title: Bayesian methods including nonrandomized study data increased the efficiency of postlaunch RCTs.
abstract: OBJECTIVE
  Findings from nonrandomized studies on safety or efficacy of treatment in patient subgroups may trigger postlaunch randomized clinical trials (RCTs). In the analysis of such RCTs, results from nonrandomized studies are typically ignored. This study explores the trade-off between bias and power of Bayesian RCT analysis incorporating information from nonrandomized studies.
  
  
  METHODS
  A simulation study was conducted to compare frequentist with Bayesian analyses using noninformative and informative priors in their ability to detect interaction effects. In simulated subgroups, the effect of a hypothetical treatment differed between subgroups (odds ratio 1.00 vs. 2.33). Simulations varied in sample size, proportions of the subgroups, and specification of the priors.
  
  
  RESULTS
  As expected, the results for the informative Bayesian analyses were more biased than those from the noninformative Bayesian analysis or frequentist analysis. However, because of a reduction in posterior variance, informative Bayesian analyses were generally more powerful to detect an effect. In scenarios where the informative priors were in the opposite direction of the RCT data, type 1 error rates could be 100% and power 0%.
  
  
  CONCLUSIONS
  Bayesian methods incorporating data from nonrandomized studies can meaningfully increase power of interaction tests in postlaunch RCTs.
authors.affiliation: Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Universiteitsweg 100, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Universiteitsweg 99, P.O. Box 80082, 3508 TB Utrecht, The Netherlands; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, The Netherlands; Institute of Cardiovascular Science, Faculty of Population Health, University College London, 222 Euston Road, London NW1 2DA, United Kingdom. Electronic address: amand.schmidt@ucl.ac.uk.
authors.forename: Amand F
authors.initials: AF
authors.lastname: Schmidt
authors.affiliation: Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, P.O. Box 80140, 3508 TC Utrecht, The Netherlands.
authors.forename: Irene
authors.initials: I
authors.lastname: Klugkist
authors.affiliation: Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Universiteitsweg 100, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Universiteitsweg 99, P.O. Box 80082, 3508 TB Utrecht, The Netherlands.
authors.forename: Olaf H
authors.initials: OH
authors.lastname: Klungel
authors.affiliation: Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, The Netherlands.
authors.forename: Mirjam
authors.initials: M
authors.lastname: Nielen
authors.affiliation: Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Universiteitsweg 99, P.O. Box 80082, 3508 TB Utrecht, The Netherlands.
authors.forename: Anthonius
authors.initials: A
authors.lastname: de Boer
authors.affiliation: Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Universiteitsweg 100, P.O. Box 85500, 3508 GA Utrecht, The Netherlands.
authors.forename: Arno W
authors.initials: AW
authors.lastname: Hoes
authors.affiliation: Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Universiteitsweg 100, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Universiteitsweg 99, P.O. Box 80082, 3508 TB Utrecht, The Netherlands.
authors.forename: Rolf H H
authors.initials: RH
authors.lastname: Groenwold
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D003198:Computer Simulation; D005260:Female; D006620:Hip Fractures / Q000139:chemically induced / Q000453:epidemiology; D006801:Humans; D008297:Male; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design; D000077154:Rosiglitazone; D018401:Sample Size; D045162:Thiazolidinediones / Q000008:administration & dosage / Q000009:adverse effects
chemical_list: D045162:Thiazolidinediones; D000077154:Rosiglitazone
keywords: Bayesian statistics; Frequentist statistics; Nonrandomized study design; Observational study design; Randomized controlled trial; Simulation