Table 3 The performance of various models for segregating ATB from LTBI in validation cohort
Parameters | Validation set (n = 263, 125 ATB, 138 LTBI) | |||||||
|---|---|---|---|---|---|---|---|---|
cforest | bart | gamboost | gbm | glmnet | lda | log_reg | svm | |
AUC (95% CI) | 0.963 (0.940–0.986) | 0.956 (0.932–0.981) | 0.947 (0.919–0.975) | 0.958 (0.935–0.981) | 0.913 (0.876–0.950) | 0.884 (0.841–0.927) | 0.910 (0.872–0.949) | 0.929 (0.896–0.962) |
Sensitivity (95% CI) | 92.80% (86.88–96.17%) | 85.60% (78.38–90.69%) | 82.40% (74.79–88.08%) | 89.60% (83.02–93.82%) | 78.40% (70.40–84.71%) | 69.60% (61.05–76.98%) | 80.80% (73.02–86.74%) | 82.40% (74.79–88.08%) |
Specificity (95% CI) | 89.86% (83.69–93.86%) | 92.03% (86.29–95.49%) | 92.03% (86.29–95.49%) | 89.86% (83.69–93.86%) | 93.48% (88.07–96.53%) | 94.93% (89.90–97.52%) | 92.75% (87.18–96.02%) | 93.48% (88.07–96.53%) |
PPV (95% CI) | 89.23% (82.73–93.48%) | 90.68% (84.08–94.72%) | 90.35% (83.55–94.53%) | 88.89% (82.21–93.27%) | 91.59% (84.78–95.51%) | 92.55% (85.42–96.35%) | 90.99% (84.21–95.03%) | 91.96% (85.43–95.72%) |
NPV (95% CI) | 93.23% (87.64–96.40%) | 87.59% (81.23–92.00%) | 85.23% (78.66–90.04%) | 90.51% (84.44–94.37%) | 82.69% (75.99–87.82%) | 77.51% (70.65–83.16%) | 84.21% (77.58–89.15%) | 85.43% (78.93–90.18%) |
PLR (95% CI) | 9.15 (5.55–15.07) | 10.74 (6.06–19.02) | 10.34 (5.83–18.33) | 8.83 (5.36–14.56) | 12.02 (6.35–22.76) | 13.72 (6.61–28.50) | 11.15 (6.10–20.38) | 12.63 (6.68–23.89) |
NLR (95% CI) | 0.08 (0.04–0.15) | 0.16 (0.10–0.24) | 0.19 (0.13–0.28) | 0.12 (0.07–0.19) | 0.23 (0.16–0.32) | 0.32 (0.24–0.42) | 0.21 (0.14–0.30) | 0.19 (0.13–0.28) |
Accuracy (95% CI) | 91.25% (87.22–94.10%) | 88.97% (84.61–92.21%) | 87.45% (82.90–90.92%) | 89.73% (85.48–92.85%) | 86.31% (81.63–89.95%) | 82.89% (77.87–86.96%) | 87.07% (82.48–90.60%) | 88.21% (83.76–91.57%) |