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Statistical modeling using preoperative prognostic variables in predicting extracapsular extension and progression
J J Bauer1, R R Connelly, I A Seterhenn
1Department of Surgery, Walter Reed Army Medical Center, Washington, DC 20307-5001, USA.
Objective:
To predict the risk of extracapsular extension and postoperative recurrence before radical prostatectomy (RP) for prostate cancer.
Methods:
We performed multivariate Cox regression analysis on preoperative variables in 260 clinically localized prostate cancer patients who underwent RP. With these data, we constructed a relative risk of recurrence (Rr) equation and an equation to predict the probability of extracapsular extension (PECE) before RP.
Results:
Rr is calculated as exp[(0.47 x race + 0.14 x PSAST) + (0.13 x worst biopsy Gleason sum) + (1.03 x stage T1c) + (1.55 x stage T2b,c)], where PSAST indicates a sigmoidal transformation of prostate-specific antigen. PECE is calculated as 1/[1 + exp(-Z)], where Z = -2.47 + 0.15 (PSAST) + 0.31 (worst biopsy Gleason sum) + 0.18 (race) + 0.16 (stage T1c) + 0.38 (stage T2b,c).
Conclusion:
These two equations can be used preoperatively to predict the probability of extracapsular disease and the risk of prostate-specific antigen recurrence in patients undergoing RP.