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Development and internal validation of a novel PHI-nomogram to identify aggressive prostate cancer
Background:
Prostate Health Index (PHI) is a new test for the detection of prostate cancer (PCa), which improves the performance of total PSA (tPSA) and is related to tumor aggressiveness. The aim of our study was to construct a nomogram based in a multivariate model incorporating PHI to estimate the individual probability of aggressive PCa.
Methods:
276 subjects selected for biopsy were enrolled in our study, including 151 patients with PCa. D'Amico criteria were used to classify these patients in three groups related to risk of progression. Intermediate and high-risk PCa were considered as aggressive PCa. Multivariable models to predict aggressive PCa were constructed using laboratory (tPSA, %fPSA, %p2PSA, PHI) and clinical variables. The best prediction model was graphically presented as a nomogram for clinical use.
Results:
The highest accuracy (AUC: 0.815) was obtained for a multivariate model including age, digital rectal examination, tPSA, %fPSA, PHI and prostate volume. DCA was performed to confirm the usefulness of this nomogram, showing a higher net clinical benefit (greater than 7%) compared to the base model which included age, digital rectal examination and tPSA.
Conclusion:
PHI-based nomogram is a useful tool for the detection of aggressive PCa.
