{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T05:24:22Z","timestamp":1788585862449,"version":"build-2803163510"},"reference-count":25,"publisher":"American Medical Association (AMA)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Metformin is often used as a first-line therapy for type 2 diabetes; however, frequent discontinuation with reduced kidney function and increased disease severity indicates that a comparison with any other group (eg, nonusers or insulin users) must address significant residual confounding concerns.<\/jats:p>\n <\/jats:sec>\n \n Objectives<\/jats:title>\n To examine the potential for residual confounding in a commonly used observational study design applied to metformin and to propose a more robust study design for future observational studies of metformin.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This retrospective cohort study with a prevalent user design was conducted using an administrative claims database for Medicare Advantage beneficiaries in the US. Participants were categorized into 2 distinct cohorts: 404\u202f458 individuals with type 2 diabetes and 81\u202f791 individuals with prediabetes. Clinical history was observed in 2018, and end points were observed in 2019. Statistical analyses were conducted between May and December 2021.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Prevalent use (recent prescription and history of use on at least 90 of the preceding 365 days) of metformin or insulin but not both at the start of the observation period.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Total inpatient admission days in 2019 and total medical spending (excluding prescription drugs) in 2019. Each of these measures was treated as a binary outcome (0 vs &amp;gt;0 inpatient days and top 10% vs bottom 90% of medical spending).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The study included 404\u202f458 adults with type 2 diabetes (mean [SD] age, 74.5 [7.5] years; 52.7% female). A strong metformin effect estimate was associated with reduced inpatient admissions (odds ratio, 0.60; 95% CI, 0.58-0.62) and reduced medical expenditures (odds ratio, 0.57; 95% CI, 0.55-0.60). However, implementation of additional robust design features (negative control outcomes and a complementary cohort) revealed that the estimated beneficial effect was attributable to residual confounding associated with individuals\u2019 overall health, not metformin itself.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n These findings suggest that common observational study designs for studies of metformin in a type 2 diabetes population are at risk for consequential residual confounding. By performing 2 additional validation checks, the study design proposed here exposes residual confounding that nullifies the initially favorable claim derived from a common study design.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2022.41505","type":"journal-article","created":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T11:33:00Z","timestamp":1668166380000},"page":"e2241505","source":"Crossref","is-referenced-by-count":11,"title":["Exploration of Residual Confounding in Analyses of Associations of Metformin Use and Outcomes in Adults With Type 2 Diabetes"],"prefix":"10.1001","volume":"5","author":[{"given":"Mike","family":"Powell","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Callahan","family":"Clark","sequence":"additional","affiliation":[{"name":"Optum Labs, Minnetonka, 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