Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Accurate cancer risk stratification approaches could increase rates of early CRC diagnosis, improve health outcomes for patients and reduce pressure on diagnostic services. The faecal immunochemical test (FIT) for blood in stool is widely used in primary care to identify symptomatic patients with likely CRC. However, there is a 6—16% noncompliance rate with FIT in clinic and ~90% of patients over the symptomatic 10μg/g test threshold do not have CRC. A polygenic risk score (PRS) quantifies an individual's genetic risk of a condition based on many common variants. Existing PRS for CRC have so far been used to stratify asymptomatic populations. We conducted a retrospective cohort study of 53,112 UK Biobank participants with a CRC symptom in their primary care record at age 40+. A PRS based on 207 variants, 5 genetic principal components and 24 other risk factors and markers for CRC were assessed for association with CRC diagnosis within two years of first symptom presentation using logistic regression. Associated variables were included in an integrated risk model and tested for ability to predict CRC diagnosis within two years, using receiver operating characteristic area under the curve (ROCAUC) and Akaike information criterion (AIC). An integrated risk model combining PRS, age, sex and patient-reported symptoms was highly predictive of CRC development (ROCAUC: 0.80, 95% confidence interval: 0.78—0.81). This model has the potential to improve early diagnosis of CRC, particularly in cases of patient non-compliance with FIT.

The authors have declared no competing interest.

This work was supported by a generous donation from the Higgins family. This study was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre and the University of Exeter Medical School. BMR is supported by a Cancer Research UK project grant (EDDPJT-May22\100006). SB is supported by an NIHR Advanced Fellowship (NIHR301666). The views expressed in the manuscript are those of the author(s) and not necessarily those of the funders named.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All human data in this study came from UK Biobank. Data from the UK Biobank resource was accessed under Application Number 74981. The North West Multi-centre Research Ethics Committee gave ethical approval for UK Biobank as a research tissue bank resource. Researchers using UK Biobank do not require separate ethical clearance and can operate under the research tissue bank resource approval.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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All participant data analysed in the study are available from UK Biobank following successful application to access the UK Biobank resource for research. This study used 235 Read codes (NHS clinical descriptors) describing colorectal cancer symptoms. 159 of these were provided by the Diagnosis of Symptomatic Cancer Optimally (DISCO) consortium, University of Exeter and are available upon reasonable request to the authors. The remaining 76 Read codes for colorectal cancer symptoms, and 59 Read codes describing colorectal cancer diagnosis, are available online at: https://github.com/bethan-mallabar-rimmer/CRC_IRM/tree/main All other data produced in the present work are contained in the manuscript.

https://github.com/bethan-mallabar-rimmer/CRC_IRM/tree/main