Contemporary identification of patients at high risk of early prostate cancer recurrence after radical retropubic prostatectomy

William W. Roberts, Erik J. Bergstralh, Michael L. Blute, Jeffrey M. Slezak, Michael A Carducci, Misop Han, Jonathan Ira Epstein, Mario Eisenberger, Patrick Walsh, Alan Wayne Partin

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Abstract

Objectives. To develop a model that will identify a contemporary cohort of patients at high risk of early prostate cancer recurrence (greater than 50% at 36 months) after radical retropubic prostatectomy for clinically localized disease. Data from this model will provide important information for patient selection and the design of prospective randomized trials of adjuvant therapies. Methods. Proportional hazards regression analysis was applied to two patient cohorts to develop and cross-validate a multifactorial predictive model to identify men with the highest risk of early prostate cancer recurrence. The model and validation cohorts contained 904 and 901 men, respectively, who underwent radical retropubic prostatectomy at Johns Hopkins Hospital. This model was then externally validated using a cohort of patients from the Mayo Clinic. Results. A model for weighted risk of recurrence was developed: RW′ = lymph node involvement (0/1) × 1.43 + surgical margin status (0/1) × 1.15 + modified Gleason score (0 to 4) × 0.71 + seminal vesicle involvement (0/1) × 0.51. Men with an RW′ greater than 2.84 (9%) demonstrated a 50% biochemical recurrence rate (prostrate-specific antigen level greater than 0.2 ng/mL) at 3 years and thus were placed in the high-risk group. Kaplan-Meier analyses of biochemical recurrence-free survival demonstrated rapid deviation of the curves based on the RW′. This model was cross-validated in the second group of patients and performed with similar results. Furthermore, similar trends were apparent when the model was externally validated on patients treated at the Mayo Clinic. Conclusions. We have developed a multivariate Cox proportional hazards model that successfully stratifies patients on the basis of their risk of early prostate cancer recurrence.

Original languageEnglish (US)
Pages (from-to)1033-1037
Number of pages5
JournalUrology
Volume57
Issue number6
DOIs
StatePublished - Jun 2001

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Prostatectomy
Prostatic Neoplasms
Recurrence
Neoplasm Grading
Seminal Vesicles
Kaplan-Meier Estimate
Proportional Hazards Models
Patient Selection
Lymph Nodes
Regression Analysis
Antigens
Survival

ASJC Scopus subject areas

  • Urology

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Contemporary identification of patients at high risk of early prostate cancer recurrence after radical retropubic prostatectomy. / Roberts, William W.; Bergstralh, Erik J.; Blute, Michael L.; Slezak, Jeffrey M.; Carducci, Michael A; Han, Misop; Epstein, Jonathan Ira; Eisenberger, Mario; Walsh, Patrick; Partin, Alan Wayne.

In: Urology, Vol. 57, No. 6, 06.2001, p. 1033-1037.

Research output: Contribution to journalArticle

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abstract = "Objectives. To develop a model that will identify a contemporary cohort of patients at high risk of early prostate cancer recurrence (greater than 50{\%} at 36 months) after radical retropubic prostatectomy for clinically localized disease. Data from this model will provide important information for patient selection and the design of prospective randomized trials of adjuvant therapies. Methods. Proportional hazards regression analysis was applied to two patient cohorts to develop and cross-validate a multifactorial predictive model to identify men with the highest risk of early prostate cancer recurrence. The model and validation cohorts contained 904 and 901 men, respectively, who underwent radical retropubic prostatectomy at Johns Hopkins Hospital. This model was then externally validated using a cohort of patients from the Mayo Clinic. Results. A model for weighted risk of recurrence was developed: RW′ = lymph node involvement (0/1) × 1.43 + surgical margin status (0/1) × 1.15 + modified Gleason score (0 to 4) × 0.71 + seminal vesicle involvement (0/1) × 0.51. Men with an RW′ greater than 2.84 (9{\%}) demonstrated a 50{\%} biochemical recurrence rate (prostrate-specific antigen level greater than 0.2 ng/mL) at 3 years and thus were placed in the high-risk group. Kaplan-Meier analyses of biochemical recurrence-free survival demonstrated rapid deviation of the curves based on the RW′. This model was cross-validated in the second group of patients and performed with similar results. Furthermore, similar trends were apparent when the model was externally validated on patients treated at the Mayo Clinic. Conclusions. We have developed a multivariate Cox proportional hazards model that successfully stratifies patients on the basis of their risk of early prostate cancer recurrence.",
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AU - Bergstralh, Erik J.

AU - Blute, Michael L.

AU - Slezak, Jeffrey M.

AU - Carducci, Michael A

AU - Han, Misop

AU - Epstein, Jonathan Ira

AU - Eisenberger, Mario

AU - Walsh, Patrick

AU - Partin, Alan Wayne

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N2 - Objectives. To develop a model that will identify a contemporary cohort of patients at high risk of early prostate cancer recurrence (greater than 50% at 36 months) after radical retropubic prostatectomy for clinically localized disease. Data from this model will provide important information for patient selection and the design of prospective randomized trials of adjuvant therapies. Methods. Proportional hazards regression analysis was applied to two patient cohorts to develop and cross-validate a multifactorial predictive model to identify men with the highest risk of early prostate cancer recurrence. The model and validation cohorts contained 904 and 901 men, respectively, who underwent radical retropubic prostatectomy at Johns Hopkins Hospital. This model was then externally validated using a cohort of patients from the Mayo Clinic. Results. A model for weighted risk of recurrence was developed: RW′ = lymph node involvement (0/1) × 1.43 + surgical margin status (0/1) × 1.15 + modified Gleason score (0 to 4) × 0.71 + seminal vesicle involvement (0/1) × 0.51. Men with an RW′ greater than 2.84 (9%) demonstrated a 50% biochemical recurrence rate (prostrate-specific antigen level greater than 0.2 ng/mL) at 3 years and thus were placed in the high-risk group. Kaplan-Meier analyses of biochemical recurrence-free survival demonstrated rapid deviation of the curves based on the RW′. This model was cross-validated in the second group of patients and performed with similar results. Furthermore, similar trends were apparent when the model was externally validated on patients treated at the Mayo Clinic. Conclusions. We have developed a multivariate Cox proportional hazards model that successfully stratifies patients on the basis of their risk of early prostate cancer recurrence.

AB - Objectives. To develop a model that will identify a contemporary cohort of patients at high risk of early prostate cancer recurrence (greater than 50% at 36 months) after radical retropubic prostatectomy for clinically localized disease. Data from this model will provide important information for patient selection and the design of prospective randomized trials of adjuvant therapies. Methods. Proportional hazards regression analysis was applied to two patient cohorts to develop and cross-validate a multifactorial predictive model to identify men with the highest risk of early prostate cancer recurrence. The model and validation cohorts contained 904 and 901 men, respectively, who underwent radical retropubic prostatectomy at Johns Hopkins Hospital. This model was then externally validated using a cohort of patients from the Mayo Clinic. Results. A model for weighted risk of recurrence was developed: RW′ = lymph node involvement (0/1) × 1.43 + surgical margin status (0/1) × 1.15 + modified Gleason score (0 to 4) × 0.71 + seminal vesicle involvement (0/1) × 0.51. Men with an RW′ greater than 2.84 (9%) demonstrated a 50% biochemical recurrence rate (prostrate-specific antigen level greater than 0.2 ng/mL) at 3 years and thus were placed in the high-risk group. Kaplan-Meier analyses of biochemical recurrence-free survival demonstrated rapid deviation of the curves based on the RW′. This model was cross-validated in the second group of patients and performed with similar results. Furthermore, similar trends were apparent when the model was externally validated on patients treated at the Mayo Clinic. Conclusions. We have developed a multivariate Cox proportional hazards model that successfully stratifies patients on the basis of their risk of early prostate cancer recurrence.

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