Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes.

BACKGROUND: Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes. OBJECTIVE: Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes. DESIGN, PARTICIPANTS, MEASURES: In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities. RESULTS: Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52). CONCLUSIONS: Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

Privacy-preserving analytic methods for multisite comparative effectiveness and patient-centered outcomes research.

BACKGROUND: For privacy and practical reasons, it is sometimes necessary to minimize sharing of individual-level information in multisite studies. However, individual-level information is often needed to perform more rigorous statistical analysis. OBJECTIVES: To compare empirically 3 analytic methods for multisite studies that only require sharing of summary-level information to perform statistical analysis that have traditionally required access to detailed individual-level data from each site. RESEARCH DESIGN, SUBJECTS, AND MEASURES: We analyzed data from a 7-site study of bariatric surgery outcomes within the Scalable Partnering Network. We compared the long-term risk of rehospitalization between adjustable gastric banding and Roux-en-y gastric bypass procedures using a stratified analysis of propensity score (PS)-defined strata, a case-centered analysis of risk set data, and a meta-analysis of site-specific effect estimates. Their results were compared with the result from a pooled individual-level data analysis. RESULTS: The study included 1327 events (18.1%) among 7342 patients. The adjusted hazard ratio was 0.71 (95% CI, 0.59, 0.84) comparing adjustable gastric banding with Roux-en-y gastric bypass in the individual-level data analysis. The corresponding effect estimate was 0.70 (0.59, 0.83) in the PS-stratified analysis, 0.71 (0.59, 0.84) in the case-centered analysis, and 0.71 (0.60, 0.84) in both the fixed-effect and random-effects meta-analysis. CONCLUSIONS: In this empirical study, PS-stratified analysis, case-centered analysis, and meta-analysis produced results that are identical or highly comparable with the result from a pooled individual-level data analysis. These methods have the potential to be viable analytic alternatives when sharing of individual-level information is not feasible or not preferred in multisite studies.

Evaluating the Safety of an Educational Deprescribing Intervention: Lessons from the Optimize Trial.

BACKGROUND: Patients, family members, and clinicians express concerns about potential adverse drug withdrawal events (ADWEs) following medication discontinuation or fears of upsetting a stable medical equilibrium as key barriers to deprescribing. Currently, there are limited methods to pragmatically assess the safety of deprescribing and ascertain ADWEs. We report the methods and results of safety monitoring for the OPTIMIZE trial of deprescribing education for patients, family members, and clinicians. METHODS: This was a pragmatic cluster randomized trial with multivariable Poisson regression comparing outcome rates between study arms. We conducted clinical record review and adjudication of sampled records to assess potential causal relationships between medication discontinuation and outcomes. This study included adults aged 65+ with dementia or mild cognitive impairment, one or more additional chronic conditions, and prescribed 5+ chronic medications. The intervention included an educational brochure on deprescribing that was mailed to patients prior to primary care visits, a clinician notification about individual brochure mailings, and an educational tip sheets was provided monthly to primary care clinicians. The outcomes of the safety monitoring were rates of hospitalizations and mortality during the 4 months following brochure mailings and results of record review and adjudication. The adjudication process was conducted throughout the trial and included classifications: likely, possibly, and unlikely. RESULTS: There was a total of 3012 (1433 intervention and 1579 control) participants. There were 420 total hospitalizations involving 269 (18.8%) people in the intervention versus 517 total hospitalizations involving 317 (20.1%) people in the control groups. Adjusted risk ratios comparing intervention to control groups were 0.92 [95% confidence interval (CI) 0.72, 1.16] for hospitalization and 1.19 (95% CI 0.67, 2.11) for mortality. Both groups had zero deaths "likely" attributed to a medication change prior to the event. A total of 3 out of 30 (10%) intervention group hospitalizations and 7 out of 35 (20%) control group hospitalizations were considered "likely" due to a medication change. CONCLUSIONS: Population-based deprescribing education is safe in the older adult population with cognitive impairment in our study. Pragmatic methods for safety monitoring are needed to further inform deprescribing interventions. TRIAL REGISTRATION: NCT03984396. Registered on 13 June 2019.

Variation in Colorectal Cancer Stage and Mortality across Large Community-Based Populations: PORTAL Colorectal Cancer Cohort.

INTRODUCTION: Colorectal cancer (CRC) incidence and mortality can be reduced by effective screening and/or treatment. However, the influence of health care systems on disparities among insured patients is largely unexplored. METHODS: To evaluate insured patients with CRC diagnosed between 2010 and 2014 across 6 diverse US health care systems in the Patient-Centered Outcomes Research Institute (PCORI) Patient Outcomes Research To Advance Learning (PORTAL) CRC cohort, we contrasted CRC stage; CRC mortality; all-cause mortality; and influences of demographics, stage, comorbidities, and treatment between health systems. RESULTS: Among 16,211 patients with CRC, there were significant differences between health care systems in CRC stage at diagnosis, CRC-specific mortality, and all-cause mortality. The unadjusted risk of CRC mortality varied from 27% lower to 21% higher than the reference system (hazard ratio [HR] = 0.73, 95% confidence interval = 0.66-0.80 to HR = 1.21, 95% confidence interval = 1.05-1.40; p < 0.01 across systems). Significant differences persisted after adjustment for demographics and comorbidities (p < 0.01); however, adjustment for stage eliminated significant differences (p = 0.24). All-cause mortality among patients with CRC differed approximately 30% between health care systems (HR = 0.89-1.17; p < 0.01). Adjustment for age eliminated significant differences (p = 0.48). DISCUSSION: Differences in CRC survival between health care systems were largely explained by stage at diagnosis, not demographics, comorbidity, or treatment. Given that stage is strongly related to early detection, these results suggest that variation in CRC screening systems represents a modifiable systems-level factor for reducing disparities in CRC survival.

Melanoma incidence, recurrence, and mortality in an integrated healthcare system: A retrospective cohort study.

BACKGROUND: Numerous studies have examined melanoma incidence and survival, but studies on melanoma recurrence are limited. We examined melanoma incidence, recurrence, and mortality among members of Kaiser Permanente Colorado (KPCO) between January 1, 2000 and December 31, 2015. METHODS: Age-adjusted incidence rates were computed to examine trends among KPCO members aged 21 years and older. Cox proportional hazards models were used to examine factors associated with recurrence and mortality. RESULTS: Our cohort included 1931 cases of invasive melanoma. Incidence rates increased over time and were higher than SEER rates; however, the increase was limited to early stage disease. In multivariable models, stage at initial diagnosis, gender, and age were associated with melanoma recurrence. Men were more likely to have a recurrence than women (adjusted hazard ratio [HR]: 1.70, 95% confidence interval [CI]: 1.19-2.43), and for each decade of increasing age, the adjusted HR = 1.20 (95% CI: 1.06-1.37). Factors associated with all-cause mortality included stage (HR = 12.87, 95% CI: 6.63-24.99, for stage IV vs stage I), male gender (HR = 1.42, 95% CI: 1.12-1.79), older age at diagnosis, lower socioeconomic status, and comorbidity index. For melanoma-specific mortality, results were similar, with one exception: age was not associated with melanoma-specific death (HR = 1.09, 95% CI: 0.94-1.25, P = 0.253). CONCLUSIONS: Data derived from an insured patient population, such as KPCO, have the potential to enhance our understanding of emerging trends in melanoma. This is the first population-based study in the United States to examine patient characteristics associated with risk of recurrence. Men have an increased risk of both recurrence and death, and thus may benefit from more intensive follow-up than women.