Document Detail

Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software.
MedLine Citation:
PMID:  22135359     Owner:  NLM     Status:  MEDLINE    
Two methods for point and interval estimation of relative risk for log-linear exposure-response relations in meta-analyses of published ordinal categorical exposure-response data have been proposed. The authors compared the results of a meta-analysis of published data using each of the 2 methods with the results that would be obtained if the primary data were available and investigated the circumstances under which the approximations required for valid use of each meta-analytic method break down. They then extended the methods to handle nonlinear exposure-response relations. In the present article, methods are illustrated using studies of the relation between alcohol consumption and colorectal and lung cancer risks from the ongoing Pooling Project of Prospective Studies of Diet and Cancer. In these examples, the differences between the results of a meta-analysis of summarized published data and the pooled analysis of the individual original data were small. However, incorrectly assuming no correlation between relative risk estimates for exposure categories from the same study gave biased confidence intervals for the trend and biased P values for the tests for nonlinearity and between-study heterogeneity when there was strong confounding by other model covariates. The authors illustrate the use of 2 publicly available user-friendly programs (Stata and SAS) to implement meta-analysis for dose-response data.
Nicola Orsini; Ruifeng Li; Alicja Wolk; Polyna Khudyakov; Donna Spiegelman
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2011-12-01
Journal Detail:
Title:  American journal of epidemiology     Volume:  175     ISSN:  1476-6256     ISO Abbreviation:  Am. J. Epidemiol.     Publication Date:  2012 Jan 
Date Detail:
Created Date:  2011-12-22     Completed Date:  2012-02-02     Revised Date:  2014-07-03    
Medline Journal Info:
Nlm Unique ID:  7910653     Medline TA:  Am J Epidemiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  66-73     Citation Subset:  IM    
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MeSH Terms
Data Interpretation, Statistical*
Dose-Response Relationship, Drug*
Linear Models*
Meta-Analysis as Topic*
Nonlinear Dynamics*
Grant Support
P01 CA-055075/CA/NCI NIH HHS; P30 CA-06516/CA/NCI NIH HHS; P30 CA006516/CA/NCI NIH HHS

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