Koos Boeve

155 Methylation biomarkers for the detection of tumor DNA in saliva Table 3. OSCC diagnostic potential in saliva of the selected methylation markers Gene name A. OSCC patients (n = 10) vs all controls (n = 10) B. OSCC patients (n = 10) vs age-matched controls (n = 5) AUC Optimal cut-off Sensitivity (%) Specificity (%) PPV (%) NPV (%) AUC Optimal cut-off Sensitivity (%) Specificity (%) PPV (%) NPV (%) C11orf85 0.56 559 50 80 71 62 0.44 533 50 60 71 38 EDNRB 0.82 38 100 60 71 100 0.68 22 100 40 77 100 HOXA9 0.44 479 40 90 80 60 0.39 479 40 80 80 40 KCNA5 0.99 5 100 80 83 100 0.98 10 90 100 100 83 NID2 0.72 27 80 60 67 75 0.66 38 70 80 88 57 SIPA1 0.40 5239 20 90 67 53 0.32 5239 30 80 75 36 TIMP3 0.57 34 30 90 75 56 0.65 25 30 100 100 42 A ROC analysis of methylation in saliva between 10 OSCC patients and 10 control patients (A) and an age-matched analysis of saliva between 10 OSCC patients and five dental implant control patients (B) for the optimal cut-off points to detect OSCC in saliva. KCNA5 combined with TIMP3 could detect OSCC with a 100% sensitivity, specificity, PPV and NPV in an age-matched analysis . Abbreviations: AUC, area under the curve; PPV, positive predictive value; negative predictive value; OSCC, oral squamous cell carcinoma.