Literature DB >> 1432006

Meta-analysis adjusting for compliance: the example of screening for breast cancer.

P P Glasziou1.   

Abstract

Randomized controlled trials are usually analysed by the group to which the patient was randomized, i.e. by "intention-to-treat", regardless of the degree of compliance. However, the "explanatory" effect, i.e. the effect that would occur if we had 100% compliance, is often of interest. This "explanatory" effect is diluted by poor compliance, and hence meta-analyses should ideally avoid both the heterogeneity of effect due to variation in compliance rates among studies, and the undeserved weight given to trials with poor compliance. Newcombe's deattenuation method, which adjusts estimates for the degree of compliance, is extended and applied to a meta-analysis of the five reported randomized controlled trials of mammographic screening. Compliance with screening varied across studies: from 61 to 93% assigned to screening had one or more mammograms. The adjusted estimate of the reduction in breast cancer mortality at 9 years follow-up is 0.37 (95% confidence interval: 0.21, 0.49).

Entities:  

Mesh:

Year:  1992        PMID: 1432006     DOI: 10.1016/0895-4356(92)90166-k

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  15 in total

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Review 2.  Screening for colorectal cancer using the faecal occult blood test, Hemoccult.

Authors:  P Hewitson; P Glasziou; L Irwig; B Towler; E Watson
Journal:  Cochrane Database Syst Rev       Date:  2007-01-24

3.  Participation in mammography screening.

Authors:  Lisa M Schwartz; Steven Woloshin
Journal:  BMJ       Date:  2007-10-13

4.  A Bayesian hierarchical model estimating CACE in meta-analysis of randomized clinical trials with noncompliance.

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5.  A systematic review of the effects of screening for colorectal cancer using the faecal occult blood test, hemoccult.

Authors:  B Towler; L Irwig; P Glasziou; J Kewenter; D Weller; C Silagy
Journal:  BMJ       Date:  1998-08-29

6.  Model of outcomes of screening mammography: information to support informed choices.

Authors:  Alexandra Barratt; Kirsten Howard; Les Irwig; Glenn Salkeld; Nehmat Houssami
Journal:  BMJ       Date:  2005-03-08

7.  Latent class instrumental variables: a clinical and biostatistical perspective.

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8.  An IV for the RCT: using instrumental variables to adjust for treatment contamination in randomised controlled trials.

Authors:  Jeremy B Sussman; Rodney A Hayward
Journal:  BMJ       Date:  2010-05-04

Review 9.  Estimating the Complier Average Causal Effect in a Meta-Analysis of Randomized Clinical Trials With Binary Outcomes Accounting for Noncompliance: A Generalized Linear Latent and Mixed Model Approach.

Authors:  Ting Zhou; Jincheng Zhou; James S Hodges; Lifeng Lin; Yong Chen; Stephen R Cole; Haitao Chu
Journal:  Am J Epidemiol       Date:  2022-01-01       Impact factor: 5.363

10.  A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials.

Authors:  John Simes; Merryn Voysey; Rachel O'Connell; Paul Glasziou; James D Best; Russell Scott; Christopher Pardy; Karen Byth; David R Sullivan; Christian Ehnholm; Anthony Keech
Journal:  PLoS One       Date:  2010-01-08       Impact factor: 3.240

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