Stopping Randomized Trials Early for Benefit: A Protocol of the Study Of Trial Policy Of Interim Truncation-2 (STOPIT-2)
Authors
Matthias Briel, McMaster University
Melanie Lane, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Victor M. Montori, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Dirk Bassler, University Children's Hospital Tuebingen, Tuebingen, Germany
Paul Glasziou, University of Oxford
German Malaga, Universidad Peruana Cayetano Heredia
Elie A. Akl, State University of New York at Buffalo
Ignacio Ferreira-Gonzalez, Vall d'Hebron Hospital, Spain
Pablo Alonso-Coello, Hospital Sant Pau, Barcelona, Spain
Gerard Urrutia, Hospital Sant Pau, Barcelona, Spain
Regina Kunz, University Hospital Basel, Basel, Switzerland
Carolina Ruiz Culebro, McMaster University
Suzana Alves da Silva, Teaching and Research Center of Pro-Cardiaco, Rio de Janeiro, Brazil
David N. Flynn, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Mohamed B. Elamin, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Brigitte Strahm, University Hospital Freiburg, Freiburg, Germany
M. Hassan Murad, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Benjamin Djulbegovic, USF Health Clinical Research, Tampa, FL
Neill K. J. Adhikari, University of Toronto
Edward J. Mills, University of British Columbia
Femida Gwadry-Sridhar, University of Western Ontario
Haresh Kirpalani, McMaster University
Heloisa P. Soares, Mount Sinai Medical Center, Miami Beach, FL
Nisrin O. Abu Elnour, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
John J. You, McMaster University
Paul J. Karanicolas, University of Western OntarioFollow
Heiner C. Bucher, University Hospital Basel, Basel, Switzerland
Julianna F. Lampropulos, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Alain J. Nordmann, University Hospital Basel, Basel, Switzerland
Karen E. A. Burns, University of Toronto
Sohail M. Mulla, McMaster University
Heike Raatz, University Hospital Basel, Basel, Switzerland
Amit Sood, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Jagdeep Kaur, McMaster University
Clare R. Bankhead, University of Oxford
Rebecca J. Mullan, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Kara A. Nerenberg, McMaster University
Per Olav Vandvik, Innlandet Hospital Health Authority, Norway
Fernando Coto-Yglesias, Hospital Nacional de Geriatría y Gerontología San José, Costa Rica
Holger Schünemann, McMaster University
Fabio Tuche, Teaching and Research Center of Pro-Cardiaco, Rio de Janeiro, Brazil
Pedro Paulo M. Chrispim, National School of Public Health (ENSP), Rio de Janeiro, Brazil
Deborah J. Cook, McMaster University
Kristina Lutz, McMaster University
Christine M. Ribic, McMaster University
Noah Vale, McMaster University
Patricia J. Erwin, Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, MN
Rafael Perera, University of Oxford
Qi Zhou, McMaster University
Diane Heels-Ansdell, McMaster University
Tim Ramsay, University of Ottawa
Stephen D. Walter, McMaster University
Gordon H. Guyatt, McMaster University
Publication Date
7-6-2009
URL with Digital Object Identifier
http://dx.doi.org/10.1186/1745-6215-10-49
Abstract
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.
