ArticleAnnals of surgical oncology2022
A Multiple-Center Nomogram to Predict Pneumonectomy Complication Risk for Non-Small Cell Lung Cancer Patients.
Article in Annals of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Impact of perioperative chemotherapy on survival outcomes in patients with non-small cell lung cancer undergoing pneumonectomy: a SEER database analysis.Journal of thoracic disease · 2026Article
- Application of a predictive model for postoperative pulmonary complications in patients with non-small cell lung cancer based on cardiopulmonary exercise testing.Journal of thoracic disease · 2026Article
- Development and validation of a clinical nomogram for predicting methicillin-resistant Staphylococcus aureus in patients with Staphylococcus aureus bacteremia: a retrospective study.European journal of medical research · 2026Article
- Development of a nomogram for overall survival prediction in primary upper lobe lung cancer patients: A SEER population-based analysis.PloS one · 2025Article
- The Impact of Postoperative Pulmonary Complications on Perioperative Outcomes in Patients Undergoing Pneumonectomy: A Multicenter Retrospective Cohort Study of the German Thorax Registry.Journal of clinical medicine · 2023Article
- Clinical characteristics and survival outcomes of patients with pneumonectomies: A population-based study.Frontiers in surgery · 2022Article
- Prediction of postoperative cardiopulmonary complications after lung resection in a Chinese population: A machine learning-based study.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveThis study aimed to construct a nomogram to quantitatively predict pneumonectomy complication risks for non-small cell lung cancer (NSCLC) patients.
methodsData from 1052 NSCLC patients who underwent pneumonectomy were retrospectively retrieved from the databases of three thoracic centers. Multivariable logistic regression was used to investigate postoperative morbidity predictors. Clinical parameters and operative features were analyzed using univariable and multivariable logistic regression analyses, and a nomogram to predict the risk of postoperative complications was constructed using bootstrap resampling. A receiver operating characteristic (ROC) curve was used to estimate the discrimination power for the nomogram.
resultsA total of 212 patients (20.2%) had major complications. After regression analysis, forced expiratory volume in 1 s, Charlson Comorbidity Index score, male sex, and right-sided pneumonectomy were identified and entered into the nomogram. The nomogram showed a robust discrimination, with an area under the ROC curve of 0.753 (95% confidence interval 0.604-0.818). The calibration curves for the probability of postoperative complications showed optimal agreement between the nomogram and the actual probability.
conclusionsBased on preoperative data, we developed a nomogram for predicting complication risks after pneumonectomy. This model may be helpful for thoracic surgeons in selecting appropriate patients for adopting prophylactic measures after surgery.
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