Skip to main content

Table 3 SLNB reduction rates using the ANN model to predict disease-free axilla. Possible SLNB reduction rate corresponding to cut-offs at maximum negative predictive value, false negative rate 5 and 10%, respectively

From: Artificial neural network models to predict nodal status in clinically node-negative breast cancer

  N0 vs. N+ n = 800
Cut-off Max NPV 0.95 TP TN FP FN
No. 283 57 457 3
SLNB Reduction Rate (TN + FN) / (TP + TN + FP + FN) = 7.50%
False Negative Rate FN / (TP + FN) = 1.05%
Cut-off
NPV 0.90
TP TN FP FN
No. 272 128 386 14
SLNB Reduction Rate (TN + FN) / (TP + TN + FP + FN) = 17.75%
False Negative Rate FN / (TP + FN) = 5%
Cut-off
NPV 0.87
TP TN FP FN
No. 258 190 324 28
SLNB Reduction Rate (TN + FN) / (TP + TN + FP + FN) = 27.25%
False Negative Rate FN / (TP + FN) = 10%
  1. Abbreviations: N0 Lymph node negative, N+ Any lymph node metastasis, SLNB Sentinel lymph node biopsy, Max NPV Maximum negative predictive value, TP True positive, TN True negative, FP False positive, FN False negative
\