Stopping randomized trials early for benefit and estimation of treatment effects: systematic review and meta-regression analysis.

CONTEXT: Theory and simulation suggest that randomized controlled trials (RCTs) stopped early for benefit (truncated RCTs) systematically overestimate treatment effects for the outcome that precipitated early stopping. OBJECTIVE: To compare the treatment effect from truncated RCTs with that from meta-analyses of RCTs addressing the same question but not stopped early (nontruncated RCTs) and to explore factors associated with overestimates of effect. DATA SOURCES: Search of MEDLINE, EMBASE, Current Contents, and full-text journal content databases to identify truncated RCTs up to January 2007; search of MEDLINE, Cochrane Database of Systematic Reviews, and Database of Abstracts of Reviews of Effects to identify systematic reviews from which individual RCTs were extracted up to January 2008. STUDY SELECTION: Selected studies were RCTs reported as having stopped early for benefit and matching nontruncated RCTs from systematic reviews. Independent reviewers with medical content expertise, working blinded to trial results, judged the eligibility of the nontruncated RCTs based on their similarity to the truncated RCTs. DATA EXTRACTION: Reviewers with methodological expertise conducted data extraction independently. RESULTS: The analysis included 91 truncated RCTs asking 63 different questions and 424 matching nontruncated RCTs. The pooled ratio of relative risks in truncated RCTs vs matching nontruncated RCTs was 0.71 (95% confidence interval, 0.65-0.77). This difference was independent of the presence of a statistical stopping rule and the methodological quality of the studies as assessed by allocation concealment and blinding. Large differences in treatment effect size between truncated and nontruncated RCTs (ratio of relative risks <0.75) occurred with truncated RCTs having fewer than 500 events. In 39 of the 63 questions (62%), the pooled effects of the nontruncated RCTs failed to demonstrate significant benefit. CONCLUSIONS: Truncated RCTs were associated with greater effect sizes than RCTs not stopped early. This difference was independent of the presence of statistical stopping rules and was greatest in smaller studies.

'All the King's horses . . .': the problematical fate of born-again evidence-based medicine: commentary on Greenhalgh, T., Snow, R., Ryan, S., Rees, S., and Salisbury, H. (2015) six 'biases' against patients and carers in evidence-based medicine. BioMed Central Medicine, 13:200.

The phrase 'evidence-based medicine (EBM)' is being used by both EBM advocates and adversaries to broadly denote the production and use of clinical research throughout the healthcare system. Recently, this trend was joined by a call for a general expansion and rebirth of EBM to encompass a diverse range of healthcare activities otherwise corresponding to person-centred care. The call asserts that EBM is to blame for anti-patient biases within clinical practice and in policy and public health domains. Effective critique of either EBM or of the healthcare system requires that EBM itself be properly identified as a research literacy movement that grew out of clinical epidemiology of the 1970's and 1980's. We demonstrate the ineffectiveness of inappropriately targeted critiques of healthcare under the banner of born-again EBM.We identify the strengths and weaknesses of EBM as an educational movement drawing on the concept of literacy associated with the Brazilian educator Paolo Freire. We consider the relationship of EBM to clinical epidemiology and conclude that it cannot fruitfully divorce itself from the latter.We briefly consider existing precedents for philosophically sound conceptual platforms for advocacy of person-centred healthcare and broad based critique of the healthcare system including relationship-centred care. We conclude that traditional EBM, as a framework for research literacy training of both clinicians and policy makers, must continue to play a subsidiary role within an expanding patient-centred healthcare system and that advocacy efforts on behalf of patient voice and engagement are best pursued unencumbered by subsidiary agendas.

'One mission accomplished, more important ones remain': commentary on Every-Palmer, S., Howick, J. (2014) How evidence-based medicine is failing due to biased trials and selective publication. Journal of†Evaluation in†Clinical†Practice, 20 (6), 908-914.

Every-Palmer and Howick suggest that evidence-based medicine (EBM) is failing in its mission because of contamination of research by manufacturer and researcher-motivated bias and self-interest. They fail to define that mission and to distinguish between the EBM movement and the research enterprise it was developed to critique. An educational movement, EBM accomplished its mission to simplify and package clinical epidemiological concepts in a form accessible to clinical learners. Its wide adoption within educational circles fostered critical literacy among several generations of practitioners. Illumination of bias, subterfuge and incomplete reporting of research has been a strength of EBM. Increased uptake and use of clinical research within the health care system properly defines the failing mission that eludes Every-Palmer and Howick. Responsibility for failure to make progress towards its achievement is shared by virtually all relevant streams within the system, including policy, clinical guideline development, educational movements and the development of approaches to evidence synthesis. Discordance between the epistemological premises pervading today's research and health care community and the complex social processes that ultimately determine research use constitutes an important factor that must be addressed as part of a remedy. Enhanced emphasis on and demonstration of alternative approaches to research such as realism and realist synthesis and the momentum towards development of a learning health care system hold promise as guideposts for the rapidly evolving health care environment.

Stopping randomized trials early for benefit: a protocol of the Study Of Trial Policy Of Interim Truncation-2 (STOPIT-2).

BACKGROUND: Randomized clinical trials (RCTs) stopped early for benefit often receive great attention and affect clinical practice, but pose interpretational challenges for clinicians, researchers, and policy makers. Because the decision to stop the trial may arise from catching the treatment effect at a random high, truncated RCTs (tRCTs) may overestimate the true treatment effect. The Study Of Trial Policy Of Interim Truncation (STOPIT-1), which systematically reviewed the epidemiology and reporting quality of tRCTs, found that such trials are becoming more common, but that reporting of stopping rules and decisions were often deficient. Most importantly, treatment effects were often implausibly large and inversely related to the number of the events accrued. The aim of STOPIT-2 is to determine the magnitude and determinants of possible bias introduced by stopping RCTs early for benefit. METHODS/DESIGN: We will use sensitive strategies to search for systematic reviews addressing the same clinical question as each of the tRCTs identified in STOPIT-1 and in a subsequent literature search. We will check all RCTs included in each systematic review to determine their similarity to the index tRCT in terms of participants, interventions, and outcome definition, and conduct new meta-analyses addressing the outcome that led to early termination of the tRCT. For each pair of tRCT and systematic review of corresponding non-tRCTs we will estimate the ratio of relative risks, and hence estimate the degree of bias. We will use hierarchical multivariable regression to determine the factors associated with the magnitude of this ratio. Factors explored will include the presence and quality of a stopping rule, the methodological quality of the trials, and the number of total events that had occurred at the time of truncation.Finally, we will evaluate whether Bayesian methods using conservative informative priors to "regress to the mean" overoptimistic tRCTs can correct observed biases. DISCUSSION: A better understanding of the extent to which tRCTs exaggerate treatment effects and of the factors associated with the magnitude of this bias can optimize trial design and data monitoring charters, and may aid in the interpretation of the results from trials stopped early for benefit.