Pan-cancer molecular signatures connecting aspartate transaminase (AST) to cancer prognosis, metabolic and immune signatures.

Background: Serum aspartate transaminase (sAST) level is used routinely in conjunction with other clinical assays to assess liver health and disease. Increasing evidence suggests that sAST is associated with all-cause mortality and has prognostic value in several cancers, including gastrointestinal and urothelial cancers. Here, we undertake a systems approach to unravel molecular connections between AST and cancer prognosis, metabolism, and immune signatures at the transcriptomic and proteomic levels. Methods: We mined public gene expression data across multiple normal and cancerous tissues using the Genotype Tissue Expression (GTEX) resource and The Cancer Genome Atlas (TCGA) to assess the expression of genes encoding AST isoenzymes (GOT1 and GOT2) and their association with disease prognosis and immune infiltration signatures across multiple tumors. We examined the associations between AST and previously reported pan-cancer molecular subtypes characterized by distinct metabolic and immune signatures. We analyzed human protein-protein interaction networks for interactions between GOT1 and GOT2 with cancer-associated proteins. Using public databases and protein-protein interaction networks, we determined whether the subset of proteins that interact with AST (GOT1 and GOT2 interactomes) are enriched with proteins associated with specific diseases, miRNAs and transcription factors. Results: We show that AST transcript isoforms (GOT1 and GOT2) are expressed across a wide range of normal tissues. AST isoforms are upregulated in tumors of the breast, lung, uterus, and thymus relative to normal tissues but downregulated in tumors of the liver, colon, brain, kidney and skeletal sarcomas. At the proteomic level, we find that the expression of AST is associated with distinct pan-cancer molecular subtypes with an enrichment of specific metabolic and immune signatures. Based on human protein-protein interaction data, AST physically interacts with multiple proteins involved in tumor initiation, suppression, progression, and treatment. We find enrichments in the AST interactomes for proteins associated with liver and lung cancer and dermatologic diseases. At the regulatory level, the GOT1 interactome is enriched with the targets of cancer-associated miRNAs, specifically mir34a - a promising cancer therapeutic, while the GOT2 interactome is enriched with proteins that interact with cancer-associated transcription factors. Conclusions: Our findings suggest that perturbations in the levels of AST within specific tissues reflect pathophysiological changes beyond tissue damage and have implications for cancer metabolism, immune infiltration, prognosis, and treatment personalization.

Profiles of Web-based Portal Users with Inflammatory Bowel Disease.

BACKGROUND: Web-based portals can enhance communication between patients and providers to support IBD self-management and improve care. We aimed to identify portal use patterns of patients with inflammatory bowel disease (IBD) to inform future web portal-based interventions and portal design. METHODS: Patients with IBD receiving care at the University of Michigan between 2012 and 2021 were identified. Meta-data from electronic logs of each patient's most recent year of portal use were abstracted. Portal engagement was characterized in terms of intensity (ie, frequency of use); comprehensiveness (ie, number of portal functions used); and duration (ie, quarters per year of portal use). We used k-means clustering, a machine-learning technique, to identify groupings of portal users defined in terms of engagement features. RESULTS: We found 5605 patients with IBD who had accessed their portal account at least once. The average age was 41.2 years (SD 16.7), 3035 (54.2%) were female, and 2214 (39.5%) received immune-targeted therapies. We identified 3 patterns of portal engagement: (1) low intensity users (29.5%); (2) moderate intensity, comprehensive, and sustained users (63.3%); and (3) high intensity, comprehensive, sustained users (7.2%). Patients with more intense, comprehensive, and sustained use of the portal were older, female, with more comorbidities, and were more likely to receive immune-targeted therapies. CONCLUSION: Understanding distinct patterns of portal use can inform portal-based interventions and portal design. Patient portals may be particularly helpful in delivering assistance to those with comorbidities and those receiving immune-targeted therapies-many of whom demonstrate more intense, comprehensive, and sustained portal use.

Inflammatory bowel disease patients have varying patterns of web-based portal engagement that can be characterized into distinct groupings. Portals-based interventions may be particularly helpful for those with comorbidities or receiving immune-targeted therapies­many of whom demonstrate more intense, comprehensive, and sustained use.

Loneliness and Depressive Symptoms Are High Among Older Adults With Digestive Disease and Associated With Lower Perceived Health.

BACKGROUND & AIMS: Current approaches to managing digestive disease in older adults fail to consider the psychosocial factors contributing to a person's health. We aimed to compare the frequency of loneliness, depression, and social isolation in older adults with and without a digestive disease and to quantify their association with poor health. METHODS: We conducted an analysis of Health and Retirement Study data from 2008 to 2016, a nationally representative panel study of participants 50 years and older and their spouses. Bivariate analyses examined differences in loneliness, depression, and social isolation among patients with and without a digestive disease. We also examined the relationship between these factors and health. RESULTS: We identified 3979 (56.0%) respondents with and 3131 (44.0%) without a digestive disease. Overall, 60.4% and 55.6% of respondents with and without a digestive disease reported loneliness (P < .001), 12.7% and 7.5% reported severe depression (P < .001), and 8.9% and 8.7% reported social isolation (P = NS), respectively. After adjusting for covariates, those with a digestive disease were more likely to report poor or fair health than those without a digestive disease (odds ratio [OR], 1.25; 95% CI, 1.11-1.41). Among patients with a digestive disease, loneliness (OR, 1.43; 95% CI, 1.22-1.69) and moderate and severe depression (OR, 2.93; 95% CI, 2.48-3.47; and OR, 8.96; 95% CI, 6.91-11.63, respectively) were associated with greater odds of poor or fair health. CONCLUSIONS: Older adults with a digestive disease were more likely than those without a digestive disease to endorse loneliness and moderate to severe depression and these conditions are associated with poor or fair health. Gastroenterologists should feel empowered to screen patients for depression and loneliness symptoms and establish care pathways for mental health treatment.

Racial Disparity in Esophageal Squamous Cell Carcinoma Treatment and Survival in the United States.

INTRODUCTION: Esophageal squamous cell carcinoma (ESCC) has a higher incidence and prevalence than esophageal adenocarcinoma among Black individuals in the United States. Black individuals have lower ESCC survival. These racial disparities have not been thoroughly investigated. We examined the disparity in treatment and survival stratified by ESCC stage at diagnosis. METHODS: The Surveillance, Epidemiology, and End Results database was queried to identify patients with ESCC between 2000 and 2019. The identified cohort was divided into subgroups by race. Patient and cancer characteristics, treatment received, and survival rates were compared across the racial subgroups. RESULTS: A total of 23,768 patients with ESCC were identified. Compared with White individuals, Black individuals were younger and had more distant disease during diagnosis (distant disease: 26.7% vs 23.8%, P < 0.001). Black individuals had lower age-standardized 5-year survival for localized (survival % [95% confidence interval]: 19.3% [16-22.8] vs 27.6% [25.1-30.2]), regional (14.3% [12-16.7] vs 21.1% [19.6-22.7]), and distant (2.9% [1.9-4.1] vs 6.5% [5.5-7.5]) disease. Black individuals were less likely to receive chemotherapy (54.7% vs 57.5%, P = 0.001), radiation (58.5% vs 60.4%, P = 0.03), and surgery (11.4% vs 16.3%, P < 0.0001). DISCUSSION: Black individuals with ESCC have a lower survival rate than White individuals. This could be related to presenting at a later stage but also disparities in which treatments they receive even among individuals with the same stage of disease. To what extent these disparities in receipt of treatment is due to structural racism, social determinants of health, implicit bias, or patient preferences deserves further study.

Association between antenatal corticosteroid treatment and severe adverse events in pregnant women.

BACKGROUND: Antenatal corticosteroids are considered the standard of care for pregnant women at risk for preterm birth, but studies examining their potential risks are scarce. We aimed to estimate the associations of antenatal corticosteroids with three severe adverse events: sepsis, heart failure, and gastrointestinal bleeding, in pregnant women. METHODS: Of 2,157,321 pregnant women, 52,119 at 24 weeks 0/7 days to 36 weeks 6/7 days of gestation were included in this self-controlled case series study during the study period of 2009-2018. We estimated incidence rates of three severe adverse events: sepsis, heart failure, and gastrointestinal bleeding. Conditional Poisson regression was used to calculate incidence rate ratios (IRRs) for comparing incidence rates of the adverse events in each post-treatment period compared to those during the baseline period among pregnant women exposed to a single course of antenatal corticosteroid treatment. RESULTS: Among 52,119 eligible participants who received antenatal corticosteroid treatment, the estimated incidence rates per 1000 person-years were 0.76 (95% confidence interval (CI): 0.69-0.83) for sepsis, 0.31 (95% CI: 0.27-0.36) for heart failure, and 11.57 (95% CI: 11.27-11.87) for gastrointestinal bleeding. The IRRs at 5 ~ 60 days after administration of antenatal corticosteroids were 5.91 (95% CI: 3.10-11.30) for sepsis and 4.45 (95% CI: 2.63-7.55) for heart failure, and 1.26 (95% CI: 1.02-1.55) for gastrointestinal bleeding; and the IRRs for days 61 ~ 180 were 2.00 (95% CI: 1.01-3.96) for sepsis, 3.65 (95% CI: 2.14-6.22) for heart failure, and 1.81 (95% CI: 1.56-2.10) for gastrointestinal bleeding. CONCLUSIONS: This nationwide population-based study suggests that a single course of antenatal corticosteroids is significantly associated with a 1.3- to 5.9-fold increased risk of sepsis, heart failure, and gastrointestinal bleeding in pregnant women. Maternal health considerations, including recommendations for adverse event monitoring, should be included in future guidelines for antenatal corticosteroid treatment.

Promoting data harmonization to evaluate vaccine hesitancy in LMICs: approach and applications.

BACKGROUND: Factors influencing the health of populations are subjects of interdisciplinary study. However, datasets relevant to public health often lack interdisciplinary breath. It is difficult to combine data on health outcomes with datasets on potentially important contextual factors, like political violence or development, due to incompatible levels of geographic support; differing data formats and structures; differences in sampling procedures and wording; and the stability of temporal trends. We present a computational package to combine spatially misaligned datasets, and provide an illustrative analysis of multi-dimensional factors in health outcomes. METHODS: We rely on a new software toolkit, Sub-National Geospatial Data Archive (SUNGEO), to combine data across disciplinary domains and demonstrate a use case on vaccine hesitancy in Low and Middle-Income Countries (LMICs). We use data from the World Bank's High Frequency Phone Surveys (HFPS) from Kenya, Indonesia, and Malawi. We curate and combine these surveys with data on political violence, elections, economic development, and other contextual factors, using SUNGEO. We then develop a stochastic model to analyze the integrated data and evaluate 1) the stability of vaccination preferences in all three countries over time, and 2) the association between local contextual factors and vaccination preferences. RESULTS: In all three countries, vaccine-acceptance is more persistent than vaccine-hesitancy from round to round: the long-run probability of staying vaccine-acceptant (hesitant) was 0.96 (0.65) in Indonesia, 0.89 (0.21) in Kenya, and 0.76 (0.40) in Malawi. However, vaccine acceptance was significantly less durable in areas exposed to political violence, with percentage point differences (ppd) in vaccine acceptance of -10 (Indonesia), -5 (Kenya), and -64 (Malawi). In Indonesia and Kenya, although not Malawi, vaccine acceptance was also significantly less durable in locations without competitive elections (-19 and -6 ppd, respectively) and in locations with more limited transportation infrastructure (-11 and -8 ppd). CONCLUSION: With SUNGEO, researchers can combine spatially misaligned and incompatible datasets. As an illustrative example, we find that vaccination hesitancy is correlated with political violence, electoral uncompetitiveness and limited access to public goods, consistent with past results that vaccination hesitancy is associated with government distrust.

Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model.

OBJECTIVE: This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya. APPROACH: The study will deploy a mobile application (app) platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya. EXPECTATION: This study will lay the basis for creating agile and scalable systems for rapid diagnostics that could inform precise interventions for mitigating depression and ensure a healthy, resilient healthcare workforce to develop sustainable economic growth in Kenya, East Africa, and ultimately neighboring countries in sub-Saharan Africa. This protocol paper provides an opportunity to share the planned study implementation methods and approaches. CONCLUSION: A mobile technology platform that is scalable and can be used to understand and improve mental health outcomes is of critical importance.

Prevalence and prescribing patterns of oral corticosteroids in the United States, Taiwan, and Denmark, 2009-2018.

Oral corticosteroids (OCS) are commonly prescribed for acute, self-limited conditions, despite studies demonstrating toxicity. Studies evaluating longitudinal OCS prescribing in the general population are scarce and do not compare use across countries. This study investigated and compared OCS prescription patterns from 2009 to 2018 in the general populations of the United States, Taiwan, and Denmark. This international population-based longitudinal cohort study used nationwide claims databases (United States: Optum Clinformatics Data Mart; de-identified; Taiwan: National Health Insurance Research Database; and Denmark: National Prescription and Patient Registries/Danish National Patient Registry) to evaluate OCS prescribing. We classified annual OCS duration as short-term (1-29 days), medium-term (30-89 days), or long-term (≥90 days). Longitudinal change in annual prevalence of OCS use and physician prescribing patterns were reported. Among 54,630,437 participants, average annual percentage of overall OCS use was 6.8% in the United States, 17.5% in Taiwan, and 2.2% in Denmark during 2009-2018. Prevalence of OCS prescribing increased at an average annual rate of 0.1%-0.17%, mainly driven by short-term prescribing to healthy adults. One-quarter to one-fifth of OCS prescribing was associated with a diagnosis of respiratory infection. Family practice and internal medicine physicians were among the highest OCS prescribers across countries and durations. Age- and sex-stratified trends mirrored unstratified trends. This study provides real-world evidence of an ongoing steady increase in OCS use in the general populations of the United States, Taiwan, and Denmark. This increase is largely driven by short-term OCS prescribing to healthy adults, a practice previously viewed as safe but recently shown to incur substantial population-level risk.

Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records.

BACKGROUND & AIMS: Tools that can automatically predict incident esophageal adenocarcinoma (EAC) and gastric cardia adenocarcinoma (GCA) using electronic health records to guide screening decisions are needed. METHODS: The Veterans Health Administration (VHA) Corporate Data Warehouse was accessed to identify Veterans with 1 or more encounters between 2005 and 2018. Patients diagnosed with EAC (n = 8430) or GCA (n = 2965) were identified in the VHA Central Cancer Registry and compared with 10,256,887 controls. Predictors included demographic characteristics, prescriptions, laboratory results, and diagnoses between 1 and 5 years before the index date. The Kettles Esophageal and Cardia Adenocarcinoma predictioN (K-ECAN) tool was developed and internally validated using simple random sampling imputation and extreme gradient boosting, a machine learning method. Training was performed in 50% of the data, preliminary validation in 25% of the data, and final testing in 25% of the data. RESULTS: K-ECAN was well-calibrated and had better discrimination (area under the receiver operating characteristic curve [AuROC], 0.77) than previously validated models, such as the Nord-Trøndelag Health Study (AuROC, 0.68) and Kunzmann model (AuROC, 0.64), or published guidelines. Using only data from between 3 and 5 years before index diminished its accuracy slightly (AuROC, 0.75). Undersampling men to simulate a non-VHA population, AUCs of the Nord-Trøndelag Health Study and Kunzmann model improved, but K-ECAN was still the most accurate (AuROC, 0.85). Although gastroesophageal reflux disease was strongly associated with EAC, it contributed only a small proportion of gain in information for prediction. CONCLUSIONS: K-ECAN is a novel, internally validated tool predicting incident EAC and GCA using electronic health records data. Further work is needed to validate K-ECAN outside VHA and to assess how best to implement it within electronic health records.

Coronavirus pandemic in the South Asia region: Health policy and economy trade-off.

Background: The South Asian Association for Regional Cooperation (SAARC) covers Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. We conducted a comparative analysis of the trade-off between the health policies for the prevention of COVID-19 spread and the impact of these policies on the economies and livelihoods of the South Asia populations. Methods: We analyzed COVID-19 data on epidemiology, public health and health policy, health system capacity, and macroeconomic indicators from January 2020 to March 2021 to determine temporal trends by conducting joinpoint regression analysis using average weekly percent change (AWPC). Results: Bangladesh had the highest statistically significant AWPC for new COVID-19 cases (17.0; 95% CI = 7.7-27.1, P < 0.001), followed by the Maldives (12.9; 95% CI = 5.3-21.0, P < 0.001) and India (10.0; 95% CI = 8.4-11.5, P < 0.001). The AWPC for COVID-19 deaths was significant for India (6.5; 95% CI = 4.3-8.9, P < 0.001) and Bangladesh (6.1; 95% CI = 3.7-8.5, P < 0.001). Nepal (55.79%), and India (34.91%) had the second- and third-highest increase in unemployment, while Afghanistan (6.83%) and Pakistan (16.83%) had the lowest. The rate of change of real GDP had the highest decrease for Maldives (557.51%), and India (297.03%); Pakistan (46.46%) and Bangladesh (70.80%), however, had the lowest decrease. The government response stringency index for Pakistan had a see-saw pattern with a sharp decline followed by an increase in the government health policy restrictions that approximated the test-positivity trend. Conclusions: Unlike developed economies, the South Asian developing countries experienced a trade-off between health policy and their economies during the COVID-19 pandemic. South Asian countries (Nepal and India), with extended periods of lockdowns and a mismatch between temporal trends of government response stringency index and the test-positivity or disease incidence, had higher adverse economic effects, unemployment, and burden of COVID-19. Pakistan demonstrated targeted lockdowns with a rapid see-saw pattern of government health policy response that approximated the test-positivity trend and resulted in lesser adverse economic effects, unemployment, and burden of COVID-19.

Characteristics of Facilities With Early and Rapid Ustekinumab Adoption for Patients With Inflammatory Bowel Disease.

INTRODUCTION: To examine which facility characteristics, including teamwork, are associated with early or rapid inflammatory bowel disease-related ustekinumab adoption. METHODS: We examined the association between ustekinumab adoption and the characteristics of 130 Veterans Affairs facilities. RESULTS: Mean ustekinumab adoption increased by 3.9% from 2016 to 2018 and was higher in urban compared with rural facilities (ß = 0.03, P = 0.033) and among facilities with more teamwork (ß = 0.11, P = 0.041). Compared with nonearly adopters, early adopters were more likely be high-volume facilities (46% vs 19%, P = 0.001). DISCUSSION: Facility variation in medication adoption provides an opportunity for improving inflammatory bowel disease care through targeted dissemination strategies to improve medication uptake.

Interventions Increase Vaccination Rates in Inflammatory Bowel Disease and Rheumatoid Arthritis: A Systematic Review and Meta-Analysis.

BACKGROUND: Patients with immune-mediated conditions such as IBD and RA are at risk for vaccine-preventable infections. Despite guideline recommendations, prior studies have shown suboptimal vaccination rates. AIM: We conducted a systematic review and meta-analysis to compare the different interventions intended to increase vaccination rates. METHODS: A systematic search was conducted of MEDLINE/PubMed, Embase, CINAHL, and Cochrane Library up to 2020 for studies with interventions intended to increase vaccination rates. We performed a random-effects meta-analysis to generate pooled odds ratios (ORs) to assess all interventions against no interventions. Our primary outcome was pneumococcal vaccination (PCV) rate. RESULTS: Our review found 8580 articles, for which 15 IBD and 8 RA articles met the inclusion criteria; 21 articles were included in the analysis. PCV was the predominant vaccination (91%). In our analysis of patients with IBD, almost all interventions (patient-oriented, physician-oriented, or barrier-oriented) increased PCV uptake [OR, 4.74; 95% CI, 2.44-6.56, I2 = 90%] compared to no intervention. The greatest effect was seen in barrier-oriented studies [OR, 12.68; 95% CI, 2.21-72.62, I2 = 92%]. For RA data, all interventions had increased PCV uptake compared to no interventions (OR 2.74; 95% CI, 1.80-4.17, I2 = 95%). CONCLUSION: Our data suggest that many different interventions can increase PCV rates. It appears that barrier-oriented interventions may have the greatest positive effect on increasing PCV uptake. However, clinicians should be encouraged to implement measures best suited to their practice. Future high-quality randomized controlled trials are needed to determine the best approach to optimize vaccination rates.

Self-Efficacy and the Impact of Inflammatory Bowel Disease on Patients' Daily Lives.

INTRODUCTION: Self-efficacy, i.e., the confidence in one's capacity to perform a behavior, is crucial to the development of inflammatory bowel disease (IBD) self-management skills. We aimed to measure IBD self-efficacy and the relationship between self-efficacy and the patient-reported impact of IBD on daily life. METHODS: We surveyed patients with IBD from a single academic center using the IBD Self-Efficacy Scale (IBD-SES) and patient-reported outcome (PRO) measures. The IBD-SES assesses 4 IBD domains: patients' confidence in managing stress and emotions, symptoms and disease, medical care, and remission. IBD PROs evaluate daily life impact, coping strategies, emotional impact, and systemic symptoms. We examined the association between IBD-SES domains with the lowest scores and IBD daily life impact. RESULTS: A total of 160 patients completed the survey. Domain scores on the IBD-SES were lowest for managing stress and emotions (mean 6.76, SD 1.86) and symptoms and disease (mean 6.71, SD 2.12) on a 1-10 scale. Controlling for age, sex, IBD type, disease activity, moderate-to-severe disease, depression and anxiety, a higher confidence in managing stress and emotions (ß -0.12, 95% confidence interval -0.20 to -0.05, P = 0.001), and managing symptoms and disease (ß -0.28, 95% confidence interval -0.35 to -0.20, P < 0.001) were each associated with lower IBD daily life impact. DISCUSSION: Patients with IBD report low confidence in managing stress and emotion and managing symptoms and disease. Higher self-efficacy in these domains was associated with lower IBD daily life impact. Self-management tools that promote self-efficacy in managing these domains have the potential to reduce IBD's daily life impact.

Prediction of Gastrointestinal Tract Cancers Using Longitudinal Electronic Health Record Data.

BACKGROUND: Luminal gastrointestinal (GI) tract cancers, including esophageal, gastric, small bowel, colorectal, and anal cancers, are often diagnosed at late stages. These tumors can cause gradual GI bleeding, which may be unrecognized but detectable by subtle laboratory changes. Our aim was to develop models to predict luminal GI tract cancers using laboratory studies and patient characteristics using logistic regression and random forest machine learning methods. METHODS: The study was a single-center, retrospective cohort at an academic medical center, with enrollment between 2004-2013 and with follow-up until 2018, who had at least two complete blood counts (CBCs). The primary outcome was the diagnosis of GI tract cancer. Prediction models were developed using multivariable single timepoint logistic regression, longitudinal logistic regression, and random forest machine learning. RESULTS: The cohort included 148,158 individuals, with 1025 GI tract cancers. For 3-year prediction of GI tract cancers, the longitudinal random forest model performed the best, with an area under the receiver operator curve (AuROC) of 0.750 (95% CI 0.729-0.771) and Brier score of 0.116, compared to the longitudinal logistic regression model, with an AuROC of 0.735 (95% CI 0.713-0.757) and Brier score of 0.205. CONCLUSIONS: Prediction models incorporating longitudinal features of the CBC outperformed the single timepoint logistic regression models at 3-years, with a trend toward improved accuracy of prediction using a random forest machine learning model compared to a longitudinal logistic regression model.

Distinct health care use patterns of patients with chronic gastrointestinal diseases.

OBJECTIVES: Patients with complex chronic conditions have varying multidisciplinary care needs and utilization patterns, which limit the effectiveness of initiatives designed to improve continuity of care (COC) and reduce utilization. Our objective was to categorize patients with complex chronic conditions into distinct groups by pattern of outpatient care use and COC to tailor interventions. STUDY DESIGN: Observational cohort study from 2014 to 2015. METHODS: We identified patients whose 1-year hospitalization risk was in at least the 90th percentile in 2014 who had a chronic gastrointestinal disease (cirrhosis, inflammatory bowel disease, chronic pancreatitis) as case examples of complex chronic disease. We described frequency of office visits, number of outpatient providers, and 2 COC measures (usual provider of care, Bice-Boxerman COC indices) over 12 months. We used latent profile analysis, a statistical method for identifying distinct subgroups, to categorize patients based on overall, primary care, gastroenterology, and mental health continuity patterns. RESULTS: The 26,751 veterans in the cohort had a mean (SD) of 13.3 (8.6) office visits and 7.2 (3.8) providers in 2014. Patients were classified into 5 subgroups: (1) high gastroenterology-specific COC with mental health use; (2) high gastroenterology-specific COC without mental health use; (3) high overall utilization with mental health use; (4) low overall COC with mental health use; and (5) low overall COC without mental health use. These groups varied in their sociodemographic characteristics and risk for hospitalization, emergency department use, and mortality. CONCLUSIONS: Patients at high risk for health care utilization with specialty care needs can be grouped by varying propensity for health care continuity patterns.