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      Are Novel, Nonrandomized Analytic Methods Fit for Decision Making? The Need for Prospective, Controlled, and Transparent Validation

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          Abstract

          Real‐world data and patient‐level data from completed randomized controlled trials are becoming available for secondary analysis on an unprecedented scale. A range of novel methodologies and study designs have been proposed for their analysis or combination. However, to make novel analytical methods acceptable for regulators and other decision makers will require their testing and validation in broadly the same way one would evaluate a new drug: prospectively, well‐controlled, and according to a pre‐agreed plan. From a European regulators' perspective, the established methods qualification advice procedure with active participation of patient groups and other decision makers is an efficient and transparent platform for the development and validation of novel study designs.

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          Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials.

          To determine if inadequate approaches to randomized controlled trial design and execution are associated with evidence of bias in estimating treatment effects. An observational study in which we assessed the methodological quality of 250 controlled trials from 33 meta-analyses and then analyzed, using multiple logistic regression models, the associations between those assessments and estimated treatment effects. Meta-analyses from the Cochrane Pregnancy and Childbirth Database. The associations between estimates of treatment effects and inadequate allocation concealment, exclusions after randomization, and lack of double-blinding. Compared with trials in which authors reported adequately concealed treatment allocation, trials in which concealment was either inadequate or unclear (did not report or incompletely reported a concealment approach) yielded larger estimates of treatment effects (P < .001). Odds ratios were exaggerated by 41% for inadequately concealed trials and by 30% for unclearly concealed trials (adjusted for other aspects of quality). Trials in which participants had been excluded after randomization did not yield larger estimates of effects, but that lack of association may be due to incomplete reporting. Trials that were not double-blind also yielded larger estimates of effects (P = .01), with odds ratios being exaggerated by 17%. This study provides empirical evidence that inadequate methodological approaches in controlled trials, particularly those representing poor allocation concealment, are associated with bias. Readers of trial reports should be wary of these pitfalls, and investigators must improve their design, execution, and reporting of trials.
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            Robust meta-analytic-predictive priors in clinical trials with historical control information.

            Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.
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              Evaluating the Use of Nonrandomized Real‐World Data Analyses for Regulatory Decision Making

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                Author and article information

                Contributors
                Hans-Georg.Eichler@ema.europa.eu
                Journal
                Clin Pharmacol Ther
                Clin. Pharmacol. Ther
                10.1002/(ISSN)1532-6535
                CPT
                Clinical Pharmacology and Therapeutics
                John Wiley and Sons Inc. (Hoboken )
                0009-9236
                1532-6535
                01 October 2019
                April 2020
                01 October 2019
                : 107
                : 4 , Data Science ( doiID: 10.1002/cpt.v107.4 )
                : 773-779
                Affiliations
                [ 1 ] European Medicines Agency (EMA) Amsterdam The Netherlands
                [ 2 ] Medical University of Vienna Vienna Austria
                [ 3 ] Federal Institute for Drugs and Medical Devices (BfArM) Bonn Germany
                [ 4 ] EMA's Committee for Medicinal Products for Human Use (CHMP) Amsterdam The Netherlands
                [ 5 ] EMA's Committee for Orphan Medicinal Products (COMP) Amsterdam The Netherlands
                [ 6 ] Universidade de Lisboa Lisbon Portugal
                [ 7 ] University Tor Vergata Rome Italy
                Author notes
                [*] [* ]Correspondence: Hans‐Georg Eichler ( Hans-Georg.Eichler@ 123456ema.europa.eu )
                Article
                CPT1638
                10.1002/cpt.1638
                7158212
                31574163
                b583fb35-c3f7-4dad-a15d-bc4712464e9c
                © 2019 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 16 July 2019
                : 02 September 2019
                Page count
                Figures: 0, Tables: 1, Pages: 7, Words: 5501
                Categories
                State of the Art
                Reviews
                State of the Art
                Custom metadata
                2.0
                April 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.0 mode:remove_FC converted:14.04.2020

                Pharmacology & Pharmaceutical medicine
                Pharmacology & Pharmaceutical medicine

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