Almost all articles on cancer prognostic markers report statistically significant results.
We aimed to understand the extent of the pursuit for statistically significant results in the prognostic literature of cancer. We evaluated 340 articles included in prognostic marker meta-analyses (Database 1) and 1575 articles on cancer prognostic markers published in 2005 (Database 2). For each article, we examined whether the abstract reported any statistically significant prognostic effect for any marker and any outcome ('positive' articles). 'Negative' articles were further examined for statements made by the investigators to overcome the absence of prognostic statistical significance. We also examined how the articles of Database 1 had presented the relative risks that were included in the respective meta-analyses. 'Positive' prognostic articles comprised 90.6% and 95.8% in Databases 1 and 2, respectively. Most of the 'negative' prognostic articles claimed significance for other analyses, expanded on non-significant trends or offered apologies that were occasionally remote from the original study aims. Only five articles in Database 1 (1.5%) and 21 in Database 2 (1.3%) were fully 'negative' for all presented results in the abstract and without efforts to expand on non-significant trends or to defend the importance of the marker with other arguments. Of the statistically non-significant relative risks in the meta-analyses, 25% had been presented as statistically significant in the primary papers using different analyses compared with the respective meta-analysis. We conclude that almost all articles on cancer prognostic marker studies highlight some statistically significant results. Under strong reporting bias, statistical significance loses its discriminating ability for the importance of prognostic markers.
Kyzas
Panayiotis A
PA
Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
Denaxa-Kyza
Despina
D
Ioannidis
John P A
JP
D014408:Biomarkers, Tumor / Q000378:metabolism; D006801:Humans; D018156:Journalism, Medical / Q000592:standards*; D009369:Neoplasms / Q000401:mortality*; D010506:Periodicals as Topic / Q000592:standards*; D011379:Prognosis; D017594:Publication Bias; D012307:Risk Factors
D014408:Biomarkers, Tumor