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. Author manuscript; available in PMC: 2017 May 1.
Published in final edited form as: Cancer Lett. 2017 Feb 20;393:86–93. doi: 10.1016/j.canlet.2017.02.019

Table 7.

ROC curves performance characteristics normal v. PDAC.

miRNA Sensitivity Specificity Cutoff AUC p-value
Exosomes
miR-10b 100% 100% >4.94 1.00 p < 0.001
miR-21 100% 100% >1.38 1.00 p < 0.001
miR-30c 100% 100% >2.14 1.00 p < 0.001
miR-106b 62% 100% >1.84 0.85 p = 0.007
miR-20a 83% 100% >1.73 0.95 p < 0.001
miR-181a 100% 100% >1.32 1.00 p < 0.001
miR-483 31% 100% >2.57 0.57 p = 0.599
miR-let7a 100% 100% <0.72 1.00 p < 0.001
miR-122 93% 100% <0.71 0.99 p < 0.001
Plasma
miR-10b 100% 100% >3.05 1.00 p < 0.001
miR-21 86% 100% >1.68 0.95 p < 0.001
miR-30c 100% 100% >1.40 1.00 p < 0.001
miR-106b 97% 100% >1.14 0.98 p < 0.001
miR-20a 93% 100% >2.46 0.99 p < 0.001
miR-181a 97% 100% >1.25 0.97 p < 0.001
miR-483 66% 67% >1.49 0.67 p = 0.20
miR-let7a 93% 100% <0.86 0.99 p < 0.001
miR-122 100% 67% <0.94 0.89 p = 0.003

Receiver operating characteristic (ROC) curves were generated with the SigmaPlot 13.0 ROC Curves macro tool, based on the levels of indicated miRs in exosomes or plasma.