ArticleFrontiers in oncology2023
Nomogram prediction model of postoperative pneumonia in patients with lung cancer: A retrospective cohort study.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Progress and current trends in prediction models for the occurrence and prognosis of cancer and cancer-related complications: a bibliometric and visualization analysis.Frontiers in oncology · 2025Pooled it
- Breathing exercises for patients with early-stage lung cancer: a meta-analysis.Systematic reviews · 2024Pooled it
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- Risk factors for postoperative pneumonia following intracranial aneurysm surgery: a propensity score matching analysis.Perioperative medicine (London, England) · 2026Article
- Clinical predictors and mortality of postoperative pneumonia following pulmonary resection in patients with lung cancer: A systematic review and meta-analysis.Lung India : official organ of Indian Chest Society · 2026Article
- Development and internal validation of a preoperative prediction model for postoperative pneumonia in lung cancer patients: a retrospective study.BMC surgery · 2025Article
- Development and validation of a risk prediction model for postoperative pneumonia in elderly non-cardiac surgery patients: a retrospective cohort study.Scientific reports · 2025Article
- Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning study.EClinicalMedicine · 2025Article
- Nomogram for predicting the development of pneumonia after colorectal cancer surgery.Scientific reports · 2025Article
- Article
- Nomogram prediction model for overall survival of late-stage lung cancer patients undergoing iodine-125 particle implantation brachytherapy.Journal of contemporary brachytherapy · 2024Article
- The (un)lucky seven-how can we mitigate risk factors for postoperative pneumonia after lung resections?Translational lung cancer research · 2024Article
- Impact of preoperative inflammatory indices and postoperative pneumonia on postoperative atrial fibrillation in patients with non-small cell lung cancer: a retrospective study.BMC pulmonary medicine · 2024Article
- XGBoost-based nomogram for predicting lymph node metastasis in endometrial carcinoma.American journal of cancer research · 2024Article
- A novel nomogram for predicting postoperative pneumonia risk in patients with localized bronchiectasis.Therapeutic advances in respiratory diseaseArticle
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6 authors.
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Abstract
Background: The prediction model of postoperative pneumonia (POP) after lung cancer surgery is still scarce. Methods: Retrospective analysis of patients with lung cancer who underwent surgery at The Fourth Hospital of Hebei Medical University from September 2019 to March 2020 was performed. All patients were randomly divided into two groups, training cohort and validation cohort at the ratio of 7:3. The nomogram was formulated based on the results of multivariable logistic regression analysis and clinically important factors associated with POP. Concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow goodness-of-fit test and decision curve analysis (DCA) were used to evaluate the predictive performance of the nomogram. Results: A total of 1252 patients with lung cancer was enrolled, including 877 cases in the training cohort and 375 cases in the validation cohort. POP was found in 201 of 877 patients (22.9%) and 89 of 375 patients (23.7%) in the training and validation cohorts, respectively. The model consisted of six variables, including smoking, diabetes mellitus, history of preoperative chemotherapy, thoracotomy, ASA grade and surgery time. The C-index from AUC was 0.717 (95%CI:0.677-0.758) in the training cohort and 0.726 (95%CI:0.661-0.790) in the validation cohort. The calibration curves showed the model had good agreement. The result of DCA showed that the model had good clinical benefits. Conclusion: This proposed nomogram could predict the risk of POP in patients with lung cancer surgery in advance, which can help clinician make reasonable preventive and treatment measures.
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