© 2005 Oxford University Press
ARTICLE |
Selective Reporting Biases in Cancer Prognostic Factor Studies
Affiliations of authors: Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece (PAK, KTL, JPAI); Biomedical Research Institute, Foundation for Research and TechnologyHellas, Ioannina, Greece (JPAI); Institute for Clinical Research and Health Policy Studies, Department of Medicine, TuftsNew England Medical Center, Boston, MA (JPAI)
Correspondence to: John P. A. Ioannidis, MD, Chairman, Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina 45110, Greece (e-mail: jioannid{at}cc.uoi.gr).
Background: Nonreported and selectively reported information and the use of different definitions may introduce biases in the literature of prognostic factors. We probed these biases in a meta-analysis of a prognostic factor for head and neck squamous cell cancer (HNSCC) mortality that has drawn wide attentionthe status of the tumor suppressor protein TP53. Methods: We compared results of meta-analyses that included published data plus unpublished data retrieved from investigators; published data; and only published data indexed with "survival" or "mortality" in MEDLINE/EMBASE, with or without standardized definitions. We also evaluated whether previously published meta-analyses on mortality predictors for various malignancies addressed issues of retrieval and standardized information. All statistical tests were two-sided. Results: For the 18 studies with 1364 patients that included published and indexed data, we obtained a highly statistically significant association between TP53 status and mortality. When we used the definitions preferred by each publication, the association was stronger (risk ratio [RR] = 1.38, 95% confidence interval [CI] = 1.13 to 1.67; P = .001) than when we standardized definitions (RR = 1.27, 95% CI = 1.06 to 1.53; P = .011). The addition of 13 studies with 1028 subjects that included published but not indexed data reduced the observed association (RR = 1.23, 95% CI = 1.03 to 1.47; P = .02). Finally, when we obtained data from investigators (11 studies with 996 patients) and analyzed it with all other data, statistical significance was lost (RR = 1.16, 95% CI = 0.99 to 1.35; P = .06). Among 18 published meta-analyses of 37 cancer prognostic factors, 13 (72%) did not use standardized definitions and 16 (89%) did not retrieve additional information. Conclusions: Selective reporting may spuriously inflate the importance of postulated prognostic factors for various malignancies. We recommend that meta-analyses thereof should maximize retrieval of information and standardize definitions.
Editorial about this Article
- Identification of Clinically Useful Cancer Prognostic Factors: What Are We Missing?
- Lisa M. McShane, Douglas G. Altman, and Willi Sauerbrei
J Natl Cancer Inst 2005 97: 1023-1025.[Extract] [Full Text] [PDF]
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