ArticleCancer medicine2020
A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database.Technology in cancer research & treatmentTrial
- Development and validation of a nomogram for predicting overall and cancer-specific survival in elderly patients (≥ 65 years) with epithelial ovarian cancer.European journal of medical research · 2025Article
- Construction of nomogram model for early death risk in patients with severe traumatic brain injury.Frontiers in neurology · 2025Article
- Constructing a Nomogram Model to Estimate the Risk of Ventilator-Associated Pneumonia for Elderly Patients in the Intensive Care Unit.Advances in respiratory medicine · 2024Article
- Determining Association between Lung Cancer Mortality Worldwide and Risk Factors Using Fuzzy Inference Modeling and Random Forest Modeling.International journal of environmental research and public health · 2022Article
- Dynamic nomogram for long-term survival in patients with non-small cell lung cancer after pneumonectomy.Journal of thoracic disease · 2021Article
- A Nomogram to Predict Long-Term Survival Outcomes of Patients Who Undergo Pneumonectomy for Non-small Cell Lung Cancer With Stage I-IIIB.Frontiers in surgery · 2021Article
- Development of a nomogram for predicting the operative mortality of patients who underwent pneumonectomy for lung cancer: a population-based analysis.Translational lung cancer research · 2021Article
- A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators.Cancer medicine · 2020Article
- Detection and Independent Validation of Model-Based Quantitative Transcriptional Regulation Relationships Altered in Lung Cancers.Frontiers in bioengineering and biotechnology · 2020Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
aimsWe aimed to establish a nomogram for lung cancer using patients' characteristics and potential hematological biomarkers.
methodsPrinciple component analysis was used to reduce the dimensions of the data, and each component was transformed into categorical variables based on cutoff values obtained using the X-tile software. Multivariate analysis was used to determine potential prognostic biomarkers. Five components were used in the predictive nomogram. Internal validation of the model was performed by bootstrapping of samples, while external validation was performed on a separate cohort from Shandong Cancer Hospital. The predictive accuracy of the model was measured by concordance index and risk group stratification. Decision curve analysis was performed to evaluate the net benefit of the models.
resultsOne hundred patients in the Discovery group and 111 patients in the Validation group were retrospectively analyzed in this study. Forty-seven indexes were sorted into eight subgroups. Five components based on cox regression analysis were enrolled into the predictive nomogram. The nomogram prediction of the probability of 3- and 5-year overall survival was in great concordance with the actual observations. Of interest, the nomogram allowed better risk stratification of patients and better accuracy in predicting patients' survival compared with pathological tumor-node-metastasis staging system.
conclusionA nomogram was established for prognosis of lung cancer, which can be used for treatment selection and clinical care management.
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