Accuracy of life tables in predicting overall survival in patients after radical prostatectomy

BJU Int. 2008 Jul;102(1):33-8. doi: 10.1111/j.1464-410X.2008.07614.x. Epub 2008 Apr 2.

Abstract

Objective: To test the accuracy of life tables (LT), the standard tool for predicting life-expectancy (LE), but the accuracy of which is unknown in patients with prostate cancer, where the 10-year LE is a widely accepted threshold for the delivery of definitive therapy.

Patients and methods: We tested the accuracy of predictions of LE from LT in 9678 men treated with radical prostatectomy (RP) for prostate cancer. The predictions of LE from LT at 10 years after RP were compared to Kaplan Meier-derived 10-year survival values. Moreover, the accuracy of LT predictions was quantified in a Cox-regression using Harrell's concordance index. To control for the effect of prostate cancer mortality, analyses were repeated in a subset of 5955 patients with no evidence of disease recurrence. Additional stratification schemes were applied to control for age and comorbidity.

Results: At RP, the median age was 64 years, the median Charlson Comorbidity Index (CCI) was 1 and the median LT-derived LE was 16 years. The median actuarial survival was not reached (mean 12.4 years). In the whole group the LT-predicted 10-year survival was 96.8%, vs an observed of 75.3%. In men with no disease recurrence the LT-predicted survival was 97.3%, vs 81.1% observed. After age and CCI stratification, LT overestimated the 10-year survival the most in those aged 65-69 years and in patients with CCI scores of >2.

Conclusion: The overestimation of LE can lead to overtreatment of prostate cancer, especially in those men who die early from other causes.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cohort Studies
  • Humans
  • Life Expectancy*
  • Life Tables*
  • Male
  • Middle Aged
  • Prostatectomy / methods*
  • Prostatectomy / mortality
  • Prostatic Neoplasms / mortality*
  • Survival Analysis