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Abstract Background Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. Methods We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. Results Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). Conclusions In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

OBJECTIVE Diabetes that arises from chronic pancreatitis (CP) is associated with increased morbidity and mortality. Methods to predict which patients with CP are at greatest risk for diabetes are urgently needed. We aimed to examine independent risk factors for diabetes in a large cohort of patients with CP. RESEARCH DESIGN AND METHODS This cross-sectional study comprised 645 individuals with CP enrolled in the PROCEED study, of whom 276 had diabetes. We conducted univariable and multivariable regression analyses of potential risk factors for diabetes. Model performance was assessed by area under the receiver operating characteristic curve (AUROC) analysis, and accuracy was evaluated by cross validation. Exploratory analyses were stratified according to the timing of development of diabetes relative to the diagnosis of pancreatitis. RESULTS Independent correlates of diabetes in CP included risk factors for type 2 diabetes (older age, overweight/obese status, male sex, non-White race, tobacco use) as well as pancreatic disease–related factors (history of acute pancreatitis complications, nonalcoholic etiology of CP, exocrine pancreatic dysfunction, pancreatic calcification, pancreatic atrophy) (AUROC 0.745). Type 2 diabetes risk factors were predominant for diabetes occurring before pancreatitis, and pancreatic disease–related factors were predominant for diabetes occurring after pancreatitis. CONCLUSIONS Multiple factors are associated with diabetes in CP, including canonical risk factors for type 2 diabetes and features associated with pancreatitis severity. This study lays the groundwork for the future development of models integrating clinical and nonclinical data to identify patients with CP at risk for diabetes and identifies modifiable risk factors (obesity, smoking) on which to focus for diabetes prevention.

Abstract BACKGROUND Participation in mentorship programs for early career physicians is crucial to developing key skills and professional networks, but availability and opportunities for mentorship may be hampered by racial, ethnic and gender leadership disparities in medicine. A 6-month virtually facilitated peer mentorship program for women and diverse early career faculty was developed and piloted through the Society for Neuro-Oncology (SNO) Women & Diversity Committee. METHODS We designed and conducted a 6-month pilot open to SNO’s multidisciplinary early career members, leveraging peer-mentoring sessions with mid-to late-career physician mentors. A curriculum with online resources was provided and group assignments were based on time-zones and interests. Pre- and post-participation surveys assessed mentee experience and descriptive statistics assessed participant demographics and survey results. Results/ CONCLUSION Twenty mentee applicants participated in 5 groups. Mentees were 90% women, 60% from diverse racial and ethnic backgrounds. Most were aged 31-40 (75%) and junior faculty (50%) in neuro-oncology (65%). Five mentors (2 female) practiced either neuro-oncology (3), neurosurgery (1) or radiation oncology (1). The proportion of mentees with a signature talk increased from 15% to 71% during the pilot. A large majority (64%) reported a positive impact of the program on their profile, career and networking, and reported participation was worthwhile (86%), and worth recommending to others (93%). Feedback themes included personal growth, peer support, networking, job opportunities, desire for late career female mentors, and scheduling constraints. The virtual environment during a global pandemic allowed participants to connect, creating a venue to discuss topics such as work-life balance, burnout, and self-advocacy. We did not have 100% post pilot follow up despite multiple attempts, limiting complete understanding of the pilot. This virtual mentorship pilot program proved feasible and of value in development of early career women and diverse individuals. A resource toolkit has been designed to scale and diffuse.

AbstractObjectiveHigh BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome‐ and phenome‐wide approach.MethodsThis study performed a phenome‐wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.ResultsClass 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome‐wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.ConclusionsThis combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

ImportanceCytokine storm due to COVID-19 can cause high morbidity and mortality and may be more common in patients with cancer treated with immunotherapy (IO) due to immune system activation.ObjectiveTo determine the association of baseline immunosuppression and/or IO-based therapies with COVID-19 severity and cytokine storm in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included 12 046 patients reported to the COVID-19 and Cancer Consortium (CCC19) registry from March 2020 to May 2022. The CCC19 registry is a centralized international multi-institutional registry of patients with COVID-19 with a current or past diagnosis of cancer. Records analyzed included patients with active or previous cancer who had a laboratory-confirmed infection with SARS-CoV-2 by polymerase chain reaction and/or serologic findings.ExposuresImmunosuppression due to therapy; systemic anticancer therapy (IO or non-IO).Main Outcomes and MeasuresThe primary outcome was a 5-level ordinal scale of COVID-19 severity: no complications; hospitalized without requiring oxygen; hospitalized and required oxygen; intensive care unit admission and/or mechanical ventilation; death. The secondary outcome was the occurrence of cytokine storm.ResultsThe median age of the entire cohort was 65 years (interquartile range [IQR], 54-74) years and 6359 patients were female (52.8%) and 6598 (54.8%) were non-Hispanic White. A total of 599 (5.0%) patients received IO, whereas 4327 (35.9%) received non-IO systemic anticancer therapies, and 7120 (59.1%) did not receive any antineoplastic regimen within 3 months prior to COVID-19 diagnosis. Although no difference in COVID-19 severity and cytokine storm was found in the IO group compared with the untreated group in the total cohort (adjusted odds ratio [aOR], 0.80; 95% CI, 0.56-1.13, and aOR, 0.89; 95% CI, 0.41-1.93, respectively), patients with baseline immunosuppression treated with IO (vs untreated) had worse COVID-19 severity and cytokine storm (aOR, 3.33; 95% CI, 1.38-8.01, and aOR, 4.41; 95% CI, 1.71-11.38, respectively). Patients with immunosuppression receiving non-IO therapies (vs untreated) also had worse COVID-19 severity (aOR, 1.79; 95% CI, 1.36-2.35) and cytokine storm (aOR, 2.32; 95% CI, 1.42-3.79).Conclusions and RelevanceThis cohort study found that in patients with cancer and COVID-19, administration of systemic anticancer therapies, especially IO, in the context of baseline immunosuppression was associated with severe clinical outcomes and the development of cytokine storm.Trial RegistrationClinicalTrials.gov Identifier: NCT04354701

PURPOSE In patients with high-grade ovarian cancer, predictors of bevacizumab efficacy in first-line setting are needed. In the ICON-7 trial, a poor tumor intrinsic chemosensitivity (defined by unfavorable modeled cancer antigen-125 [CA-125] ELIMination rate constant K [KELIM] score) was a predictive biomarker. Only the patients with high-risk disease (suboptimally resected stage III, or stage IV) exhibiting unfavorable KELIM score < 1.0 had overall survival (OS) benefit from bevacizumab (median: 29.7 v 20.6 months; hazard ratio [HR], 0.78). An external validation study in the GOG-0218 trial was performed. METHODS In GOG-0218, 1,873 patients were treated with carboplatin-paclitaxel ± concurrent-maintenance bevacizumab/placebo. Patient KELIM values were calculated with CA-125 kinetics during the first 100 chemotherapy days by the Lyon University team. The association between KELIM score (favorable ≥ 1.0, or unfavorable < 1.0) and bevacizumab benefit for progression-free survival (PFS)/OS was independently assessed by NGR-GOG using univariate/multivariate analyses. RESULTS KELIM was assessable in 1,662 patients with ≥ 3 CA-125 available values. An unfavorable KELIM score was associated with bevacizumab benefit compared with placebo (PFS: HR, 0.70; 95% CI, 0.59 to 0.82; OS: HR, 0.87; 95% CI, 0.73 to 1.03), whereas a favorable KELIM was not (PFS: HR, 0.96; 95% CI, 0.79 to 1.17; OS: HR, 1.11; 95% CI, 0.89 to 1.39). The highest benefit was observed in patients with a high-risk disease exhibiting unfavorable KELIM, for PFS (median: 9.1 v 5.6 months; HR, 0.64; 95% CI, 0.53 to 0.78), and for OS (median: 35.1 v 29.1 months; HR, 0.79; 95% CI, 0.65 to 0.97). CONCLUSION This GOG-0218 trial investigation validates ICON-7 findings about the association between poor tumor chemosensitivity and benefit from concurrent-maintenance bevacizumab, suggesting that bevacizumab may mainly be effective in patients with poorly chemosensitive disease. Bevacizumab may be prioritized in patients with a high-risk and poorly chemosensitive disease to improve their PFS/OS (patient KELIM score calculator available on the Biomarker Kinetics website).

27 Background: In the US, two million people are referred to urologists for the evaluation of microscopic hematuria (MH). MH guidelines were revised in 2020 by the American Urological Association, recommending that only patients at high risk for malignancy based on age, smoking history, or urinalysis receive computed tomography (CT) imaging. We found in previous studies that providers continued to use CT for patients with low-to-intermediate risk, representing low-value care. To understand reasons for continued CT use for patients with low-to-intermediate risk MH, we assessed determinants of low-value care in a concurrent mixed-method study. Methods: We stratified patients with a urology consultation within 180 days of a urinalysis documented in one academic medical center’s electronic health record between 1/1/15 and 7/1/21 into high-, intermediate-, and low-risk categories and validated risk designation in a chart review of a 5% subsample. We defined low-value care as CT for patients with low-to-intermediate-risk MH. To assess determinants of low-value MH care, we conducted semi-structured interviews with primary, urology, and gynecology providers (n = 7) identified through our professional networks. Results: Six hundred nineteen patients were referred to urology for MH. 58.6% were high-risk, 33.6% intermediate-risk, 4.4% low-risk, and 3.4% were undefined. 15.9% of intermediate-risk (n = 33) and 11.1% of low-risk (n = 3) patients received CT. Of the 14 patients referred to urology post-guideline change, none with low-to-intermediate-risk received CT. Interviews demonstrated substantial variation in approaches to MH evaluation. Urologists were largely aware of the revised guideline but noted inappropriate evaluation before referral, unnecessary referrals, and inefficiency in evaluation following referral. Lacking accessible data for risk stratification, other providers’ approaches were varied but driven by a common goal of ruling out renal malignancy, based on medical school training and institutional norms. Conclusions: Low-value care was limited but persistent and may be driven by a lack of resources to support risk-stratified MH evaluation, including accessible risk stratification data and clear guidelines for appropriate evaluation. This is consistent with a lack of practical guidance for implementing MH evaluation guidelines. In future studies, we will develop strategies to facilitate risk-stratified MH evaluation in practice.

AbstractIntroductionCOVID‐19 has created additional challenges for the analysis of non‐randomized interventions in health system settings. Our objective is to evaluate these challenges and identify lessons learned from the analysis of a medically tailored meals (MTM) intervention at Kaiser Permanente Northwest (KPNW) that began in April 2020.MethodsWe identified both a historical and concurrent comparison group. The historical comparison group included patients living in the same area as the MTM recipients prior to COVID‐19. The concurrent comparison group included patients admitted to contracted non‐KPNW hospitals or admitted to a KPNW facility and living outside the service area for the intervention but otherwise eligible. We used two alternative propensity score methods in response to the loss of sample size with exact matching to evaluate the intervention.ResultsWe identified 452 patients who received the intervention, 3873 patients in the historical comparison group, and 5333 in the concurrent comparison group. We were able to mostly achieve balance on observable characteristics for the intervention and the two comparison groups.ConclusionsLessons learned included: (a) The use of two different comparison groups helped to triangulate results; (b) the meaning of utilization measures changed pre‐ and post‐COVID‐19; and (c) that balance on observable characteristics can be achieved, especially when the comparison groups are meaningfully larger than the intervention group. These findings may inform the design for future evaluations of interventions during COVID‐19.