Table 3 Performance of AutoML in the validation cohort, Changhai prospective cohorts, and Zhongda prospective cohorts at 95% sensitivity
Cohort | Biopsy result | Total | Performance, % | |
|---|---|---|---|---|
csPCa | Benign+nsPCa | |||
Validation internal cohort, cut-off value= 23.8% | ||||
 AutoML probability > cut point | 195 | 353 | 548 | Sensitivity= 95.1 |
 AutoML probability <= cut point | 10 | 250 | 260 | Specificity= 41.5 |
 Total | 205 | 603 | 808 | PPV= 35.6, NPV= 96.2 |
 csPCa biopsy prevalence % | 25.4 | Fraction predicted negative | 32.2 | Missing= 4.9 |
Changhai prospective cohort, cut-off value= 21.5% | ||||
 AutoML probability > cut point | 168 | 203 | 371 | Sensitivity= 95.5 |
 AutoML probability <= cut point | 8 | 71 | 79 | Specificity= 25.9 |
 Total | 176 | 274 | 450 | PPV=45.3, NPV=89.9 |
 csPCa biopsy prevalence % | 39.1 | Fraction predicted negative | 17.6 | Missing=4.5 |
Zhongda prospective cohort, cut-off value= 24.3% | ||||
 AutoML probability > cut point | 93 | 98 | 191 | Sensitivity=95.9 |
 AutoML probability <= cut point | 4 | 64 | 68 | Specificity=39.5 |
 Total | 97 | 162 | 259 | PPV=48.7, NPV=94.1 |
 csPCa biopsy prevalence % | 37.5 | Fraction predicted negative | 26.3 | Missing=4.1 |