Background: Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United\nStates. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple\nrisk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to\nsystematically identify and compare the performance of models that predict the risk of primary CRC among\nsymptomatic individuals.\nMethods: We searched Medline and EMBASE to identify primary research studies reporting, validating or\nassessing the impact of models. For inclusion, models needed to assess a combination of risk factors that\nincluded symptoms, present data on model performance, and be applicable to the general population.\nScreening of studies for inclusion and data extraction were completed independently by at least two\nresearchers.\nResults: Twelve thousand eight hundred eight papers were identified from the literature search and three\nthrough citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary\ncare populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation\nstudies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off\nchosen.\nConclusions: Models with good discrimination have been developed in both primary and secondary care\npopulations. Most contain variables that are easily obtainable in a single consultation, but further research is\nneeded to assess clinical utility before they are incorporated into practice.
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