Table 5 The prediction performance of radiomics for NAC response in osteosarcoma patients
Clinical question | MRI-driven radiomics prediction model for NAC response in osteosarcoma patients |
|---|---|
Number of studies | 4 |
Good responder/sample size | 44/115 |
Pooled analysis | |
 DOR (95%CI) | 28.83 (10.27–80.95) |
 p value for DOR | p < 0.001 |
 Sensitivity (95% CI) | 0.84 (0.70–0.92) |
 Specificity (95% CI) | 0.85 (0.74–0.91) |
 PLR (95% CI) | 5.43 (3.11–9.49) |
 NLR (95% CI) | 0.19 (0.09–0.37) |
 AUC (95% CI) | 0.91 (0.88–0.93) |
Heterogeneity | |
 Higgins I2 test | I2 = 42.04% |
 Cochran’s Q test | Q = 5.18, p = 0.160 |
Publication bias | |
 Egger’s test | p = 0.035 |
 Begg’s test | p = 0.089 |
 Deeks’ test | p = 0.069 |
Trim and fill method | |
 Number of missing studies | 2 |
 Adjusted DOR (95%CI) | 20.53 (7.80–54.06) |
 p value for adjusted DOR | p < 0.001 |
 Level of Evidence | Weak |