More Accurate Oral Cancer Screening with Fewer Salivary Biomarkers

Biomarkers in Cancer
James Michael MenkeSuan Phaik Khoo

Abstract

Signal detection and Bayesian inferential tools were applied to salivary biomarkers to improve screening accuracy and efficiency in detecting oral squamous cell carcinoma (OSCC). Potential cancer biomarkers are identified by significant differences in assay concentrations, receiver operating characteristic areas under the curve (AUCs), sensitivity, and specificity. However, the end goal is to report to individual patients their risk of having disease given positive or negative test results. Likelihood ratios (LRs) and Bayes factors (BFs) estimate evidential support and compile biomarker information to optimize screening accuracy. In total, 26 of 77 biomarkers were mentioned as having been tested at least twice in 137 studies and published in 16 summary papers through 2014. Studies represented 10 212 OSCC and 25 645 healthy patients. The measure of biomarker and panel information value was number of biomarkers needed to approximate 100% positive predictive value (PPV). As few as 5 biomarkers could achieve nearly 100% PPV for a disease prevalence of 0.2% when biomarkers were ordered from highest to lowest LR. When sequentially interpreting biomarker tests, high specificity was more important than test sensitivity in achieving rap...Continue Reading

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Citations

Apr 3, 2020·Oral Diseases·Carlos Antonio Schaffer PenteadoLuciana Reis Azevedo-Alanis
Jul 21, 2020·Head & Neck·Fiona T DeutschNham T Tran

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Methods Mentioned

BETA
biopsy
ESR

Software Mentioned

DiSc
R language
R
mada
Meta

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