Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer

Stacy Loeb, Sanghyuk S. Shin, Dennis L. Broyles, John T. Wei, Martin Sanda, George Klee, Alan W. Partin, Lori Sokoll, Daniel W. Chan, Chris H. Bangma, Ron H N van Schaik, Kevin M. Slawin, Leonard S. Marks, William J. Catalona

Research output: Contribution to journalArticle

24 Citations (Scopus)

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.

Original languageEnglish (US)
JournalBJU International
DOIs
StateAccepted/In press - 2016

Fingerprint

Prostate
Prostatic Neoplasms
Health
Biopsy
Prostate-Specific Antigen
Digital Rectal Examination
Nomograms
Decision Support Techniques
Neoplasm Grading
Calibration
Multicenter Studies
Area Under Curve
Population

Keywords

  • Nomogram
  • Prostate biopsy
  • Prostate cancer
  • Prostate Health Index
  • Risk assessment

ASJC Scopus subject areas

  • Urology

Cite this

Loeb, S., Shin, S. S., Broyles, D. L., Wei, J. T., Sanda, M., Klee, G., ... Catalona, W. J. (Accepted/In press). Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer. BJU International. https://doi.org/10.1111/bju.13676

Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer. / Loeb, Stacy; Shin, Sanghyuk S.; Broyles, Dennis L.; Wei, John T.; Sanda, Martin; Klee, George; Partin, Alan W.; Sokoll, Lori; Chan, Daniel W.; Bangma, Chris H.; van Schaik, Ron H N; Slawin, Kevin M.; Marks, Leonard S.; Catalona, William J.

In: BJU International, 2016.

Research output: Contribution to journalArticle

Loeb, S, Shin, SS, Broyles, DL, Wei, JT, Sanda, M, Klee, G, Partin, AW, Sokoll, L, Chan, DW, Bangma, CH, van Schaik, RHN, Slawin, KM, Marks, LS & Catalona, WJ 2016, 'Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer', BJU International. https://doi.org/10.1111/bju.13676
Loeb, Stacy ; Shin, Sanghyuk S. ; Broyles, Dennis L. ; Wei, John T. ; Sanda, Martin ; Klee, George ; Partin, Alan W. ; Sokoll, Lori ; Chan, Daniel W. ; Bangma, Chris H. ; van Schaik, Ron H N ; Slawin, Kevin M. ; Marks, Leonard S. ; Catalona, William J. / Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer. In: BJU International. 2016.
@article{f75596cd52094dcc924aed0232332ec6,
title = "Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer",
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 = "Nomogram, Prostate biopsy, Prostate cancer, Prostate Health Index, Risk assessment",
author = "Stacy Loeb and Shin, {Sanghyuk S.} and Broyles, {Dennis L.} and Wei, {John T.} and Martin Sanda and George Klee and Partin, {Alan W.} and Lori Sokoll and Chan, {Daniel W.} and Bangma, {Chris H.} and {van Schaik}, {Ron H N} and Slawin, {Kevin M.} and Marks, {Leonard S.} and Catalona, {William J.}",
year = "2016",
doi = "10.1111/bju.13676",
language = "English (US)",
journal = "BJU International",
issn = "1464-4096",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer

AU - Loeb, Stacy

AU - Shin, Sanghyuk S.

AU - Broyles, Dennis L.

AU - Wei, John T.

AU - Sanda, Martin

AU - Klee, George

AU - Partin, Alan W.

AU - Sokoll, Lori

AU - Chan, Daniel W.

AU - Bangma, Chris H.

AU - van Schaik, Ron H N

AU - Slawin, Kevin M.

AU - Marks, Leonard S.

AU - Catalona, William J.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Nomogram

KW - Prostate biopsy

KW - Prostate cancer

KW - Prostate Health Index

KW - Risk assessment

UR - http://www.scopus.com/inward/record.url?scp=85006054111&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85006054111&partnerID=8YFLogxK

U2 - 10.1111/bju.13676

DO - 10.1111/bju.13676

M3 - Article

JO - BJU International

JF - BJU International

SN - 1464-4096

ER -