Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/3684
Title: | Application of credibility ceilings probes the robustness of meta-Analyses of biomarkers and cancer risk | Authors: | Papatheodorou, Stefania Tsilidis, Konstantinos K. Ioannidis, John P. A. Evangelou, Evangelos |
Major Field of Science: | Medical and Health Sciences | Field Category: | Clinical Medicine | Keywords: | Biomarkers;Cancer;Credibility ceiling;Meta-Analyses;Predictive intervals | Issue Date: | 1-Feb-2015 | Source: | Journal of Clinical Epidemiology, 2015, vol. 68, no. 2, pp. 163-174 | Volume: | 68 | Issue: | 2 | Start page: | 163 | End page: | 174 | Journal: | Journal of Clinical Epidemiology | Abstract: | Objectives Meta-Analyses of biomarkers often present spurious significant results and large effects. We applied sensitivity analyses with the use of credibility ceilings to assess whether and how the results of meta-Analyses of biomarkers and cancer risk would change. Study Design and Setting We evaluated 98 meta-Analyses, 43 (44%) of which had nominally statistically significant results. We assumed that any single study cannot give more than a maximum certainty 100 - c% (c, credibility ceiling) that the effect estimate [odds ratio (OR)] exceeds 1 (null) or 1.2. Results Nominal statistical significance was maintained for 21 (21%) meta-Analyses, for c = 10% and OR >1, and these proportions changed to 7%, 3%, and 6% with ceilings of 20%, 30%, and 40%, respectively. For ceilings for OR >1.2, the respective proportions were 37%, 21%, 7%, and 3%. Seven meta-Analyses on infectious agents retained statistical significance even with a high ceiling of c = 20% for OR >1.00. Meta-Analyses without other hints of bias (large between-study heterogeneity, small-study effects, excess significance) were more likely to retain statistical significance than those that had such hints of bias. Conclusion Credibility ceilings may be helpful in meta-Analyses of biomarkers to understand the robustness of the results to different levels of uncertainty. | URI: | https://hdl.handle.net/20.500.14279/3684 | ISSN: | 08954356 | DOI: | http://dx.doi.org/10.1016/j.jclinepi.2014.09.004 | Rights: | © Elsevier | Type: | Article | Affiliation : | Cyprus University of Technology University of Ioannina Stanford University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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