Full BLOOD count TRends for colorectal cAnCer deteCtion (BLOODTRACC): external validation of dynamic clinical prediction models for early detection of colorectal cancer in primary care.

Virdee PS., Birks J., Holt T., Snell KIE., Abel G., Nicholson BD.

BACKGROUND: Colorectal cancer has low survival rates when diagnosed late-stage. We previously developed sex-specific dynamic risk prediction models utilising trends in the full blood count (FBC), a blood test commonly performed in primary care, to support early detection. We aimed to externally validate these prediction models. METHODS: We performed a cohort study of patients with at least one haemoglobin, mean cell volume, and platelet test. Patients were aged at least 40 years at their current test and had no history of colorectal cancer. The models included age (years) at current test and simultaneous trends over historical tests measured over five years before the current test to inform two-year risk of colorectal cancer diagnosis. Performance measures included the c-statistic and calibration slope. RESULTS: We included 2,956,977 males and 3,561,349 females, with 0.4% (n = 12,578) and 0.3% (n = 11,939) diagnosed with colorectal cancer, respectively. The c-statistic (95% CI) was 0.73 (0.72-0.73) for males and 0.74 (0.74-0.75) for females. The calibration slope (95% CI) was 0.92 (0.89-0.94) for males and 0.95 (0.93-0.98) for females. Calibration was good in subgroups of patient data, except under-predicted risk in those aged 70 + years, White individuals, and those with higher IMD. The c-statistic (95% CI) was similar regardless of the number of repeat tests used to define trend and increased as the longitudinal trend window increased until around 2.5-3.0 years for men (0.73 (0.71-0.74)) and 3.0-3.5 years for women (0.73 (0.72-0.75)) and decreased with increasing longitudinal windows thereafter. CONCLUSION: Utilising temporal changes in the commonly performed FBC test could enhance risk stratification for colorectal cancer in primary care. Further research may highlight approaches for improving predictive performance further.

DOI

10.1186/s12885-026-16179-9

Type

Journal article

Publication Date

2026-05-14T00:00:00+00:00

Keywords

Blood test, Colorectal cancer, Full blood count, Joint modelling of longitudinal and time-to-event data., Prediction model, Primary care

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