Table 2.
Summary of pooled rates
| Pooled rate (95% CI) | I2% heterogeneity (95% PI) | |
|---|---|---|
| Accuracy | ||
| Overall | 86% (82.8-88.6) 10 datasets |
57% (71-94) |
| EUS-images | 91.8% (82.3-96.4) 5 datasets |
78% (52-99) |
| EUS-elastography | 85.4% (82-88.2) 5 datasets |
0% (79-89) |
| Neural network algorithm | 85.5% (80-89.8) 5 datasets |
69% (61-97) |
| Sensitivity | ||
| Overall | 90.4% (88.1-92.3) 13 datasets |
39% (83-96) |
| EUS-images | 93.4% (88.9-96.1) 7 datasets |
60% (78-98) |
| EUS-elastography | 88.9% (85.8-91.4) 5 datasets |
0% (84-93) |
| Neural network algorithm | 91.8% (87.8-94.6) 8 datasets |
45% (84-97) |
| Specificity | ||
| Overall | 84% (79.3-87.8) 13 datasets |
88% (51-97) |
| EUS-images | 89.8% (76.3-96) 7 datasets |
92% (35-99) |
| EUS-elastography | 79.9% (73.5-85.1) 5 datasets |
61% (55-93) |
| Neural network algorithm | 84.6% (73-91.7) 8 datasets |
90% (39-97) |
| PPV | ||
| Overall | 90.2% (87.4-92.3) 12 datasets |
70% (65-97) |
| EUS-images | 87.9% (80.8-92.6) 6 datasets |
75% (54-96) |
| EUS-elastography | 90% (86.6-92.6) 5 datasets |
16% (85-95) |
| Neural network algorithm | 87.4% (82-91.3) 7 datasets |
68% (59-96) |
| NPV | ||
| Overall | 89.8% (86-92.7) 12 datasets |
90% (51-99) |
| EUS-images | 96.3% (93.3-98) 6 datasets |
37% (89-98) |
| EUS-elastography | 77% (65.1-85.8) 5 datasets |
86% (27-96) |
| Neural network algorithm | 91.4% (83.7-95.6) 7 datasets |
85% (43-98) |
CI: Confidence interval; PPV: Positive predictive value; NPV: Negative predictive value; PI: Prediction interval