American Association for Cancer Research
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10559965epi141227-sup-140235_2_supp_2894792_nl2120.pptx (213.57 kB)

Supplementary Figure S4 from Improving the Quality of Biomarker Discovery Research: The Right Samples and Enough of Them

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posted on 2023-03-31, 13:40 authored by Margaret S. Pepe, Christopher I. Li, Ziding Feng

Supplementary Figure S4. ROC curves for the combination of TP53 and CTAGIA in independent samples.

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ARTICLE ABSTRACT

Background: Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs.Methods: The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE).Results: We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions.Conclusions: Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified.Impact: The scientific rigor of discovery research should be improved. Cancer Epidemiol Biomarkers Prev; 24(6); 944–50. ©2015 AACR.

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    Cancer Epidemiology, Biomarkers & Prevention

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