Overinterpretation and misreporting of prognostic factor studies in oncology: a systematic review

E. Kempf, J.A. de Beyer, J. Cook, J. Holmes, S. Mohammed, T.-L. Nguyên, I. Simera, M. Trivella, D.G. Altman, S. Hopewell, K.G.M. Moons, R. Porcher, J.B. Reitsma, W. Sauerbrei, G.S. Collins

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Cancer prognostic biomarkers have shown disappointing clinical applicability. The objective of this study was to classify and estimate how study results are overinterpreted and misreported in prognostic factor studies in oncology.

This systematic review focused on 17 oncology journals with an impact factor above 7. PubMed was searched for primary clinical studies published in 2015, evaluating prognostic factors. We developed a classification system, focusing on three domains: misleading reporting (selective, incomplete reporting, misreporting), misleading interpretation (unreliable statistical analysis, spin) and misleading extrapolation of the results (claiming irrelevant clinical applicability, ignoring uncertainty).

Our search identified 10,844 articles. The 98 studies included investigated a median of two prognostic factors (Q1–Q3, 1–7). The prognostic factors’ effects were selectively and incompletely reported in 35/98 and 24/98 full texts, respectively. Twenty-nine articles used linguistic spin in the form of strong statements. Linguistic spin rejecting non-significant results was found in 34 full-text results and 15 abstract results sections. One in five articles had discussion and/or abstract conclusions that were inconsistent with the study findings. Sixteen reports had discrepancies between their full-text and abstract conclusions.

Our study provides evidence of frequent overinterpretation of findings of prognostic factor assessment in high-impact medical oncology journals.
Original languageEnglish
Pages (from-to)1288-1296
Number of pages9
JournalBritish Journal of Cancer
Early online date24 Oct 2018
Publication statusPublished - 13 Nov 2018
Externally publishedYes

Bibliographical note

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  • Prognostic markers
  • Tumour biomarkers


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