ArticleCancer cell international2023
Nomogram prediction for the risk of venous thromboembolism in patients with lung cancer.
Article in Cancer cell international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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16 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- A systematic review of risk prediction model of venous thromboembolism for patients with lung cancer.Thoracic cancer · 2024Pooled it
- Construction and validation of a nomogram for overall survival prognosis in patients with advanced (stage III/IV) pancreatic cancer.Scientific reports · 2026Article
- Systemic immune-inflammation index as a predictor of venous thromboembolism in NSCLC patients treated with ICIs: a retrospective study.BMC pulmonary medicine · 2026Article
- Nomogram-based prediction of checkpoint inhibitor pneumonitis in lung cancer patients.BMC cancer · 2026Article
- The Predictive Value of Dynamic Changes in Procalcitonin and C-Reactive Protein in Evaluating Response of Patients with Pulmonary Tuberculosis in the Early Treatment.Infection and drug resistance · 2026Article
- Risk factors and clinical prediction model for vertebral artery stenosis following radiotherapy for nasopharyngeal carcinoma.The Journal of international medical research · 2025Article
- Development and validation of a risk prediction model for venous thromboembolism after surgery in elderly patients with lung cancer.BMC surgery · 2025Article
- Development and validation of a nomogram for predicting postoperative venous thromboembolism risk in patients with hepatocellular carcinoma.World journal of gastrointestinal oncology · 2025Article
- A nomogram predicting venous thromboembolism risk in primary liver cancer patients.Journal of thrombosis and thrombolysis · 2025Article
- Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach.PloS one · 2025Article
- Validation of risk assessment scores in predicting venous thromboembolism in patients with lung cancer receiving immune checkpoint inhibitors.BMC pulmonary medicine · 2024Article
- 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
- A nomogram to predict the risk of venous thromboembolism in patients with colon cancer in China.Cancer medicine · 2024Article
- Nomogram model combined thrombelastography for venous thromboembolism risk in patients undergoing lung cancer surgery.Frontiers in physiology · 2023Article
- Development and validation of a nomogram model for predicting the risk of venous thromboembolism in lymphoma patients undergoing chemotherapy: a prospective cohort study conducted in China.Annals of medicine · 2023Article
- 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
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10 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveThe aim of this study was to establish a nomogram graph model to accurately predict the venous thromboembolism (VTE) risk probability in the general population with lung cancer.
methodsBased on data from patients with lung cancer in Chongqing University Cancer Hospital of China, the independent risk factors of VTE were identified by the logistic univariable and multivariable analysis and were integrated to construct a nomogram, which was validated internally. The predictive effectiveness of the nomogram was evaluated by the receiver operating characteristic curve (ROC) and calibration curve.
resultsA total of 3398 lung cancer patients were included for analysis. The nomogram incorporated eleven independent VTE risk factors including karnofsky performance scale (KPS), stage of cancer, varicosity, chronic obstructive pulmonary disease (COPD), central venous catheter (CVC), albumin, prothrombin time (PT), leukocyte counts, epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), dexamethasone, and bevacizumab. The C-index of the nomogram model was 0.843 and 0.791 in the training and validation cohort, respectively, demonstrating good discriminative power. The calibration plots of the nomogram revealed excellent agreement between the predicted and actual probabilities.
conclusionsWe established and validated a novel nomogram for predicting the risk of VTE in patients with lung cancer. The nomogram model could precisely estimate the VTE risk of individual lung cancer patients and identify high-risk patients who are in need of a specific anticoagulation treatment strategy.
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