ArticleTranslational cancer research2026
Development and validation of a predictive model for perioperative venous thromboembolism in colorectal cancer patients based on D-dimer combined with fibrinogen levels.
Article in Translational cancer research, 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
Background: Perioperative venous thromboembolism (VTE) is a frequent and potentially fatal complication in colorectal cancer (CRC) surgery. Although coagulation and inflammatory biomarkers are associated with cancer-related thrombosis, integrated prediction models for perioperative VTE in CRC remain limited. The aim of this study is to develop and validate a biomarker-based model for predicting perioperative VTE risk in CRC patients and to evaluate its clinical utility. Methods: A single-center retrospective cohort study was conducted, enrolling 618 CRC patients who underwent surgical treatment between January 1, 2020 and June 30, 2025, with follow-up until postoperative day 30. The primary endpoint was the occurrence of perioperative VTE, defined as deep vein thrombosis (DVT) and/or pulmonary embolism (PE) occurring from 72 hours before surgery to 30 days after surgery. Primary predictors included D-dimer and fibrinogen levels measured within 72 hours preoperatively. Secondary predictors included the neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), carcinoembryonic antigen (CEA), among others. A multivariate logistic regression model was constructed. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA), with internal validation performed via the bootstrap method. Results: VTE occurred in 70 patients (11.3%). Multivariate analysis identified D-dimer score [odds ratio (OR) =2.63], fibrinogen score (OR =2.18), NLR score (OR =2.35), CRP score (OR =0.92), and CEA score (OR =1.84) as independent predictors of perioperative VTE. The model demonstrated an area under the curve (AUC) of 0.83, good calibration (Hosmer-Lemeshow test P=0.49, Brier score =0.12), and an AUC of 0.81 after internal validation. DCA indicated significant net benefit within a risk threshold range of 5-35%. Risk stratification based on the model-derived total score revealed VTE incidence rates of 3.4%, 9.4%, and 26.3% in the low-, intermediate-, and high-risk groups, respectively (P<0.001). Conclusions: The predictive model incorporating preoperative D-dimer, fibrinogen, and inflammatory-immune markers effectively identifies CRC patients at high risk for perioperative VTE. It exhibits favorable discriminative ability and holds promise for clinical application, potentially informing individualized prevention strategies.
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