ArticleTranslational oncology2026
Haematological pre-staging of colorectal cancer: Longitudinal trends identify high-risk metastatic phenotypes 24 months prior to diagnosis.
Article in Translational oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe latent systemic phase of colorectal cancer (CRC) offers a critical but often missed window for early intervention. This study evaluates whether longitudinal Complete Blood Count (CBC) trajectories can stratify metastatic risk before diagnosis.
methodsA retrospective cohort of CRC patients from the Health Department of La Ribera (Spain) was analysed using serial CBC data collected up to 24 months prior to diagnosis. Linear Mixed-Effects Models characterized patient-specific longitudinal trajectories, capturing intra-individual variability over time. In parallel, supervised machine learning models (Random Forest) were applied to evaluate the discriminative capacity of these haematological variables to distinguish synchronous metastatic phenotypes from non-metastatic cases.
resultsConsistent haematological deviations were detected at least 24 months before diagnosis. A distinct "metastatic gradient" emerged, where patients presenting with synchronous metastases exhibited significantly accelerated trajectories, specifically steeper declines in haemoglobin and sharper rises in inflammatory indices (neutrophil and platelet-to-lymphocyte ratios), compared to non-metastatic cases. These alterations were statistically significant even within clinically normal reference ranges. The predictive models achieved effective risk stratification, demonstrating a robust negative predictive value capable of excluding low-risk phenotypes.
conclusionsLongitudinal CBC monitoring reveals early systemic "red flags" that anticipate aggressive metastatic behaviour, supporting its use as a haematological pre-staging approach. Assessing the velocity of haematological change, could transform routine historical into a cost-effective resource for risk-adapted imaging and personalized surveillance. However, these findings represent a retrospective proof-of-concept; the approach remains investigational and should not be clinically implemented until validated prospectively in independent external cohorts.
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