ArticleThrombosis journal2023
Early identification of lung cancer patients with venous thromboembolism: development and validation of a risk prediction model.
Article in Thrombosis journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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9 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Risk prediction models for venous thromboembolism in lung cancer patients after surgery: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Article
- Biomarkers of Coagulation Disorders-Where to from Here?Biomolecules · 2026Review
- Incidence and risk factors of venous and arterial thromboembolism events in lung cancer patients treated with immune checkpoint inhibitors.Frontiers in pharmacology · 2026Article
- Splenic infarction secondary to multi-site thrombosis in lung adenocarcinoma with EGFR-L858R mutation: A case report.Oncology letters · 2025Article
- Novel orthotopic patient-derived xenograft model using human pancreatic cancer tissue fragments to recapitulate distant metastasis and cancer-related hypercoagulability.Medical molecular morphology · 2025Article
- Development and validation of a risk prediction model for venous thromboembolism after surgery in elderly patients with lung cancer.BMC surgery · 2025Article
- Review
- D-dimer cut-off value for predicting venous thromboembolism at the initial diagnosis in Japanese patients with advanced lung cancer.Japanese journal of clinical oncology · 2024Observational
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4 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionVenous thromboembolism(VTE) is a leading cause of death in patients with lung cancer. Furthermore, hospitalization of patients with advanced lung cancer for VTE treatment represents a major economic burden on the national public health resources. Therefore, we performed this prospective study to identify clinical biomarkers for the early identification of VTE in lung cancer patients.
methodsThis prospective study enrolled 158 patients with confirmed lung cancer, including 27 who were diagnosed with VTE within six months of the follow-up after lung cancer diagnosis. Multivariate logistic regression analysis was used to evaluate the diagnostic performancese of all the relevant clinical features and laboratory indicators in identifying lung cancer patients with a higher risk of VTE. A novel risk prediction model was constructed consisting of five clinical variables with the best diagnostic performances and was validated using the receiver operation characteristic(ROC) curves. The diagnostic performances of the new risk prediction model was also compared with the Khorana risk score (KRS) and the Padua risk score (PRS).
resultsThe VTE group of lung cancer patients (n = 27) showed significantly higher serum levels of fibrin degradation products (FDP), D-dimer, thrombomodulin (TM), thrombin-antithrombin-complex (TAT), α2-plasmin inhibitor-plasmin Complex (PIC), and tissue plasminogen activator-plasminogen activator inhibitor complex (t-PAIC) compared to those in the non-VTE group (n = 131). ROC curve analyses showed that the diagnostic efficacy of the new VTE risk prediction model with TM ≥ 9.75 TU/ml, TAT ≥ 2.25ng/ml, t-PAIC ≥ 7.35ng/ml, history of VTE, and ECOG PS score ≥ 2 was superior than the KRS and the PRS in the early identification of lung cancer patients with a higher risk of VTE.
conclusionsThe new risk prediction model showed significantly high diagnostic efficacy in the early identification of lung cancer patients with a high risk of VTE. The diagnostic efficacy of the new risk prediction model was higher than the KRS and the PRS in this cohort of lung cancer patients.
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