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

Yazhou He, Yuhan Ong, Xue Li, Farhat Vn. Din, Ewan Brown, Maria Timofeeva, Ziqiang Wang, Susan M. Farrington, Harry Campbell, Malcolm G. Dunlop, Evropi Theodoratou

Research output: Contribution to journalArticlepeer-review

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. There is a pressing need for more external validation studies so as to evaluate the performance of other abundant published prediction models that have not been adequately validated. Future research should also focus on investigating the real-word impact and cost effectiveness of existing prediction models for CRC prognosis in clinical practice.
Original languageEnglish
Pages (from-to)196-202
Number of pages7
JournalSurgical Oncology
Volume29
Early online date20 May 2019
DOIs
Publication statusPublished - Jun 2019

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