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Biostatistical modeling using traditional variables and genetic biomarkers for predicting the risk of prostate carcinoma recurrence after radical prostatectomy.

Publication ,  Journal Article
Bauer, JJ; Connelly, RR; Sesterhenn, IA; Bettencourt, MC; McLeod, DG; Srivastava, S; Moul, JW
Published in: Cancer
March 1, 1997

BACKGROUND: Approximately 50-60% of patients treated with radical prostatectomy for clinically localized prostate carcinoma are found to have microscopic disease that is not organ-confined, and a significant portion of these patients will relapse. Multiple studies have attempted to identify these high risk patients by evaluating many potential prognostic variables. These studies, however, have not included the more recent molecular biomarkers found to be independent predictors of disease recurrence. METHODS: One hundred thirty-two patients who underwent radical prostatectomy at one center between 1986 and 1993 were subjected to a multivariable Cox regression analysis to determine the preoperative and postoperative variables that remain significant predictors for the likelihood of serologic recurrence. The preoperative variables included in the model were age, race, and prostate specific antigen(PSA); the postoperative variables were Gleason sum, nuclear grade, pathologic stage (capsular status), p53 tumor suppressor gene expression, bcl-2 protooncogene expression, and proliferative biomarker Ki-67 expression. Biomarkers were also evaluated separately. RESULTS: A model was developed using only variables that remained significant predictors for the likelihood of recurrence. The following equation calculated the relative risk of recurrence: Rw = exp [(0.70 x Race) + (0.79 x PSA[4.1-10]) + (1.34 x PSA[>10]) + ( 0.91 x Organ confinement) + (0.65 x p53[1,2+]) + (1.45 x p53[3,4+]) + (0.70 x bcl-2)]. This equation categorized men into 3 distinct risk groups (low: Rr < 5.0; intermediate: Rr = 5.0-15.0; high risk: Rr > 15.0). CONCLUSIONS: This equation allows patients at high risk for PSA recurrence to be identified shortly after radical surgery. These patients at high risk for serologic recurrence and eventual progression may be considered for currently accepted adjuvant therapy or enrollment in clinical trials for the newer investigational therapies for locally advanced prostate carcinoma.

Duke Scholars

Published In

Cancer

ISSN

0008-543X

Publication Date

March 1, 1997

Volume

79

Issue

5

Start / End Page

952 / 962

Location

United States

Related Subject Headings

  • Tumor Suppressor Protein p53
  • Time Factors
  • Survival Analysis
  • Risk Factors
  • Risk
  • Proto-Oncogene Proteins c-bcl-2
  • Prostatic Neoplasms
  • Prostatectomy
  • Proportional Hazards Models
  • Oncology & Carcinogenesis
 

Citation

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Bauer, J. J., Connelly, R. R., Sesterhenn, I. A., Bettencourt, M. C., McLeod, D. G., Srivastava, S., & Moul, J. W. (1997). Biostatistical modeling using traditional variables and genetic biomarkers for predicting the risk of prostate carcinoma recurrence after radical prostatectomy. Cancer, 79(5), 952–962.
Bauer, J. J., R. R. Connelly, I. A. Sesterhenn, M. C. Bettencourt, D. G. McLeod, S. Srivastava, and J. W. Moul. “Biostatistical modeling using traditional variables and genetic biomarkers for predicting the risk of prostate carcinoma recurrence after radical prostatectomy.Cancer 79, no. 5 (March 1, 1997): 952–62.
Bauer JJ, Connelly RR, Sesterhenn IA, Bettencourt MC, McLeod DG, Srivastava S, et al. Biostatistical modeling using traditional variables and genetic biomarkers for predicting the risk of prostate carcinoma recurrence after radical prostatectomy. Cancer. 1997 Mar 1;79(5):952–62.
Bauer JJ, Connelly RR, Sesterhenn IA, Bettencourt MC, McLeod DG, Srivastava S, Moul JW. Biostatistical modeling using traditional variables and genetic biomarkers for predicting the risk of prostate carcinoma recurrence after radical prostatectomy. Cancer. 1997 Mar 1;79(5):952–962.
Journal cover image

Published In

Cancer

ISSN

0008-543X

Publication Date

March 1, 1997

Volume

79

Issue

5

Start / End Page

952 / 962

Location

United States

Related Subject Headings

  • Tumor Suppressor Protein p53
  • Time Factors
  • Survival Analysis
  • Risk Factors
  • Risk
  • Proto-Oncogene Proteins c-bcl-2
  • Prostatic Neoplasms
  • Prostatectomy
  • Proportional Hazards Models
  • Oncology & Carcinogenesis