Table 4.
Defined Approach (DA) performance in predicting LLNA hazard (sensitizer/non-sensitizer).
| Predicting LLNA Hazard | |||||||
|---|---|---|---|---|---|---|---|
| Defined Approach: |
BASF 2/3 (DKH) |
Kao STS | Kao ITS |
ICCVAM SVM (LLNA) |
Shiseido ANN (D_hC) |
Shiseido ANN (D_hC_KS) |
P&G BN ITS-3 |
| N | 127 | 126 | 120 | 120 | 126 | 126 | 119 |
| Accuracy (%)* | 70.1 | 77.8 | 79.2 | 88.3 | 76.2 | 81.0 | 83.2 |
| Sensitivity (%) | 72.3 | 92.6 | 85.6 | 93.3 | 90.4 | 97.9 | 83.2 |
| Specificity (%) | 63.6 | 34.4 | 60.0 | 73.3 | 34.4 | 31.3 | 83.3 |
| BA (%) | 68.0 | 63.5 | 72.8 | 83.3 | 62.4 | 64.6 | 83.3 |
*
Performance is shown against the maximum subset (N) out of 128 substances with all necessary DA features. Abbreviations: LLNA: local lymph node assay, BA: Balanced Accuracy, STS: sequential testing strategy, ITS: integrated testing strategy, SVM: support vector machine, ANN: artificial neural network, BN: Bayesian network, DKH and D_hC_KS: DPRA/hCLAT/KeratinoSens™, D_hC: DPRA/hCLAT