Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Multicenter Study
. 2017 Jul;120(1):61-68.
doi: 10.1111/bju.13676. Epub 2016 Nov 22.

Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer

Stacy Loeb  1 , Sanghyuk S Shin  2 , Dennis L Broyles  2 , John T Wei  3 , Martin Sanda  4 , George Klee  5 , Alan W Partin  6 , Lori Sokoll  7 , Daniel W Chan  7 , Chris H Bangma  8 , Ron H N van Schaik  9 , Kevin M Slawin  10 , Leonard S Marks  11 , William J Catalona  12
Affiliations
Multicenter Study

Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer

Stacy Loeb et al. BJU Int. 2017 Jul.

Abstract

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 multicentre US study.

Materials and methods: The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a 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 (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). 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. The 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, previous biopsy, prostate volume, PSA and PHI, with an area under the curve 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.

Keywords: Prostate Health Index; nomogram; prostate biopsy; prostate cancer; risk assessment.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Receiver operating characteristic analysis showing the improvement in predictive accuracy for aggressive prostate cancer by adding phi to the (a) PCPT risk calculator and (b) ERSPC risk calculator.
Figure 2
Figure 2
Receiver operating characteristic analysis showing the improvement in predictive accuracy for overall prostate cancer by adding phi to the (a) PCPT risk calculator and (b) ERSPC risk calculator.
Figure 3
Figure 3
Combined receiver operating characteristic plot comparing the new derived model to the PCPT and ERSPC risk calculators for (a) aggressive and (b) overall prostate cancer detection.
Figure 4
Figure 4
Nomogram with phi and other variables to predict aggressive prostate cancer. Based on adjusted model for patient population with 25% prevalence of prostate cancer and 8.8% prevalence of aggressive cancer.
Figure 5
Figure 5
Decision curve analysis comparing final model with phi to biopsy-all and biopsy-none strategies. Based on adjusted model for patient population with 25% prevalence of prostate cancer and 8.8% prevalence of aggressive cancer.
See this image and copyright information in PMC

References

    1. Catalona WJ, Partin AW, Sanda MG, Wei JT, Klee GG, Bangma CH, Slawin KM, Marks LS, Loeb S, Broyles DL, Shin SS, Crus AB, Chan DW, Sokoll LJ, Roberts WL, van Schaik RHN, Mizrahi IA. A Multicenter Study of [−2] Pro-Prostate Specific Antigen Combined With Prostate Specific Antigen and Free Prostate Specific Antigen for Prostate Cancer Detection in the 2.0 to 10.0 ng/ml Prostate Specific Antigen Range. J Urol. 2011;185:1650–5. - PMC - PubMed
    1. Loeb S, Sanda MG, Broyles DL, Shin SS, Bangma CH, Wei JT, et al. The Prostate Health Index Selectively Identifies Clinically Significant Prostate Cancer. J Urol. 2014 Nov 15; - PMC - PubMed
    1. de la Calle C, Patil D, Wei JT, Scherr DS, Sokoll L, Chan DW, et al. Multicenter Evaluation of the Prostate Health Index (PHI) for Detection of Aggressive Prostate Cancer in Biopsy-Naive Men. J Urol. 2015 Jan 27; - PMC - PubMed
    1. Tosoian JJ, Loeb S, Feng Z, Isharwal S, Landis P, Elliot DJ, et al. Association of [−2]proPSA with Biopsy Reclassification During Active Surveillance for Prostate Cancer. The Journal of urology. 2012 Oct;188:1131–6. - PMC - PubMed
    1. Hirama H, Sugimoto M, Ito K, Shiraishi T, Kakehi Y. The impact of baseline [−2]proPSA-related indices on the prediction of pathological reclassification at 1 year during active surveillance for low-risk prostate cancer: the Japanese multicenter study cohort. Journal of cancer research and clinical oncology. 2014 Feb;140:257–63. - PMC - PubMed

Publication types

Substances