ArticleJournal of thrombosis and thrombolysis2023
A nomogram for predicting the risk of venous thromboembolism in patients with solid cancers.
Article in Journal of thrombosis and thrombolysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Evaluating the Predictive Value of the Endothelial Activation and Stress Index in Determining the Severity and Prognosis of Acute Pulmonary Embolism.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026Article
- Development and validation of a predictive model for postoperative hypercoagulability in middle-aged and elderly patients undergoing total knee arthroplasty: a retrospective study.European journal of medical research · 2025Article
- Development and validation of a nomogram model for predicting venous thromboembolism risk in lung cancer patients treated with immune checkpoint inhibitors: A cohort study in China.Cancer medicine · 2024Article
- The association between lactate dehydrogenase to serum albumin ratio and in-hospital mortality in patients with pulmonary embolism: a retrospective analysis of the MIMIC-IV database.Frontiers in cardiovascular medicine · 2024Article
- Construction and Validation of a Nomogram to Predict the Postoperative Venous Thromboembolism Risk in Patients with HGSOC.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
- Exploring Risk Factors for Lower Extremity Deep Vein Thrombosis Patients with Co-existing Pulmonary Embolism Based on Multiple Logistic Regression Model.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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Authors and funding
5 authors.
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Abstract
Cancer patients with venous thromboembolism (VTE) are prone to poor prognoses. Thus, we aimed to develop a nomogram to predict the risk of VTE in these patients. We retrospectively analyzed 791 patients diagnosed with solid tumors between January 2017 and May 2021 at Tongji Hospital. Univariate logistic analysis and multivariate logistic regression were adopted in this study. Our results indicated that age ≥ 60 years, tumor stages III-IV, platelet distribution width (PDW) ≤ 12.6%, albumin concentration ≤ 38.8 g/L, lactate dehydrogenase (LDH) concentration ≥ 198 U/L, D-dimer concentration ≥ 1.72 µg/mL, blood hemoglobin concentration ≤ 100 g/dL or the use of erythropoiesis-stimulating agents and cancer types were independent risk factors. The nomogram prediction model was developed based on the regression coefficients of these variables. We assessed the performance of the nomogram by calibration plot and the area under the receiver operating characteristic curve and compared it with the Khorana score. The concordance index (C- index) of the nomogram was 0.852 [95% confidence interval (CI) 0.823 to 0.880], while the Khorana score was 0.681 (95% CI 0.639 to 0.723). Given its performance, this nomogram could be used to select cancer patients at high risk for VTE and guide thromboprophylaxis treatment in clinical practice, provided it is validated in an external cohort.
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