Key result
A novel nomogram incorporating age, cancer stage, NSAID use, D-dimer, and diabetes predicted cancer-associated venous thromboembolism with an AUC of 0.816 (95% CI 0.770-0.861).
Why the study?
The study was conducted to develop a novel nomogram to predict cancer-associated venous thromboembolism in hospitalized patients with cancer receiving chemoradiotherapy.
Can a nomogram accurately predict cancer-associated venous thromboembolism in hospitalized patients receiving chemoradiotherapy?
Cohort (n=778)
Can a nomogram accurately predict cancer-associated venous thromboembolism in hospitalized patients receiving chemoradiotherapy?
Effect estimate: AUC 0.816 (95% CI 0.770-0.861)
A novel 5-factor nomogram demonstrated good predictive accuracy for cancer-associated venous thromboembolism in hospitalized patients receiving chemoradiotherapy.
Nomogram shows good discrimination for CAT in chemoradiotherapy patients; hypothesis-generating pending external validation and prospective outcome trials.
PURPOSE: The aim of this study was to develop a novel nomogram to predict cancer-associated venous thromboembolism (CAT) in hospitalized patients with cancer who receive chemoradiotherapy. METHODS: This was a retrospective cohort study of hospitalized patients with cancer who received chemoradiotherapy between January 2010 and December 2022. Predictive factors for CAT were determined using univariate and multivariate logistic regression analyses, and a risk prediction model based on the nomogram was constructed and validated internally. Nomogram performance was assessed using receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 778 patients were eligible for inclusion in this study. The nomogram incorporated 5 independent risk factors: age, cancer stage, use of nonsteroidal anti-inflammatory drugs, D-dimer levels, and history of diabetes mellitus. The area under the curve (AUC) of the nomogram for the training and validation cohorts was 0.816 and 0.781, respectively, with 95% confidence intervals (CIs) of 0.770-0.861 and 0.703-0.860, respectively. The calibration and DCA curves also displayed good agreement and clinical applicability of the nomogram model. CONCLUSIONS: The incidence of CAT was relatively high among patients with cancer receiving chemoradiotherapy. The nomogram risk model developed in this study has good prediction efficiency and can provide a reference for the clinical evaluation of the risk of adverse outcomes in patients with cancer receiving chemoradiotherapy.
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Sisi et al. (2024) conducted a cohort in Cancer-associated venous thromboembolism (n=778). Risk factors (age, cancer stage, NSAID use, D-dimer levels, diabetes mellitus) was evaluated on Cancer-associated venous thromboembolism (CAT) (AUC 0.816, 95% CI 0.770-0.861). A novel nomogram incorporating age, cancer stage, NSAID use, D-dimer, and diabetes predicted cancer-associated venous thromboembolism with an AUC of 0.816 (95% CI 0.770-0.861).
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