Crown, William H.

Background/aims There has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials. Methods This study compared participants’ demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials’ using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance). Results The PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial. Conclusion Despite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Abstract Objective To emulate the GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) trial using real world data before its publication. GRADE directly compared second line glucose lowering drugs for their ability to lower glycated hemoglobin A 1c (HbA 1c ). Design Observational study. Setting OptumLabs® Data Warehouse (OLDW), a nationwide claims database in the US, 25 January 2010 to 30 June 2019. Participants Adults with type 2 diabetes and HbA 1c 6.8-8.5% while using metformin monotherapy, identified according to the GRADE trial specifications, who also used glimepiride, liraglutide, sitagliptin, or insulin glargine. Main outcome measures The primary outcome was time to HbA 1c ≥7.0%. Secondary outcomes were time to HbA 1c >7.5%, incident microvascular complications, incident macrovascular complications, adverse events, all cause hospital admissions, and all cause mortality. Propensity scores were estimated using the gradient boosting machine method, and inverse propensity score weighting was used to emulate randomization of the treatment groups, which were then compared using Cox proportional hazards regression. Results 8252 people were identified (19.7% of adults starting the study drugs in OLDW) who met eligibility criteria for the GRADE trial (glimepiride arm=4318, liraglutide arm=690, sitagliptin arm=2993, glargine arm=251). The glargine arm was excluded from analyses owing to small sample size. Median times to HbA 1c ≥7.0% were 442 days (95% confidence interval 394 to 480 days) for glimepiride, 764 (741 to not calculable) days for liraglutide, and 427 (380 to 483) days for sitagliptin. Liraglutide was associated with lower risk of reaching HbA 1c ≥7.0% compared with glimepiride (hazard ratio 0.57, 95% confidence interval 0.43 to 0.75) and sitagliptin (0.55, 0.41 to 0.73). Results were consistent for the secondary outcome of time to HbA 1c >7.5%. No significant differences were observed among treatment groups for the remaining secondary outcomes. Conclusions In this emulation of the GRADE trial, liraglutide was statistically significantly more effective at maintaining glycemic control than glimepiride or sitagliptin when added to metformin monotherapy. Generating timely evidence on medical treatments using real world data as a complement to prospective trials is of value.

Background In comparison to warfarin, non–vitamin K antagonist oral anticoagulants ( NOAC s) have the advantages of ease of dosing, fewer drug interactions, and lack of need for ongoing monitoring. We sought to evaluate whether these advantages translate to improved adherence and whether adherence is associated with improved outcomes in patients with atrial fibrillation. Methods and Results We performed a retrospective cohort analysis by using a large US commercial insurance database to identify 64 661 patients with atrial fibrillation who initiated warfarin, dabigatran, rivaroxaban, or apixaban treatment between November 1, 2010, and December 31, 2014. During a median of 1.1 y of follow‐up, 47.5% of NOAC patients had a proportion of days covered of ≥80%, compared with 40.2% in warfarin patients ( P <0.001). Patients with CHA 2 DS 2 ‐ VAS c (risk based on the presence of congestive heart failure, hypertension age 65–74 y, age ≥75 y, diabetes mellitus, prior stroke or transient ischemic attack, vascular disease, sex category) score ≥4 were at increased risk of stroke when they were not taking anticoagulation ≥1 month versus <1 week (1–3 months: hazard ratio [ HR ] 1.96, 3–6 months: HR 2.64, ≥6 months: HR 3.66; all P <0.001). Patients with CHA 2 DS 2 ‐ VAS c score 2 or 3 were at increased risk of stroke when they were not taking anticoagulation ≥6 months ( HR 2.73, P <0.001). In these patients with CHA 2 DS 2 ‐ VAS c score ≥2, nonadherence was not associated with intracranial hemorrhage. Among patients with CHA 2 DS 2 ‐ VAS c score 0 or 1, time not taking anticoagulation was not associated with stroke, but not taking anticoagulation ≥3 months was associated with a significant reduction of bleeding. Conclusions Adherence to anticoagulation is poor in practice and may be modestly improved with NOAC s. Adherence to therapy appears to be most important in patients with CHA 2 DS 2 ‐ VAS c score ≥2, whereas the benefits of anticoagulation may not outweigh the harms in patients with CHA 2 DS 2 ‐ VAS c score 0 or 1.

Aim: Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. Methods: This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. Results: The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. Conclusion: The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

Propensity score (PS) methods have proliferated in recent years in observational studies in general and in observational comparative effectiveness research (CER) in particular. PS methods are an important set of tools for estimating treatment effects in observational studies, enabling adjustment for measured confounders in an easy-to-understand and transparent way. This article demonstrates how PS methods have been used to address specific CER questions from 2001 through to 2012 by identifying six impactful studies from this period. This article also discusses areas for improvement, including data infrastructure, and a unified set of guidelines in terms of PS implementation and reporting, which will boost confidence in evidence generated through observational CER using PS methods.