title: A bias-adjusted evidence synthesis of RCT and observational data: the case of total hip replacement.
abstract: Evaluation of clinical effectiveness of medical devices differs in some aspects from the evaluation of pharmaceuticals. One of the main challenges identified is lack of robust evidence and a will to make use of experimental and observational studies (OSs) in quantitative evidence synthesis accounting for internal and external biases. Using a case study of total hip replacement to compare the risk of revision of cemented and uncemented implant fixation modalities, we pooled treatment effect estimates from OS and RCTs, and simplified existing methods for bias-adjusted evidence synthesis to enhance practical application. We performed an elicitation exercise using methodological and clinical experts to determine the strength of beliefs about the magnitude of internal and external bias affecting estimates of treatment effect. We incorporated the bias-adjusted treatment effects into a generalized evidence synthesis, calculating both frequentist and Bayesian statistical models. We estimated relative risks as summary effect estimates with 95% confidence/credibility intervals to capture uncertainty. When we compared alternative approaches to synthesizing evidence, we found that the pooled effect size strongly depended on the inclusion of observational data as well as on the use bias-adjusted estimates. We demonstrated the feasibility of using observational studies in meta-analyses to complement RCTs and incorporate evidence from a wider spectrum of clinically relevant studies and healthcare settings. To ensure internal validity, OS data require sufficient correction for confounding and selection bias, either through study design and primary analysis, or by applying post-hoc bias adjustments to the results. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center I, Hall i.T., Austria.
authors.forename: Petra
authors.initials: P
authors.lastname: Schnell-Inderst
authors.affiliation: Department of Health Sciences, University of York, Heslington, UK.|Centre for Health Economics, University of York, UK.|Hull and York Medical School, University of York, UK.|Luxemboug Institute of Health, Luxembourg.
authors.forename: Cynthia P
authors.initials: CP
authors.lastname: Iglesias
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center I, Hall i.T., Austria.
authors.forename: Marjan
authors.initials: M
authors.lastname: Arvandi
authors.affiliation: Institute of Health Services Research, University of Exeter Medical School, Exeter, UK.|Centre for Research on Health and Social Care Management, Bocconi University, Milan, Italy.
authors.forename: Oriana
authors.initials: O
authors.lastname: Ciani
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center I, Hall i.T., Austria.
authors.forename: Raffaella
authors.initials: R
authors.lastname: Matteucci Gothe
authors.affiliation: Institute of Health Services Research, University of Exeter Medical School, Exeter, UK.
authors.forename: Jaime
authors.initials: J
authors.lastname: Peters
authors.affiliation: Musculoskeletal Research Unit, University of Bristol, Bristol, UK.
authors.forename: Ashley W
authors.initials: AW
authors.lastname: Blom
authors.affiliation: Institute of Health Services Research, University of Exeter Medical School, Exeter, UK.
authors.forename: Rod S
authors.initials: RS
authors.lastname: Taylor
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center I, Hall i.T., Austria.|Center for Health Decision Science, Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA.|Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Uwe
authors.initials: U
authors.lastname: Siebert
mesh_terms: D019644:Arthroplasty, Replacement, Hip / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data; D015982:Bias; D057186:Comparative Effectiveness Research / Q000379:methods / Q000592:standards*; D055317:Evidence-Based Practice / Q000379:methods / Q000592:standards*; D006801:Humans; D064887:Observational Studies as Topic; D016032:Randomized Controlled Trials as Topic
keywords: bias adjustment; expert elicitation; generalized evidence synthesis; health technology assessment; medical devices