Use of negative control outcomes to assess the comparability of patients initiating lipid‐lowering therapies

Abstract

Purpose Clinical trials have demonstrated efficacy of proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) in reducing risk of cardiovascular disease events, but effectiveness in routine clinical care has not been well‐studied. We used negative control outcomes to assess potential confounding in an observational study of PCSK9i versus ezetimibe or high‐intensity statin. Methods Using commercial claims, we identified U.S. adults initiating PCSK9i, ezetimibe, or high‐intensity statin in 2015–2018, with other lipid‐lowering therapy (LLT) use in the year prior (LLT cohort) or atherosclerotic cardiovascular disease (ASCVD) in the past 90 days (ASCVD cohort). We compared initiators of PCSK9i to ezetimibe and high‐intensity statin by estimating one‐year risks of negative control outcomes influenced by frailty or health‐seeking behaviors. Inverse probability of treatment and censoring weighted estimators of risk differences (RDs) were used to evaluate residual confounding after controlling for covariates. Results PCSK9i initiators had lower one‐year risks of negative control outcomes associated with frailty, such as decubitus ulcer in the ASCVD cohort (PCSK9i vs. high‐intensity statin RD = −3.5%, 95% confidence interval (CI): −4.6%, −2.5%; PCSK9i vs. ezetimibe RD = −1.3%, 95% CI: −2.1%, −0.6%), with similar but attenuated associations in the LLT cohort. Lower risks of accidents and fractures were also observed for PCSK9i, varying by cohort. Risks were similar for outcomes associated with health‐seeking behaviors, although trended higher for PCSK9i in the ASCVD cohort. Conclusions Observed associations suggest lower frailty and potentially greater health‐seeking behaviors among PCSK9i initiators, particularly those with a recent ASCVD diagnosis, with the potential to bias real‐world analyses of treatment effectiveness.

Pragmatic considerations for negative control outcome studies to guide non‐randomized comparative analyses: A narrative review

“…The risk of decubitus ulcer among PCSK9i initiators was consistently lower (risk ratios 0.4-0.7), while risks of vaccinations tended to be higher (risk ratios 1.1-1.2 for some contrasts). 21 A subsequent NCO study can determine whether bias may be sufficiently reduced through more stringent inclusion criteria to balance patients' health status and healthcare access. Another design-driven approach would be to refine the comparator definition.…”

“…For example, in the NCO study of patients initiating lipid‐lowering therapies, results suggested patients with less frailty and higher healthcare utilization were more likely to be prescribed a PCSK9i compared with patients initiating statins or ezetimibe. The risk of decubitus ulcer among PCSK9i initiators was consistently lower (risk ratios 0.4–0.7), while risks of vaccinations tended to be higher (risk ratios 1.1–1.2 for some contrasts) 21 . A subsequent NCO study can determine whether bias may be sufficiently reduced through more stringent inclusion criteria to balance patients' health status and healthcare access.…”

“…Comprehensive reviews of prior work involving NCOs have already been conducted 14,15 ; instead, we focus on practical steps to be taken in future research and highlight as examples two recently conducted studies. 20,21 These studies were selected to illustrate use of a variety of NCOs corresponding to several confounding mechanisms in different therapeutic areas. The first assessed the comparability of disease risk for patients initiating osteoporosis medications 20 and the second for those initiating lipid-lowering therapies 21 (Table 1).…”

“…The objective of this narrative review is to propose considerations for the pragmatic use of NCOs in guiding study design decisions and highlight two recent studies that inform these recommendations. Comprehensive reviews of prior work involving NCOs have already been conducted 14,15 ; instead, we focus on practical steps to be taken in future research and highlight as examples two recently conducted studies 20,21 . These studies were selected to illustrate use of a variety of NCOs corresponding to several confounding mechanisms in different therapeutic areas.…”

Visualizations throughout pharmacoepidemiology study planning, implementation, and reporting

“…However, interactive data visualization tools can allow the user to easily browse a large volume of results from the many combinations of analyses that are performed. For example, in a negative control outcome study of lipid‐lowering therapies, 43 results from multiple outcomes, cohorts, and subgroups are easily explored using simple interactive graphs and tables 44 . Similarly, the Observational Health Data Science Initiative has created R packages to allow results from pharmacoepidemiologic studies to be explored via R/Shiny applications 45 .…”