Observational and clinical trial findings on the comparative effectiveness of diabetes drugs showed agreement

Rivaroxaban was found to be noninferior to warfarin in routine clinical care: A retrospective noninferiority cohort replication study

Purpose

To compare the effectiveness and safety of a drug in daily practice with the outcomes of a target non‐inferiority trial by rigorously mimickingin an observational study the trial's design features.

Methods

This cohort study was conducted using the British Clinical Practice Research Datalink (CPRD) to emulate the ROCKET AF (Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation) trial. Patients with atrial fibrillation who were newly prescribed (>=12 months of no use) either rivaroxaban or warfarinfrom October 2008 to December 2017 were included. Non‐inferiority of rivaroxaban to warfarin in the prevention of stroke or systemic embolism was assessed in different analysis populations (intention‐to‐treat [ITT], per‐protocol [PP], and as‐treated populations) using a hazardratio (HR) of 1.46 as the non‐inferiority margin. Major bleeding (safety outcome) was also assessed and compared to that of the target trial. All outcomes were analyzed using Cox‐proportional hazard analyses.

Results

We included 25,473 incident users of rivaroxaban (n=4,008) or warfarin(n=21,465). Similar to the trial, non‐inferiority in the primary out come was demonstrated in all three analysis populations: HR=1.04 (95%CI 0.84 to 1.30) (ITT), HR=0.98 (95%CI 0.70 to 1.38) (PP), and HR=1.11 (95%CI 0.86 to 1.42) (as‐treated). Risk of major bleeding was also similar to the target trial.

Conclusion

The results of this study provide supportive evidence to the effectiveness of rivaroxaban and adds knowledge on the usefulness of emulating a non‐inferiority trial to assess drug effectiveness.

Identifying the "Blip on the Radar Screen": Leveraging Big Data in Defining Drug Safety and Efficacy in Pediatric Practice

The immense amount of electronic health data (pharmacy and administrative claims, electronic health records, and clinical registries) that is being generated every day in the care of patients has the potential to be leveraged for improving clinical decisions at the point of care, uncovering or validating drug efficacy and drug safety. The potential use of big data for improving safe and effective use of medications is especially important in children because of their low drug exposure relative to adults. Electronic health data is collected primarily for clinical or billing purposes and not for research purposes. The major steps involved in data acquisition, extraction, aggregation, analysis, modeling, and interpretation are discussed. It is important to understand the limitation of big data and utilize appropriate study design and statistical methods. Possible applications are presented along with specific examples of how big data has been used in drug research to find that blip on the radar screen that may give an efficacy or safety signal that can lead to further investigation.