Assessing the probability that a positive report is false: An approach for molecular epidemiology studies

Sholom Wacholder, Stephen Chanock, Montserrat Garcia-Closas, Laure El Ghormli, Nathaniel Rothman

Research output: Contribution to journalArticlepeer-review

Abstract

Too many reports of associations between genetic variants and common cancer sites and other complex diseases are false positives. A major reason for this unfortunate situation is the strategy of declaring statistical significance based on a P value alone, particularly, any P value below .05. The false positive report probability (FPRP), the probability of no true association between a genetic variant and disease given a statistically significant finding, depends not only on the observed P value but also on both the prior probability that the association between the genetic variant and the disease is real and the statistical power of the test. In this commentary, we show how to assess the FPRP and how to use it to decide whether a finding is deserving of attention or "noteworthy." We show how this approach can lead to improvements in the design, analysis, and interpretation of molecular epidemiology studies. Our proposal can help investigators, editors, and readers of research articles to protect themselves from overinterpreting statistically significant findings that are not likely to signify a true association. An FPRP-based criterion for deciding whether to call a finding noteworthy formalizes the process already used informally by investigators - that is, tempering enthusiasm for remarkable study findings with considerations of plausibility.

Original languageEnglish (US)
Pages (from-to)434-442
Number of pages9
JournalJournal of the National Cancer Institute
Volume96
Issue number6
DOIs
StatePublished - Mar 17 2004

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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