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      False-Positive Results in Cancer Epidemiology: A Plea for Epistemological Modesty

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          Abstract

          False-positive results are inherent in the scientific process of testing hypotheses concerning the determinants of cancer and other human illnesses. Although much of what is known about the etiology of human cancers has arisen from well-conducted epidemiological studies, epidemiology has been increasingly criticized for producing findings that are often sensationalized in the media and fail to be upheld in subsequent studies. Herein we describe examples from cancer epidemiology of likely false-positive findings and discuss conditions under which such results may occur. We suggest general guidelines or principles, including the endorsement of editorial policies requiring the prominent listing of study caveats, which may help reduce the reporting of misleading results. Increased epistemological humility regarding findings in epidemiology would go a long way to diminishing the detrimental effects of false-positive results on the allocation of limited research resources, on the advancement of knowledge of the causes and prevention of cancer, and on the scientific reputation of epidemiology and would help to prevent oversimplified interpretations of results by the media and the public.

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          Most cited references68

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study.

            Measurement error in explanatory variables and unmeasured confounders can cause considerable problems in epidemiologic studies. It is well recognized that under certain conditions, nondifferential measurement error in the exposure variable produces bias towards the null. Measurement error in confounders will lead to residual confounding, but this is not a straightforward issue, and it is not clear in which direction the bias will point. Unmeasured confounders further complicate matters. There has been discussion about the amount of bias in exposure effect estimates that can plausibly occur due to residual or unmeasured confounding. In this paper, the authors use simulation studies and logistic regression analyses to investigate the size of the apparent exposure-outcome association that can occur when in truth the exposure has no causal effect on the outcome. The authors consider two cases with a normally distributed exposure and either two or four normally distributed confounders. When the confounders are uncorrelated, bias in the exposure effect estimate increases as the amount of residual and unmeasured confounding increases. Patterns are more complex for correlated confounders. With plausible assumptions, effect sizes of the magnitude frequently reported in observational epidemiologic studies can be generated by residual and/or unmeasured confounding alone.
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              Quantitative trait Loci analysis using the false discovery rate.

              False discovery rate control has become an essential tool in any study that has a very large multiplicity problem. False discovery rate-controlling procedures have also been found to be very effective in QTL analysis, ensuring reproducible results with few falsely discovered linkages and offering increased power to discover QTL, although their acceptance has been slower than in microarray analysis, for example. The reason is partly because the methodological aspects of applying the false discovery rate to QTL mapping are not well developed. Our aim in this work is to lay a solid foundation for the use of the false discovery rate in QTL mapping. We review the false discovery rate criterion, the appropriate interpretation of the FDR, and alternative formulations of the FDR that appeared in the statistical and genetics literature. We discuss important features of the FDR approach, some stemming from new developments in FDR theory and methodology, which deem it especially useful in linkage analysis. We review false discovery rate-controlling procedures--the BH, the resampling procedure, and the adaptive two-stage procedure-and discuss the validity of these procedures in single- and multiple-trait QTL mapping. Finally we argue that the control of the false discovery rate has an important role in suggesting, indicating the significance of, and confirming QTL and present guidelines for its use.
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                Author and article information

                Journal
                J Natl Cancer Inst
                jnci
                jnci
                JNCI Journal of the National Cancer Institute
                Oxford University Press
                0027-8874
                1460-2105
                16 July 2008
                16 July 2008
                16 July 2008
                16 July 2008
                : 100
                : 14
                : 988-995
                Affiliations
                Affiliations of authors: Lifestyle, Environment and Cancer Group, International Agency for Research on Cancer, Lyon, France (PB); International Epidemiology Institute, Rockville, MD (JKM, RET, LL, WJB); Vanderbilt University Medical Center, Vanderbilt-Ingram Cancer Center, Nashville, TN (JKM, RET, LL, WJB); Laboratory of Epidemiology, Mario Negri Institute, Milan, Italy (CLV); Institute of Medical Statistics and Biometry, University of Milan, Milan, Italy (CLV)
                Author notes
                Correspondence to: Paolo Boffetta, MD, PhD, Lifestyle, Environment and Cancer Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France (e-mail: boffetta@ 123456iarc.fr ).
                Article
                10.1093/jnci/djn191
                2467434
                18612135
                fd7da9d7-489d-4d66-b3db-d189e028c571
                © 2008 The Author(s).

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 3 March 2008
                : 24 April 2008
                : 16 May 2008
                Categories
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                Oncology & Radiotherapy
                Oncology & Radiotherapy

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