Dependent censoring involves a preferential attrition of a subgroup of interest; occurring in survival analysis, it may impact interpretation by introducing a selection bias. To assess the potential bias in a comparison of bisoprolol to other antihypertensives in terms of Type 2 diabetes mellitus (T2DM) incidence, inverse probability of censoring weights (IPCW) was used. It was further used to contextualize results obtained through competing risks analysis. Two estimands were considered to assess T2DM incidence while accounting for deviations from the initial antihypertensive monotherapy (DFM). A hypothetical estimand using IPCW, treating DFM as censoring, was interpreted together with a 'while-on-treatment' estimand, treating DFM as a competing risk. We illustrated our application with a cohort study based on Clinical Practice Research Datalink (CPRD) including 267,352 patients with newly diagnosed arterial hypertension between 2000 and 2017, initiating antihypertensive monotherapy among bisoprolol, other beta-blockers, renin-angiotensin system drugs (ACEi/ARB), diuretics and calcium-channel blockers. A mild dependent censoring process was hypothesized, leading to slight overestimation of T2DM incidence. Although subject to some limitations, a nonsignificant trend toward an excess of risk associated with ACEi/ARB was yielded consistently by IPCW and competing risks analyses. Conversely, in comparisons of bisoprolol versus either diuretics, other beta-blockers or calcium channel blockers, no significant differences or critical dependent censoring impact were found. Concurrent use of complementary estimands allowed formulating a refined interpretation of our findings: though not significant, the trend toward an excess of T2DM risk associated with a ACEi/ARB monotherapy compared with bisoprolol is likely not originating only from the minor dependent censoring. Reassessing identical estimands in other cohorts would provide insights to corroborate or refute this result.
Keywords: CPRD; IPCW; Type 2 diabetes mellitus; antihypertensive therapy; bisoprolol; censoring bias; real-world evidence.