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Older studies can underestimate prognosis of glioblastoma biomarker in meta-analyses: a meta-epidemiological study for study-level effect in the current literature

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Abstract

Introduction

There are many potential biomarkers in glioblastoma (GBM), and meta-analyses represent the highest level of evidence when inferring their prognostic significance. It is possible however, that inherent design properties of the studies included in these meta-analyses may affect the pooled hazard ratio (HR) of the meta-analyses. This meta-epidemiological study aims to investigate the potential bias of three study-level properties in meta-analyses of GBM biomarkers currently published in the literature.

Methods

Seven electronic databases from inception to December 2017 were searched for meta-analyses evaluating different GBM biomarkers, which were screened against specific criteria. Study-level data were extracted from each meta-analysis, and analyzed using logistic regression to yield the ratio of HR (RHR) summary statistic.

Results

Nine meta-analyses investigating different GBM biomarkers were included. Of all the meta-analyses, the HRs of two studies were significantly underestimated by older studies; they investigated biomarkers IDH1 (RHR = 1.145; p = 0.017) and CD133 (RHR = 0.850; p = 0.013). Study-level size and design showed non-significant trends towards affecting the overall HR in all included meta-analyses.

Conclusions

This meta-epidemiological study demonstrated that study-level year can already significantly affect the pooled HR of GBM biomarkers reported by meta-analyses. It is possible that in the future, more study-level properties will exert significant effect. In terms of future GBM biomarker meta-analyses, special consideration of bias should be given to these study-level properties as potential sources of effect on the prognostic pooled HR.

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Authors and Affiliations

  1. Cure Brain Cancer Neuro-oncology Laboratory, Prince of Wales Clinical School, Lowy Cancer Research Centre, University of New South Wales, Sydney, Australia

    Victor M. Lu, Julia X. M. Yin & Kerrie L. McDonald

  2. Prince of Wales Clinical School, University of New South Wales, Randwick, Sydney, NSW, 2031, Australia

    Victor M. Lu, Kevin Phan & Kerrie L. McDonald

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  1. Victor M. Lu
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  2. Kevin Phan
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Correspondence to Victor M. Lu.

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Lu, V.M., Phan, K., Yin, J.X.M. et al. Older studies can underestimate prognosis of glioblastoma biomarker in meta-analyses: a meta-epidemiological study for study-level effect in the current literature. J Neurooncol 139, 231–238 (2018). https://doi.org/10.1007/s11060-018-2897-2

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