DPP-4阻害薬と心血管イベント：MACEリスクに対するエリア別処方傾向と医師の処方選好度を比較したインストゥルメンタル変数法

Randomized trials (RCT) of major adverse cardiovascular events found no effect of dipeptidyl-peptidase-4 inhibitors (DPP-4i) medications compared to second-generation sulfonylureas while non-randomized studies estimated a benefit of DPP-4i. Socioeconomic residual confounding was thought to be implicated. We compared area-level prescribing density and physician prescribing preference as candidate instrumental variables for the effect of DPP-4i medications on major adverse cardiovascular events.

Using Medicare claims data, we built two cohorts emulating RCTs of sitagliptin or saxagliptin starters, each compared to sulfonylurea starters. The proportion of DPP-4i prescribing in a ZIP Code tabulation area defined the area-level prescribing density instrumental variable at various cutoffs (0% vs. 100% to <50% vs. ≥50%). Patients' physician prescribing history using the same proportion cutoffs was the physician prescribing preference candidate instrumental variable. An instantaneous physician preference instrumental variable used a physician's most recent prescription. We adjusted two-stage instrumental variable regression models for propensity score quintiles.

Unadjusted analyses for sitagliptin and saxagliptin, each compared to sulfonylurea, estimated a reduced risk of major adverse cardiovascular events (sitagliptin hazard ratio (HR)=0.86; 95% confidence interval 0.83 to 0.88); saxagliptin HR=0.68; 0.64 to 0.73). All instrumental variables were strong and reduced covariate imbalance. Analyses of area-level prescribing density found no meaningful difference for sitagliptin (0% vs. 100% HR=1.1; 0.79 to 1.6). Analyses of physician prescribing preference estimated reduced risk for sitagliptin (<50% vs. ≥50% HR=0.69; 0.48 to 0.98). Instantaneous physician prescribing preference analyses showed little to no difference for sitagliptin (HR=0.86; 0.60 to 1.1) and saxagliptin (HR=0.98; 0.56 to 1.7).

Candidate instrumental variables focusing on short-term prescribing preference hold promise over area-based variables but remain inefficient.