Fagenholz PJ et al. Ann Epidemiol. 2007;17(7):491.e1-.e8.

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12. Dellinger EP et al. Ann Surg. 2012;256(6):875-80.

13. Petrov MS et al. Gastroenterology. 2010;139(3):813-20.

14. Sternby H et al. Ann Surg. Apr 18. doi: 10.1097/SLA.0000000000002766.

15. Huh JH et al. J Clin Gastroenterol. 2018;52(2):178-83.

16. Wu BU et al. Gastroenterology. 2008;135(3):816-20.

17. Gardner TB et al. Clin Gastroenterol Hepatol. 2008;6(10):1070-6.

18. Krishna SG et al. Am J Gastroenterol. 2015;110(11):1608-19.

19. Lee PJ et al. Pancreas. 2016;45(4):561-4.

20. Mandalia A et al. F1000Research. 2018 Jun 28;7.

21. Majumder S et al. Pancreas. 2015;44(4):540-6.

22. DiMagno MJ. Clin Gastroenterol Hepatol. 2011;9(11):920-2.

23. Yadav D, Whitcomb DC. Nature Rev Gastroenterol Hepatol. 2010;7(3):131-45.

24. Samokhvalov AV et al. EBioMedicine. 2015;2(12):1996-2002.

25. Barkin JA et al. Pancreas. 2017;46(8):1035-8.

26. Chen Y-T et al. J Gastroenterol Hepatol. 2016;31(4):782-7.

27. Ramos LR et al. J Crohns Colitis. 2016;10(1):95-104.

28. Avram MM. Nephron. 1977;18(1):68-71.

29. Lankisch PG et al. Nephrol Dial Transplant. 2008;23(4):1401-5.

30. Owyang C et al. Mayo Clin Proc. 1979;54(12):769-73.

31. Owyang Cet al. Gut. 1982;23(5):357-61.

32. Quraishi ER et al. Am J Gastroenterol. 2005;100:2288.

33. Vaziri ND et al. Nephron. 1987;46(4):347-9.

34. Chen HJ et al. Nephrol Dial Transplant. 2017;32(10):1731-6.

35. Kirkegard J et al. Gastroenterology. 2018;May;154(6):1729-36.

36. Karlson BM, et al. Gastroenterology. 1997;113(2):587-92.

37. Munigala S et al. Clin Gastroenterol Hepatol. 2014;12(7):1143-50.e1.

38. Carr RA et al. Pancreatology. 2016;16(4):469-76.

39. Li X et al. BMC Gastroenterol. 2018;18(1):89.

40. Ahmed AU et al. Clin Gastroenterol Hepatol. 2016;14(5):738-46.

41. Sankaran SJ et al. Gastroenterology. 2015;149(6):1490-500.e1.

42. Berglund L et al. J Clin Endocrinol Metab. 2012;97(9):2969-89.

43. Catapano AL et al. Atherosclerosis. 2011;217(1):3-46.

44. Pedersen SB et al. JAMA Intern Med. 2016;176(12):1834-42.

45. Nawaz H et al. Am J Gastroenterol. 2015;110(10):1497-503.

46. Banks PA et al. Gut. 2013;62(1):102-11.

47. Kondo S et al. Eur J Radiol. 2005;54(2):271-5.

48. Meeralam Y et al. Gastrointest Endosc. 2017;86(6):986-93.

49. Stimac D et al. Am J Gastroenterol. 2007;102(5):997-1004.

50. Jin DX et al. Dig Dis Sci. 2017;62(10):2894-9.

51. Freeman ML. Gastrointest Endosc Clin N Am. 2012;22(3):567-86.

52. De Lisi S et al. Eur J Gastroenterol Hepatol. 2011;23(5):367-74.

53. Di MY et al. Ann Int Med. 2016;165(7):482-90.

54. Mounzer R et al. Gastroenterology. 2012;142(7):1476-82; quiz e15-6.

55. Koutroumpakis E et al. Am J Gastroenterol. 2015;110(12):1707-16.

56. Wu BU et al. Gastroenterology. 2009;137(1):129-35.

57. Buddingh KT et al. J Am Coll Surg. 2014;218(1):26-32.

58. Buxbaum J et al. Am J Gastroenterol. 2018;113(5):755-64.

59. Jabaudon M et al. Crit Car Med. 2018;46(3):e198-e205.

60. Barlass U et al. Gut. 2018;67(4):600-2.

61. Buxbaum JL et al. Am J Gastroenterol. 2017;112(5):797-803.

62. de-Madaria E et al. United Eur Gastroenterol J. 2018;6(1):63-72.

63. Bakker OJ et al. N Engl J Med. 2014;371(21):1983-93.

64. Tse F et al. Cochrane Database Syst Rev. 2012(5):Cd009779.

65. Kaner EFS et al. Cochrane Database Syst Rev. 2007(2):Cd004148.

66. da Costa DW et al. Lancet. 2015;386(10000):1261-8.

67. Schepers NJ et al. Trials. 2016;17:5.

68. Vadala di Prampero SF et al. Eur J Gastroenterol Hepatol. 2016;28(12):1415-24.

69. Kubiliun NM et al. Clin Gastroenterol Hepatol. 2015;13(7):1231-9; quiz e70-1.

70. Wan J et al. BMC Gastroenterol. 2017;17(1):43.

71. Yang C et al. Pancreatology. 2017;17(5):681-8.

72. DiMagno MJ et al. Pancreas. 2014;43(4):642-7.

73. Sagi SV et al. J Gastroenterol Hepatol. 2014;29(6):1316-20.

74. Choi JH et al. Clin Gastroenterol Hepatol. 2017;15(1):86-92.e1.

75. Wu D et al. J Clin Gastroenterol. 2017;51(8):e68-e76.

76. Zhang ZF et al. J Clin Gastroenterol. 2017;51(3):e17-e26.

77. Park CH et al. Endoscopy 2018 Apr;50(4):378-85.

78. Mok SRS et al. Gastrointest Endosc. 2017;85(5):1005-13.

79. Smeets XJN et al. Trials. 2018;19(1):207.

80. Elmunzer BJ et al. Trials. 2016;17(1):120.

 

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