Objective
To examine the use of the Prostate Health Index (phi)* as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicenter US study.
Materials and Methods
The study population included 728 men with PSA levels of 2-10 ng/mL and negative digital rectal examination enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of phi improves the performance of currently available risk calculators (PCPT and ERSPC). We also designed and internally validated a new phi-based multivariable predictive model, and created a nomogram.
Results
Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. Phi predicted the risk of aggressive prostate cancer across the spectrum of values. Adding phi significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, prior biopsy, prostate volume, PSA, and phi with an AUC of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision curve analysis.
Conclusion
Using phi as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis.