Literature DB >> 9149663

Comparison of effect estimates from a meta-analysis of summary data from published studies and from a meta-analysis using individual patient data for ovarian cancer studies.

K K Steinberg1, S J Smith, D F Stroup, I Olkin, N C Lee, G D Williamson, S B Thacker.   

Abstract

To determine the relative merits of two quantitative methods used to estimate the summary effects of observational studies, the authors compared two methods of meta-analysis. Each quantified the relation between oral contraceptive use and the risk for ovarian cancer. One analysis consisted of a meta-analysis using summary data from 11 published studies from the literature (MAL) in which the study was the unit of analysis, and the second consisted of a meta-analysis using individual patient data (MAP) in which the patient was the unit of analysis. The authors found excellent quantitative agreement between the summary effect estimates from the MAL and the MAP. The MAP permits analysis 1) among outcomes, exposures, and confounders not investigated in the original studies, 2) when the original effect measures differ among studies and cannot be converted to a common measure (e.g., slopes vs. correlation coefficients), and 3) when there is a paucity of studies. The MAL permits analysis 1) when resources are limited, 2) when time is limited, and 3) when original study data are not available or are available only from a biased sample of studies. In public health epidemiology, data from original studies are often accessible only to limited numbers of research groups and for only a few types of studies that have high public health priority. Consequently, few opportunities for pooled analysis exist. However, from a policy view, MAL will provide answers to many questions and will help in identifying questions for future investigation.

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Year:  1997        PMID: 9149663     DOI: 10.1093/oxfordjournals.aje.a009051

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  32 in total

1.  Comparing meta-analysis and ecological-longitudinal analysis in time-series studies. A case study of the effects of air pollution on mortality in three Spanish cities.

Authors:  M Saez; A Figueiras; F Ballester; S Pérez-Hoyos; R Ocaña; A Tobías
Journal:  J Epidemiol Community Health       Date:  2001-06       Impact factor: 3.710

2.  Reduced-function CYP2C19 genotype and risk of adverse clinical outcomes among patients treated with clopidogrel predominantly for PCI: a meta-analysis.

Authors:  Jessica L Mega; Tabassome Simon; Jean-Philippe Collet; Jeffrey L Anderson; Elliott M Antman; Kevin Bliden; Christopher P Cannon; Nicolas Danchin; Betti Giusti; Paul Gurbel; Benjamin D Horne; Jean-Sebastian Hulot; Adnan Kastrati; Gilles Montalescot; Franz-Josef Neumann; Lei Shen; Dirk Sibbing; P Gabriel Steg; Dietmar Trenk; Stephen D Wiviott; Marc S Sabatine
Journal:  JAMA       Date:  2010-10-27       Impact factor: 56.272

3.  Mammographic density, MRI background parenchymal enhancement and breast cancer risk.

Authors:  M C Pike; C L Pearce
Journal:  Ann Oncol       Date:  2013-11       Impact factor: 32.976

Review 4.  Addressing multimorbidity in evidence integration and synthesis.

Authors:  Thomas A Trikalinos; Jodi B Segal; Cynthia M Boyd
Journal:  J Gen Intern Med       Date:  2014-01-18       Impact factor: 5.128

5.  Collaborative, pooled and harmonized study designs for epidemiologic research: challenges and opportunities.

Authors:  Catherine R Lesko; Lisa P Jacobson; Keri N Althoff; Alison G Abraham; Stephen J Gange; Richard D Moore; Sharada Modur; Bryan Lau
Journal:  Int J Epidemiol       Date:  2018-04-01       Impact factor: 7.196

6.  Efficacy and safety of 1,000 mg effervescent aspirin: individual patient data meta-analysis of three trials in migraine headache and migraine accompanying symptoms.

Authors:  Christian Lampl; M Voelker; H C Diener
Journal:  J Neurol       Date:  2007-04-10       Impact factor: 4.849

7.  An empirical comparison of meta-analysis and mega-analysis of individual participant data for identifying gene-environment interactions.

Authors:  Yun Ju Sung; Karen Schwander; Donna K Arnett; Sharon L R Kardia; Tuomo Rankinen; Claude Bouchard; Eric Boerwinkle; Steven C Hunt; Dabeeru C Rao
Journal:  Genet Epidemiol       Date:  2014-04-09       Impact factor: 2.135

8.  The implications of Big Five standing for the distribution of trait manifestation in behavior: fifteen experience-sampling studies and a meta-analysis.

Authors:  William Fleeson; Patrick Gallagher
Journal:  J Pers Soc Psychol       Date:  2009-12

Review 9.  Antidepressant drug effects and depression severity: a patient-level meta-analysis.

Authors:  Jay C Fournier; Robert J DeRubeis; Steven D Hollon; Sona Dimidjian; Jay D Amsterdam; Richard C Shelton; Jan Fawcett
Journal:  JAMA       Date:  2010-01-06       Impact factor: 56.272

10.  On meta- and mega-analyses for gene-environment interactions.

Authors:  Jing Huang; Yulun Liu; Steve Vitale; Trevor M Penning; Alexander S Whitehead; Ian A Blair; Anil Vachani; Margie L Clapper; Joshua E Muscat; Philip Lazarus; Paul Scheet; Jason H Moore; Yong Chen
Journal:  Genet Epidemiol       Date:  2017-11-07       Impact factor: 2.135

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