American Association for Cancer Research
19406207capr150274-sup-152358_1_supp_3120229_ntqsxv.docx (58.8 kB)

Supplementary Table 2 from Risk Prediction Models for Colorectal Cancer: A Systematic Review

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journal contribution
posted on 2023-04-03, 22:08 authored by Juliet A. Usher-Smith, Fiona M. Walter, Jon D. Emery, Aung K. Win, Simon J. Griffin

Methods for validation studies.



Colorectal cancer is the second leading cause of cancer-related death in Europe and the United States. Survival is strongly related to stage at diagnosis and population-based screening reduces colorectal cancer incidence and mortality. Stratifying the population by risk offers the potential to improve the efficiency of screening. In this systematic review we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict future risk of primary colorectal cancer for asymptomatic individuals. A total of 12,808 papers were identified from the literature search and nine through citation searching. Fifty-two risk models were included. Where reported (n = 37), half the models had acceptable-to-good discrimination (the area under the receiver operating characteristic curve, AUROC >0.7) in the derivation sample. Calibration was less commonly assessed (n = 21), but overall acceptable. In external validation studies, 10 models showed acceptable discrimination (AUROC 0.71–0.78). These include two with only three variables (age, gender, and BMI; age, gender, and family history of colorectal cancer). A small number of prediction models developed from case–control studies of genetic biomarkers also show some promise but require further external validation using population-based samples. Further research should focus on the feasibility and impact of incorporating such models into stratified screening programmes. Cancer Prev Res; 9(1); 13–26. ©2015 AACR.See related article by Frank L. Meyskens, Jr., p. 11

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