TY - JOUR
T1 - The EMPaCT Classifier
T2 - A Validated Tool to Predict Postoperative Prostate Cancer-related Death Using Competing-risk Analysis
AU - for the European Multicenter Prostate Cancer Clinical and Translational Research Group (EMPaCT)
AU - Tosco, Lorenzo
AU - Laenen, Annouschka
AU - Briganti, Alberto
AU - Gontero, Paolo
AU - Karnes, R. Jeffrey
AU - Bastian, Patrick J.
AU - Chlosta, Piotr
AU - Claessens, Frank
AU - Chun, Felix K.
AU - Everaerts, Wouter
AU - Gratzke, Christian
AU - Albersen, Maarten
AU - Graefen, Markus
AU - Kneitz, Burkhard
AU - Marchioro, Giansilvio
AU - Salas, Rafael Sanchez
AU - Tombal, Bertrand
AU - Van den Broeck, Thomas
AU - Van Der Poel, Henk
AU - Walz, Jochen
AU - De Meerleer, Gert
AU - Bossi, Alberto
AU - Haustermans, Karin
AU - Van Poppel, Hendrik
AU - Spahn, Martin
AU - Joniau, Steven
N1 - Publisher Copyright:
© 2017 European Association of Urology
PY - 2018/4
Y1 - 2018/4
N2 - 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. The EMPaCT classifier can accurately predict the survival of patients with high-risk prostate cancer. The EMPaCT classifier can become a novel standard to support decision-making in the multimodal setting.
AB - 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. The EMPaCT classifier can accurately predict the survival of patients with high-risk prostate cancer. The EMPaCT classifier can become a novel standard to support decision-making in the multimodal setting.
KW - High-risk disease
KW - Prognosis
KW - Prostate cancer
KW - Surgery
UR - http://www.scopus.com/inward/record.url?scp=85009799285&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85009799285&partnerID=8YFLogxK
U2 - 10.1016/j.euf.2016.12.008
DO - 10.1016/j.euf.2016.12.008
M3 - Article
C2 - 28753838
AN - SCOPUS:85009799285
SN - 2405-4569
VL - 4
SP - 369
EP - 375
JO - European Urology Focus
JF - European Urology Focus
IS - 3
ER -