Validation of the Memorial Sloan-Kettering Cancer Center Nomogram to Predict Overall Survival After Curative Colectomy in a Chinese Colon Cancer Population

Ann Surg Oncol. 2015 Nov;22(12):3881-7. doi: 10.1245/s10434-015-4495-2. Epub 2015 May 12.

Abstract

Background: Colon cancer nomogram designed by Memorial Sloan-Kettering Cancer Center (MSKCC) is an online prediction tool to predict overall survival for individual patient after curative resection. However, this model was never externally validated. We evaluated the accuracy of this nomogram in an independent external Chinese cohort.

Methods: Clinical data from 1005 patients who underwent primary curative-intent surgery at Peking University Cancer Hospital & Institute between 1996 and 2008 were used for external validation. Clinicopathologic characteristics and the performance of the MSKCC nomogram for prediction of overall survival were evaluated for 985 patients with complete data by using concordance index (C-index) and calibration plot.

Results: The C-index for the MSKCC nomogram was 0.71 in the Chinese cohort, compared with 0.67 for American Joint Committee on Cancer (AJCC) stage (P < .0001). This suggests that the nomogram discriminates overall survival better than AJCC staging system. Calibration plot showed a good calibration of the nomogram in the validation cohort. Furthermore, the MSKCC nomogram prediction illustrated the heterogeneity for survival of Chinese patients within each AJCC stage.

Conclusions: The MSKCC nomogram for colon cancer provides more accurate survival predictions than the AJCC staging system when applied to an external Chinese cohort. The MSKCC nomogram improved individualized prediction of survival and may aid in more accurate patient counseling, selection of various treatment options, and follow-up scheduling.

Publication types

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

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • China
  • Colectomy / mortality*
  • Colonic Neoplasms / mortality*
  • Colonic Neoplasms / surgery*
  • Decision Support Techniques
  • Female
  • Forecasting / methods
  • Humans
  • Male
  • Middle Aged
  • Nomograms*
  • Survival Rate
  • Young Adult