Drug‐Drug Interaction Surveillance Study: Comparing Self‐Controlled Designs in Five Empirical Examples in Real‐World Data

Abstract

Self‐controlled designs, specifically the case‐crossover (CCO) and the self‐controlled case series (SCCS), are increasingly utilized to generate real‐world evidence (RWE) on drug‐drug interactions (DDIs). Although these designs share the advantages and limitations of within‐individual comparison, they also have design‐specific assumptions. It is not known to what extent the differences in assumptions lead to different results in RWE DDI analyses. Using a nationwide US commercial healthcare insurance database (2006–2016), we compared the CCO and SCCS designs, as they are implemented in DDI studies, within five DDI‐outcome examples: (1) simvastatin + clarithromycin and muscle‐related toxicity; (2) atorvastatin + valsartan, and muscle‐related toxicity; and (3–5) dabigatran + P‐glycoprotein inhibitor (clarithromycin, amiodarone, and verapamil) and bleeding. Analyses were conducted within person‐time exposed to the object drug (statins and dabigatran) and adjusted for bias associated with the inhibiting drugs via control groups of individuals unexposed to the object drug. The designs yielded similar estimates in most examples, with SCCS displaying better statistical efficiency. With both designs, results varied across sensitivity analyses, particularly in CCO analyses with small number of exposed individuals. Analyses in controls revealed substantial bias that may be differential across DDI‐exposed and control individuals. Thus, both designs showed no association between amiodarone or verapamil and bleeding in dabigatran‐exposed but revealed strong positive associations in controls. Overall, bias adjustment via a control group had a larger impact on results than the choice of a design, highlighting the importance and challenges of appropriate control group selection for adequate bias control in self‐controlled analyses of DDIs.

Bleeding events among patients concomitantly treated with direct oral anticoagulants and macrolide or fluoroquinolone antibiotics

“…Bykov et al compared the case‐crossover and the self‐controlled case series designs to evaluate drug‐drug interactions in adults, including the effect of the concomitant use of dabigatran and clarithromycin on hospitalization for major bleeding. 9 Consistent with our results, using these two approaches they did not find any association between concomitant use and major bleeding, but they may have had low power due to a very small number of patients exposed to dabigatran and clarithromycin.…”

“…They are all metabolized by cytochrome p450 3a4 (CYP3A4) and/or are substrates for the efflux transporter P‐glycoprotein (P‐gp) and therefore susceptible to interactions with drugs that affect these enzymes. However, the contributions of CYP3A4 and P‐gp differ, and the drug interaction by concomitant use of drugs that inhibit or induce these enzymes and transporters shows differences between DOACs 7–9 …”

“…However, the contributions of CYP3A4 and P-gp differ, and the drug interaction by concomitant use of drugs that inhibit or induce these enzymes and transporters shows differences between DOACs. [7][8][9] Fluoroquinolones are widely used to treat urinary tract, gastrointestinal and respiratory infections. 10 The most commonly used fluoroquinolone in Sweden is ciprofloxacin, which is a moderate inhibitor of CYP3A4 and may also reduce the mRNA expression of CYP3A4 and P-gp by reducing the bacteria that produce hepatic secondary bile acids.…”

“…However, the contributions of CYP3A4 and P‐gp differ, and the drug interaction by concomitant use of drugs that inhibit or induce these enzymes and transporters shows differences between DOACs. 7 , 8 , 9 …”

Real‐World Evidence and the Regulation of Medicines

“…Bykov et al . have assessed how different RWE self‐controlled study designs can influence the results and conclusions in their paper, “Drug‐drug interaction surveillance study: comparing self‐controlled designs in five empirical examples in real‐world data.” 5 Pharmacopidemiological approaches have long been applied to detect and quantify the impact of drug‐drug interactions (DDIs), but the realization that the results can vary depending on the different approaches for post hoc bias adjustment is being recognized as RWE approaches become more commonplace 6 . The authors compare two frequently used self‐controlled designs to assess and quantify five different known DDIs.…”