Document Detail


Stopping rules and estimation problems in clinical trials.
MedLine Citation:
PMID:  3231947     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Stopping rules in clinical trials can lead to bias in point estimation of the magnitude of treatment difference. A simulation exercise, based on estimation of the risk ratio in a typical post-myocardial infarction trial, examines the nature of this exaggeration of treatment effect under various group sequential plans and also under continuous naive monitoring for statistical significance. For a fixed treatment effect the median bias in group sequential design is small, but it is greatest for effects that the trial has reasonable power to detect. Bias is evidently greater in trials that stop early and is dramatic under naive monitoring for significance. Group sequential plans lead to a multimodal sampling distribution of treatment effect, which poses problems for incorporating their estimates into meta-analyses. By simulating a population of trials with treatment effects modelled by an underlying distribution of true risk ratios, a Bayesian method is proposed for assessing the plausible range of true treatment effect for any trial based on interim results. This approach is particularly useful for producing shrinkage of the unexpectedly large and imprecise observed treatment effects that arise in clinical trials that stop early. Its implications for trial design are discussed.
Authors:
M D Hughes; S J Pocock
Related Documents :
10986437 - Control of error in randomized clinical trials.
21446857 - Participation frequency and perceived participation restrictions at older age: applying...
19706267 - Perceived curative factors and their relationship to outcome: a study of schizophrenic ...
21249697 - Acupuncture for primary dysmenorrhoea.
15261607 - Neuroprotection and pharmacotherapy for motor symptoms in parkinson's disease.
17491177 - Impact of a cell phone intervention on mediating mechanisms of smoking cessation in ind...
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Statistics in medicine     Volume:  7     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  1988 Dec 
Date Detail:
Created Date:  1989-04-20     Completed Date:  1989-04-20     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  1231-42     Citation Subset:  IM    
Affiliation:
Department of Clinical Epidemiology and General Practice, Royal Free Hospital School of Medicine, London, U.K.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Bayes Theorem*
Clinical Trials as Topic*
Humans
Mathematics
Meta-Analysis as Topic
Probability*
Random Allocation
Research Design

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Bayesian analysis of case-control studies.
Next Document:  A quantitative study of the bias in estimating the treatment effect caused by omitting a balanced co...