Risk prediction models for colorectal cancer in people with symptoms: a systematic review.
BACKGROUND
Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals.


METHODS
We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers.


RESULTS
Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen.


CONCLUSIONS
Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice.
School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Tom G S
TG
Williams
Department of Gastroenterology, Complexo Hospitalario Universitario de Ourense, Instituto de Investigación Biomédica Ourense-Vigo-Pontevedra, Ourense, Spain.
Joaquín
J
Cubiella
The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.
Simon J
SJ
Griffin
The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.
Fiona M
FM
Walter
The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK. jau20@medschl.cam.ac.uk.
Juliet A
JA
Usher-Smith
D015179:Colorectal Neoplasms / Q000175:diagnosis*; D006801:Humans; D015233:Models, Statistical; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity
Colorectal cancer; Model; Prediction; Risk; Symptoms