Altmetric

Size matters: just how big is BIG? Quantifying realistic sample size requirements for human genome epidemiology

Title: Size matters: just how big is BIG? Quantifying realistic sample size requirements for human genome epidemiology
Authors: Burton, PR
Hansell, AL
Fortier, I
Manolio, TA
Khoury, MJ
Little, J
Elliott, P
Item Type: Journal Article
Abstract: Background Despite earlier doubts, a string of recent successes indicates that if sample sizes are large enough, it is possible—both in theory and in practice—to identify and replicate genetic associations with common complex diseases. But human genome epidemiology is expensive and, from a strategic perspective, it is still unclear what ‘large enough’ really means. This question has critical implications for governments, funding agencies, bioscientists and the tax-paying public. Difficult strategic decisions with imposing price tags and important opportunity costs must be taken. Methods Conventional power calculations for case–control studies disregard many basic elements of analytic complexity—e.g. errors in clinical assessment, and the impact of unmeasured aetiological determinants—and can seriously underestimate true sample size requirements. This article describes, and applies, a rigorous simulation-based approach to power calculation that deals more comprehensively with analytic complexity and has been implemented on the web as ESPRESSO: (www.p3gobservatory.org/powercalculator.htm). Results Using this approach, the article explores the realistic power profile of stand-alone and nested case–control studies in a variety of settings and provides a robust quantitative foundation for determining the required sample size both of individual biobanks and of large disease-based consortia. Despite universal acknowledgment of the importance of large sample sizes, our results suggest that contemporary initiatives are still, at best, at the lower end of the range of desirable sample size. Insufficient power remains particularly problematic for studies exploring gene–gene or gene–environment interactions. Discussion Sample size calculation must be both accurate and realistic, and we must continue to strengthen national and international cooperation in the design, conduct, harmonization and integration of studies in human genome epidemiology.
Issue Date: 1-Aug-2008
Date of Acceptance: 8-Jun-2008
URI: http://hdl.handle.net/10044/1/52108
DOI: https://dx.doi.org/10.1093/ije/dyn147
ISSN: 1464-3685
Publisher: Oxford University Press (OUP)
Start Page: 263
End Page: 273
Journal / Book Title: International Journal of Epidemiology
Volume: 38
Issue: 1
Copyright Statement: The Author 2008; all rights reserved. The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org.
Keywords: Science & Technology
Life Sciences & Biomedicine
Public, Environmental & Occupational Health
PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH, SCI
Human genome epidemiology
biobank
sample size
statistical power
simulation studies
measurement error
reliability
aetiological heterogeneity
GENE-DISEASE ASSOCIATIONS
FACTOR-H POLYMORPHISM
WIDE ASSOCIATION
MENDELIAN RANDOMIZATION
MACULAR DEGENERATION
COMPLEX DISEASES
COMMON DISEASES
SUSCEPTIBILITY LOCI
COLORECTAL-CANCER
PROSTATE-CANCER
Adult
Aged
Biological Specimen Banks
Case-Control Studies
Chronic Disease
Disease
Female
Genetic Predisposition to Disease
Genomics
Humans
Life Style
Male
Middle Aged
Research Design
Sample Size
0104 Statistics
1117 Public Health And Health Services
Epidemiology
Publication Status: Published
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons