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Table 1 ROC analysis for each marker individually

From: A molecular computational model improves the preoperative diagnosis of thyroid nodules

  Sensitivity Specificity AUCa SEb Thresholds Value 95% CIc
KIT* 79.6 86.8 0,900 0.0313 ≤ 0.105 0.817-0.954
CDH1* 61.2 73.7 0.700 0.0586 ≤ 0.11 0.559-0.766
NATH 57.8 57.9 0.553 0.0658 ≤ 0.112 0.440-0.662
LSM7* 69.4 57.9 0.625 0.0633 ≤ 0.11 0.515-0.727
C21orf4* 58.3 73.7 0.644 0.0607 ≤ 0.0001 0.533-0.744
DDI2* 56.2 86.8 0.729 0.0551 ≤ 0.0026 0.622-0.819
SYNGR2 47.9 78.9 0.608 0.0613 ≤ 0.04 0.497-0.712
TC1 85.0 38.2 0.581 0.0679 > 0.006 0.460-0.695
Hs.296031 77.8 32.4 0.490 0.0671 ≤ 0.0051 0.375-0.605
  1. aAUC (area under the curve).
  2. bSE (standard error).
  3. cCI (confidence interval).
  4. *p < 0.05.