Do PHI and PHI density improve detection of clinically significant prostate cancer only in the PSA gray zone?

OBJECTIVES

Prostate health index (PHI) is a predictive biomarker of positive prostate biopsy. The majority of evidence refers to its use in the PSA gray zone (4-10 ng/mL) and negative digital rectal exam (DRE). We aim to evaluate and compare the predictive accuracy of PHI and PHI density (PHId) with PSA, percentage of free PSA and PSA density, in a wider range of patients for the detection of clinically significant prostate cancer (csPCa).

METHODS

Multicenter prospective study that included patients suspicious of harboring prostate cancer. Non-probabilistic convenience sampling, where men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate and compare diagnostic accuracy AUC and decision curve analysis (DCA) were calculated. All these procedures were performed for the overall sample and the following subsamples: PSA < 4 ng/ml; PSA 4-10 ng/ml; PSA 4-10 ng/ml plus negative DRE and PSA > 10 ng/ml.

RESULTS

Among the 559 men included, 194 (34.7%) were diagnosed of csPCa. PHI and PHId outperfomed PSA in all subgroups. PHI best diagnostic performance was found in PSA 4-10 ng/ml with negative DRE (sensitivity 93.33, NPV 96.04). Regarding AUC, significant differences were found between PHId and PSA in the subgroup of PSA 4-10 ng/ml, whatever DRE status. In DCA, PHI density shows the highest net benefit.

CONCLUSIONS

PHI and PHId outperfom PSA in csPCa detection, not only in the PSA grey zone with negative DRE, but also in a wider range of PSA values. There is an urgent need of prospective studies to established a validated threshold and its incorporation in risk calculators.

Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer

Simple Summary

In the last decades, the widespread use of PSA as the standard tool for prostate cancer diagnosis led to a high rate of overdiagnosis and overtreatment. More recently, multiparametric magnetic resonance imaging (mpMRI) became part of the diagnostic pathway, and several next-generation PSA-based tests (PHI, PHI density, 4Kscore, STHLM3) have been proposed. The multivariable approach promises to help with a better stratification of PCa patients at initial diagnosis. In this study, we evaluated the performance of the prostate health index (PHI) and mpMRI for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). Our findings suggested that PHI had a better ability than mpMRI to predict positive biopsy, whereas a comparable performance in the identification of pathological aggressive PCa was pointed out. Notably, PHI and PHI density might represent useful biomarkers to recognize high-grade PCa in patients with low or uncertain PI-RADS scores on mpMRI.

Abstract

Widespread use of PSA as the standard tool for prostate cancer (PCa) diagnosis led to a high rate of overdiagnosis and overtreatment. In this study, we evaluated the performance of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). To this end, we prospectively enrolled 196 biopsy-naïve patients who underwent mpMRI. A subgroup of 116 subjects with biopsy-proven PCa underwent surgery. We found that PHI significantly outperformed both PI-RADS score (difference in AUC: 0.14; p < 0.001) and PHI density (difference in AUC: 0.08; p = 0.002) in the ability to predict positive biopsy with a cut-off value of 42.7 as the best threshold. Conversely, comparing the performance in the identification of clinically significant prostate cancer (csPCa) at RP, we found that PHI ≥ 61.68 and PI-RADS score ≥ 4 were able to identify csPCa (Gleason score ≥ 7 (3 + 4)) both alone and added to a base model including age, PSA, fPSA-to-tPSA ratio and prostate volume. In conclusion, PHI had a better ability than PI-RADS score to predict positive biopsy, whereas it had a comparable performance in the identification of pathological csPCa.