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      Comparison of treatment effect sizes associated with surrogate and final patient relevant outcomes in randomised controlled trials: meta-epidemiological study

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective To quantify and compare the treatment effect and risk of bias of trials reporting biomarkers or intermediate outcomes (surrogate outcomes) versus trials using final patient relevant primary outcomes.

          Design Meta-epidemiological study.

          Data sources All randomised clinical trials published in 2005 and 2006 in six high impact medical journals: Annals of Internal Medicine, BMJ, Journal of the American Medical Association, Lancet, New England Journal of Medicine, and PLoS Medicine.

          Study selection Two independent reviewers selected trials.

          Data extraction Trial characteristics, risk of bias, and outcomes were recorded according to a predefined form. Two reviewers independently checked data extraction. The ratio of odds ratios was used to quantify the degree of difference in treatment effects between the trials using surrogate outcomes and those using patient relevant outcomes, also adjusted for trial characteristics. A ratio of odds ratios >1.0 implies that trials with surrogate outcomes report larger intervention effects than trials with patient relevant outcomes.

          Results 84 trials using surrogate outcomes and 101 using patient relevant outcomes were considered for analyses. Study characteristics of trials using surrogate outcomes and those using patient relevant outcomes were well balanced, except for median sample size (371 v 741) and single centre status (23% v 9%). Their risk of bias did not differ. Primary analysis showed trials reporting surrogate endpoints to have larger treatment effects (odds ratio 0.51, 95% confidence interval 0.42 to 0.60) than trials reporting patient relevant outcomes (0.76, 0.70 to 0.82), with an unadjusted ratio of odds ratios of 1.47 (1.07 to 2.01) and adjusted ratio of odds ratios of 1.46 (1.05 to 2.04). This result was consistent across sensitivity and secondary analyses.

          Conclusions Trials reporting surrogate primary outcomes are more likely to report larger treatment effects than trials reporting final patient relevant primary outcomes. This finding was not explained by differences in the risk of bias or characteristics of the two groups of trials.

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          Most cited references32

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

          K Schulz, I. Chalmers, R Hayes … (1995)
          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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            The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials.

            H. C. Bucher, G H Guyatt, L Griffith … (1997)
            When little or no data directly comparing two treatments are available, investigators often rely on indirect comparisons from studies testing the treatments against a control or placebo. One approach to indirect comparison is to pool findings from the active treatment arms of the original controlled trials. This approach offers no advantage over a comparison of observational study data and is prone to bias. We present an alternative model that evaluates the differences between treatment and placebo in two sets of clinical trials, and preserves the randomization of the originally assigned patient groups. We apply the method to data on sulphamethoxazole-trimethoprim or dapsone/pyrimethamine as prophylaxis against Pneumocystis carinii in HIV infected patients. The indirect comparison showed substantial increased benefit from the former (odds ratio 0.37, 95% CI 0.21 to 0.65), while direct comparisons from randomized trials suggests a much smaller difference (risk ratio 0.64, 95% CI 0.45 to 0.90; p-value for difference of effect = 0.11). Direct comparisons of treatments should be sought. When direct comparisons are unavailable, indirect comparison meta-analysis should evaluate the magnitude of treatment effects across studies, recognizing the limited strength of inference.
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              Surrogate end points in clinical trials: are we being misled?

              Thomas Fleming (1996)
              Article 0 comments Cited 254 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                : Role: PhD candidate
                : Role: chairman
                : Role: senior lecturer
                : Role: research fellow
                : Role: professor
                : Role: professor
                : Role: professor
                Journal
                Journal ID (nlm-ta): BMJ
                Journal ID (iso-abbrev): BMJ
                Journal ID (publisher-id): bmj
                Title: BMJ : British Medical Journal
                Publisher: BMJ Publishing Group Ltd.
                ISSN (Print): 0959-8138
                ISSN (Electronic): 1756-1833
                Publication date Collection: 2013
                Publication date (Print): 2013
                Publication date (Electronic): 29 January 2013
                Volume: 346
                Electronic Location Identifier: f457
                Affiliations
                [1 ]PenTAG, Institute for Health Services Research, University of Exeter Medical School, University of Exeter, Exeter EX2 4SG, UK
                [2 ]International Drug Development Institute, Louvain-la-Neuve, Belgium and Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium
                [3 ]School of Human Movement Studies, University of Queensland, Brisbane, QLD, Australia
                [4 ]School of Social and Community Medicine, University of Bristol, Bristol, UK
                Author notes
                Correspondence to: O Ciani oriana.ciani@ 123456pcmd.ac.uk
                Article
                Publisher ID: ciao006838
                DOI: 10.1136/bmj.f457
                PMC ID: 3558411
                PubMed ID: 23360719
                SO-VID: e59d5df4-4005-4418-a14b-944cdda335fc
                Copyright © © Ciani et al 2013
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

                History
                Date accepted : 29 October 2012
                Categories
                Subject: Research

                ScienceOpen disciplines: Medicine
                Data availability:
                ScienceOpen disciplines: Medicine

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