Table 1.
Clinical characteristics of cohorts included in early diagnostics (eDX), therapy-monitoring, and GIA to PHI test comparison analyses.
Fig 1.
ROC analysis depicting tPSA (black line), fPSA (red line), fPSA% (green line) and GIA test (blue line) curves for cases of early DX (501 samples in total).
The AUC values are 0.71 and 0.83 for tPSA and GIA test, respectively.
Fig 2.
Percentage of negative (avoidable) biopsies (orange columns) calculated at 80% sensitivity for PCa biomarkers tPSA, fPSA and GIA test, respectively; Results are based on 559 serum samples.
Negative (avoidable) biopsies were calculated as the ratio of correctly identified benign patients from among the whole benign cohort.
Fig 3.
ROC analysis depicting ROC curves for tPSA (black line) and GIA test (blue line) as PCa biomarkers for therapy-monitoring (PCa patients who underwent therapy vs. PCa patients without any treatment).
Clinical validation using 176 samples revealed AUC of 0.51 for tPSA and of 0.90 for GIA test.
Fig 4.
Head-to-head comparison of PHI and GIA tests: ROC analysis for PHI (magenta line) and GIA (blue line) as PCa biomarkers for early PCa diagnostics using 215 serum samples.
AUC values obtained for PHI and GIA tests were 0.69 and 0.81, respectively.
Fig 5.
Percentage of negative (avoidable) biopsies (orange columns) calculated with 80% sensitivity for all four PCa biomarkers (tPSA, fPSA, PHI test and GIA test) from a clinical validation study performed using 215 serum samples for which PHI values were available.
Negative (avoidable) biopsies were calculated as the ratio of correctly identified benign patients out of the whole BPH cohort.
Fig 6.
Decision curve analysis (DCA) for commonly used serological screening tPSA test (black line) and GIA test (blue line), showing two extreme strategies, i.e. intervention for all patients (dashed green line) and for none (dashed red line).
Fig 7.
Principal component analysis (PCA) biplot showing scores and loadings for tPSA, fPSA and GIA test components (left) and eigenvalues (line plot on the right) for principal components (PC).