Sensitivities, specificities, areas under the curve, group descriptions and miRNAs of interest for 69 studies covering a broad range of diseases are provided.
Diagnostic performance was measure by sensitivity, specificity, area under receiver operating characteristics curve (AUC), positive predictive value (PPV), and negative predictive value (NPV).
ROC analysis showed that a 9% increase in ADC 1 5 min after sonication separated samples with significant ADC increases that persisted 20 min after sonication from those that did not with 69% sensitivity and 89% specificity (area under the curve (AUC), 0.80).
Note however that different studies used different performance measures (sensitivity, specificity, Area Under the Curve (AUC), percentage of concordance in classification, etc) to this end.
Furthermore, we only selected studies which presented a diagnostic accuracy measurement (e.g., sensitivity and specificity, area under ROC curve, diagnostic odds ratio, likelihood ratios) or that provided enough information for their calculation.
experimental values (Matthews Correlation Coefficient, accuracy, sensitivity, specificity, area under the ROC curve, correlation and rank correlation).
Sensitivity, specificity, area under receiver operating characteristic curves (AUC) and likelihood ratios (LR) were calculated.
Receiver-operating characteristic (ROC) analysis was performed to calculate sensitivity, specificity, area under the curve and the optimal cut-off.
No value of CVP discriminated between R and NR with good sensitivity and specificity (area under the curve (AUC) 0,68.
We determined the sensitivity, specificity, area under the receiver operator characteristics curves, proportions correctly classified and the tendency to make performance seem better than it was.
