The EMPaCT Classifier: A Validated Tool to Predict Postoperative Prostate Cancer-related Death Using Competing-risk Analysis

Eur Urol Focus. 2018 Apr;4(3):369-375. doi: 10.1016/j.euf.2016.12.008. Epub 2017 Jan 17.

Abstract

Background: Accurate prediction of survival after radical prostatectomy (RP) is important for making decisions regarding multimodal therapies. There is a lack of tools to predict prostate cancer-related death (PCRD) in patients with high-risk features.

Objective: To develop and validate a prognostic model that predicts PCRD combining pathologic features and using competing-risks analysis.

Design, setting, and participants: This was a retrospective multi-institutional observational cohort study of 5876 patients affected by high-risk prostate cancer. Patients were treated using RP and pelvic lymph node dissection (PLND) in a multimodal setting, with median follow-up of 49 mo.

Outcome measurements and statistical analysis: For PCRD prediction, a multivariate model with correction for competing risks was constructed to evaluate pathologic high-risk features (pT3b-4, Gleason score ≥8, and pN1) as predictors of mortality. All possible associations of the predictors were combined, and then subgroups with similar risk of PCRD were collapsed to obtain a simplified model encoding subgroups with significantly differing risk. Eightfold cross-validation of the model was performed.

Results and limitations: After applying exclusion criteria, 2823 subjects were identified. pT3b-4, Gleason score ≥8, and pN1 were all independent predictors of PCRD. The simplified model included the following prognostic groups: good prognosis, pN0 with 0-1 additional predictors; intermediate prognosis, pN1 with 0-1 additional predictors; poor prognosis, any pN with two additional predictors. The cross-validation yielded excellent median model accuracy of 88%. The retrospective design and the short follow-up could limit our findings.

Conclusions: We developed and validated a novel and easy-to-use prognostic instrument to predict PCRD after RP+PLND. This model may allow clinicians to correctly counsel patients regarding the intensity of follow-up and to tailor adjuvant treatments.

Patient summary: Prediction of mortality after primary surgery for prostate cancer is important for subsequent treatment plans. We present an accurate postoperative model to predict cancer mortality after radical prostatectomy for high-risk prostate cancer.

Keywords: High-risk disease; Prognosis; Prostate cancer; Surgery.

Publication types

  • Multicenter Study
  • Observational Study
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Combined Modality Therapy / methods
  • Decision Making
  • Humans
  • Lymph Node Excision
  • Male
  • Neoplasm Grading / methods
  • Postoperative Period
  • Predictive Value of Tests
  • Prognosis
  • Prostate-Specific Antigen / blood
  • Prostatectomy / methods*
  • Prostatic Neoplasms / mortality*
  • Prostatic Neoplasms / pathology
  • Prostatic Neoplasms / surgery*
  • Prostatic Neoplasms / therapy*
  • Retrospective Studies
  • Risk Factors

Substances

  • Prostate-Specific Antigen