Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study

Abstract

Introduction: We aimed to develop an easy-to-use individual survival prognostication tool based on competing risk analyses to predict the risk of 5-year cancer-specific death after radical prostatectomy for patients with prostate cancer (PCa).Methods: We obtained the data from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016). The main variables obtained included age at diagnosis, marital status, race, pathological extension, regional lymphonode status, prostate specific antigen level, pathological Gleason Score. In order to reveal the independent prognostic factors. The cumulative incidence function was used as the univariable competing risk analyses and The Fine and Gray's proportional subdistribution hazard approach was used as the multivariable competing risk analyses. With these factors, a nomogram and risk stratification based on the nomogram was established. Concordance index (C-index) and calibration curves were used for validation.Results: A total of 95,812 patients were included and divided into training cohort (n = 67,072) and validation cohort (n = 28,740). Seven independent prognostic factors including age, race, marital status, pathological extension, regional lymphonode status, PSA level, and pathological GS were used to construct the nomogram. In the training cohort, the C-index was 0.828 (%95CI, 0.812–0.844), and the C-index was 0.838 (%95CI, 0.813–0.863) in the validation cohort. The results of the cumulative incidence function showed that the discrimination of risk stratification based on nomogram is better than that of the risk stratification system based on D'Amico risk stratification.Conclusions: We successfully developed the first competing risk nomogram to predict the risk of cancer-specific death after surgery for patients with PCa. It has the potential to help clinicians improve post-operative management of patients.

The survival benefit of different lymph node yields in radical prostatectomy for pN1M0 prostate cancer patients: Implications from a population-based study

“…Pathological N1M0 PCa was a multifaceted disease; age, race, marital status, positive surgical margins, pathological stage, positive nodes number, PSA level, and pathological Gleason score were prognostic factors for patients who received RP ( 5 , 13 , 14 ). Few studies focused on the oncological outcomes according to the number of LND.…”

The Dilemma of Misclassification Rates in Senior Patients With Prostate Cancer, Who Were Treated With Robot-Assisted Radical Prostatectomy: Implications for Patient Counseling and Diagnostics

“…However, consistent with several studies developing prediction tools for upgrading and upstaging, when biopsy vs. final histopathology was compared, senior age appeared indeed to have more unfavorable pathology and our own observations indicated greater misclassification between clinical vs. pathological stages. This phenomenon of misclassification likely explains findings of previous studies that reported rather higher rates of biochemical recurrence or even metastatic progression in senior men ( 5 – 7 ), since the studies adjusted for clinical parameters. In fact, such contradicting findings in combination with a rather dated concept to derive life expectancy based on demographics instead at the individual level supported the widely adopted notion to refrain from offering surgical local treatment to senior patients with PCa since the beneficiary potential of RARP appeared compromised ( 3 , 8 – 11 ).…”