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Sökning: WFRF:(Khudyakov Polyna) > (2012) > Meta-Analysis for L...

Meta-Analysis for Linear and Nonlinear Dose-Response Relations : Examples, an Evaluation of Approximations, and Software

Orsini, Nicola (författare)
Karolinska Institutet
Li, Ruifeng (författare)
Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA.
Wolk, Alicja (författare)
Karolinska Institutet
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Khudyakov, Polyna (författare)
Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA.;Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA.
Spiegelman, Donna (författare)
Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA.;Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA.
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Karolinska Institutet Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA (creator_code:org_t)
2011-12-01
2012
Engelska.
Ingår i: American Journal of Epidemiology. - : OXFORD UNIV PRESS INC. - 0002-9262 .- 1476-6256. ; 175:1, s. 66-73
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)

Nyckelord

cohort studies
data interpretation
statistical
dose-response relationship
drug
linear models
meta-analysis
meta-analysis as topic

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