Association between statin exposure and diabetes incidence among privately-insured patients before and after applying a novel technique to control for selection bias

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: The association between statins and incident diabetes mellitus (DM) in observational studies is much larger than that reported from randomized controlled trials. We sought to assess this association using a novel design controlling for selection bias. Methods: Using data from MarketScan, we identified a cohort of non-diabetic patients who initiated a statin and matched them to patients not taking statins. From the statin-user cohort, we identified two subgroups: patients who received statin refills for >6 months (continuers) and patients who received statin refills <6 months (discontinuers). Patients were followed for a minimum of two years to determine incident DM. Results: We included 442,526 patients, divided equally between statin users and non-users. Statin use was associated with increased DM (9.9% vs. 4.4%, HR 2.2, p < 0.001). Among the 221,263 statin users, there were 194,357 continuers and 26,906 discontinuers. There was no significant difference in the incidence rate of DM between both groups (10.0% vs. 9.3%, HR 1.03, p = 0.22). Conclusions: Statin use was strongly associated with incident diabetes when users were compared to non-users but not when continuers were compared to discontinuers. Selection bias confounds the association between statin use and incident diabetes in observational studies.

Original languageEnglish (US)
Pages (from-to)26-30
Number of pages5
JournalAmerican Journal of the Medical Sciences
Volume365
Issue number1
DOIs
StatePublished - Jan 2023

All Science Journal Classification (ASJC) codes

  • General Medicine

Fingerprint

Dive into the research topics of 'Association between statin exposure and diabetes incidence among privately-insured patients before and after applying a novel technique to control for selection bias'. Together they form a unique fingerprint.

Cite this