Early detection of colorectal cancer using symptoms and the ColonFlag: case-control and cohort studies

Abstract

Background: Early detection of colorectal cancer confers substantial prognostic benefit. Most symptoms are non-specific and easily missed. The ColonFlag algorithm identifies risk of undiagnosed colorectal cancer using age, sex and changes in full blood count (FBC) indices. The aim of this study was to investigate whether the ColonFlag detects undiagnosed colorectal cancer prior to the recording of symptoms in general practice.  Methods: We conducted case-control and cohort studies by linking primary care data from the Clinical Practice Research Datalink with colorectal cancer diagnoses from the National Cancer Registry. A ColonFlag score was derived for each FBC. We assessed the prevalence of symptoms at six-monthly intervals prior to index date (diagnosis date for cases, randomly selected date for controls). We then derived odds ratios (ORs) and area under the receiver operating characteristic (AUROC) curve for the ColonFlag, and for symptoms using logistic regression at each interval (primary outcome 18-24 months). Results: We included 1,893,641 patients, 10,875,556 FBCs and 8,918,037 ColonFlag scores. ColonFlag scores began to increase in cases compared with controls around 3-4 years before diagnosis. The AUROC for a diagnosis 18-24 months following the ColonFlag score was 0.736 (95% CI 0.715-0.759), falling to 0.536 (95% CI 0.523-0.548) with adjustment for age. ORs for individual symptoms became non-significant prior to 12 months before index date, except for abdominal pain (females OR=1.29, p<0.0001 at 12-18 months) and rectal bleeding (females OR=2.09, males OR=1.92, p<0.0001 at 18-24 months). Conclusions: Symptoms appear relatively late in the colorectal cancer process and are limited for supporting early stage detection. The ColonFlag can discriminate usefully at 18-24 months before diagnosis, suggesting a role for this algorithm in primary care, although some of its discriminatory ability comes from the age variable.