Performance of prediction models on survival outcomes of colorectal cancer with surgical resection: A systematic review and meta-analysis

Surg Oncol. 2019 Jun:29:196-202. doi: 10.1016/j.suronc.2019.05.014. Epub 2019 May 20.

Abstract

Prediction models allow accurate estimate of individualized prognosis. Increasing numbers of models on survival of CRC patients with surgical resection are being published. However, their performance and potential clinical utility have been unclear. A systematic search in MEDLINE and Embase databases (until 9th April 2018) was performed. Original model development studies and external validation studies predicting any survival outcomes from CRC (follow-up ≥1 year after surgery) were included. We conducted random-effects meta-analyses in external validation studies to estimate the performance of each model. A total of 83 original prediction models and 52 separate external validation studies were identified. We identified five models (Basingstoke score, Fong score, Nordinger score, Peritoneal Surface Disease Severity Score and Valentini nomogram) that were validated in at least two external datasets with a median summarized C-statistic of 0.67 (range: 0.57-0.74). These models can potentially assist clinical decision-making. Besides developing new models, future research should also focus on validating existing prediction models and investigating their real-word impact and cost-effectiveness for CRC prognosis in clinical practice.

Keywords: Colorectal cancer; Prediction model; Surgery; Survival; Systematic review.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Colorectal Neoplasms / mortality*
  • Colorectal Neoplasms / pathology
  • Colorectal Neoplasms / surgery
  • Colorectal Surgery / mortality*
  • Humans
  • Models, Statistical
  • Nomograms*
  • Predictive Value of Tests
  • Severity of Illness Index*
  • Survival Rate