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Marks, Leonard S.

https://orcid.org/0000-0002-7910-179X

Mayo Clinic

University of California, Los Angeles

Citations 4

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

BJU International | October 15, 2016 | Volume: 120 | Issue: 1 | Pages: 61-68

10.1111/bju.13676 Get It

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.
The Prostate Health Index Selectively Identifies Clinically Significant Prostate Cancer
Sanda, Martin G. , Broyles, Dennis L., Shin, Sanghyuk S. , Bangma, Chris H. , Wei, John T., Partin, Alan W. , Klee, George G., Slawin, Kevin M., Marks, Leonard S. , Schaik, Ron H. N. van , Chan, Daniel W. , Sokoll, Lori J. , Cruz, Amabelle B., Mizrahi, Isaac, Catàlona, William J. , Loeb, Stacy

Journal of Urology | November 17, 2014 | Volume: 193 | Issue: 4 | Pages: 1163-1169

10.1016/j.juro.2014.10.121 Get It

Prospective Multicenter Evaluation of the Beckman Coulter Prostate Health Index Using WHO Calibration
Loeb, Stacy , Sokoll, Lori J. , Broyles, Dennis L., Bangma, Chris H. , Schaik, Ron H. N. van , Klee, George G., Wei, John T., Sanda, Martin G. , Partin, Alan W. , Slawin, Kevin M., Marks, Leonard S. , Mizrahi, Isaac, Shin, Sanghyuk S. , Cruz, Amabelle B., Chan, Daniel W. , Roberts, William L. , Catàlona, William J. , Loeb, Stacy

Journal of Urology | November 30, 2012 | Volume: 189 | Issue: 5 | Pages: 1702-1706

10.1016/j.juro.2012.11.149 Get It

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

Journal of Urology | April 10, 2011 | Volume: 185 | Issue: 5 | Pages: 1650-1655

10.1016/j.juro.2010.12.032 Get It