Trial reportCancer medicine2023
Development and validation of a nomogram to assess postoperative venous thromboembolism risk in patients with stage IA non-small cell lung cancer.
Trial report in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 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
- Postoperative venous thromboembolism risk following lung cancer surgery: a systematic review and meta-analysis.Journal of thrombosis and thrombolysis · 2025Pooled it
- Development and validation of a nomogram to assess postoperative venous thromboembolism risk in patients with stage IA non-small cell lung cancer.Cancer medicine · 2023Trial
- Navigating Immunotherapy Resistance: The Role of Cross-Line Strategies in Cancer Treatment.Journal of clinical medicine · 2026Article
- Construction and validation of a risk prediction model for venous thromboembolism post-VATS in simultaneous multicentric primary lung cancers.Journal of thoracic disease · 2025Article
- Development and Validation of a Predictive Nomogram for Venous Thromboembolism Risk in Multiple Myeloma Patients: A Single-Center Cohort Study in China.Biomedicines · 2025Article
- PRESCO: an online tool for predicting severe pulmonary complications and survival after cancer surgery.Frontiers in oncology · 2025Article
- Developing and validating risk predicting models to assess venous thromboembolism risk after radical cystectomy.Translational andrology and urology · 2024Article
- A Nomogram Model to Predict Deep Vein Thrombosis Risk After Surgery in Patients with Hip Fractures.Indian journal of orthopaedics · 2024Article
- Nomogram prediction for the risk of venous thromboembolism in patients with lung cancer.Cancer cell international · 2023Article
- Nomogram model combined thrombelastography for venous thromboembolism risk in patients undergoing lung cancer surgery.Frontiers in physiology · 2023Article
- Development of a Clinical-Radiomics Nomogram That Used Contrast-Enhanced Ultrasound Images to Anticipate the Occurrence of Preoperative Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma Patients.International journal of general 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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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVenous thromboembolism (VTE) is a common postoperative complication in patients with lung cancer that seriously affects prognosis and quality of life. At present, the detection rate of patients with early-stage lung cancer is increasing, but there are few studies on the risk factors for postoperative venous thromboembolism (VTE) in patients with stage IA non-small cell lung cancer (NSCLC). This study aimed to establish a nomogram for predicting the probability of postoperative VTE risk in patients with stage IA NSCLC.
methodsThe clinical data of 452 patients with stage IA NSCLC from January 2017 to January 2022 in our center were retrospectively analyzed and randomly divided into a training set and a validation set at a ratio of 7:3. Independent risk factors were identified by univariate and multivariate logistic regression analyses, and a nomogram was established based on the results and internally validated. The predictive power of the nomogram was evaluated by receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).
resultsThe nomogram prediction model included three risk factors: age, preoperative D-dimer, and intermuscular vein dilatation. The areas under the ROC curve of this predictive model were 0.832 (95% CI: 0.732-0.924) and 0.791 (95% CI: 0.668-0.930) in the training and validation sets, respectively, showing good discriminative power. In addition, the probability of postoperative VTE occurrence predicted by the nomogram was consistent with the actual occurrence probability. In the decision curve, the nomogram model had a better net clinical benefit at a threshold probability of 5%-90%.
conclusionThis study is the first to develop a nomogram for predicting the risk of postoperative VTE in patients with stage IA NSCLC; this nomogram can accurately and intuitively evaluate the probability of VTE in these patients and help clinicians make decisions on prevention and treatment.
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