ArticleOncology letters2020
Nomogram construction for predicting survival of patients with non-small cell lung cancer with malignant pleural or pericardial effusion based on SEER analysis of 10,268 patients.
Article in Oncology letters, 2020. 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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7 citing papers in PubMed, 13 citations in OpenAlex.
- Exploring prognostic precision: a nomogram approach for malignant pleural effusion in lung cancer.BMC cancer · 2025Article
- Development and validation of the CAIL prognostic score in non-small cell lung cancer patients with malignant pleural effusion.The clinical respiratory journal · 2023Article
- A novel LASSO-derived prognostic model predicting survival for non-small cell lung cancer patients with M1a diseases.Cancer medicine · 2022Article
- Score for predicting overall survival in pancreatic adenocarcinoma patients with positive lymph nodes after surgery: a novel nomogram-based risk assessment.Gland surgery · 2021Article
- Development and External Validation of a Nomogram for Predicting Cancer-Specific Survival of Non-Small Cell Lung Cancer Patients With Ipsilateral Pleural Dissemination.Frontiers in oncology · 2021Article
- Prognostic Value of Germline Copy Number Variants and Environmental Exposures in Non-small Cell Lung Cancer.Frontiers in genetics · 2021Article
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6 authors at 2 institutions in 1 country.
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Abstract
Determining the accurate outcome of patients with non-small cell lung cancer (NSCLC) and malignant pleural effusion (MPE) or malignant pleural pericardial effusion (MPCE) at the initial diagnosis remains a challenge. The aim of the present study was to develop an effective nomogram for individualized estimation of overall survival in these patients. Patients diagnosed between January 2010 and December 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Age, race, sex, grade, histology, laterality, stage and status of MPE or MPCE at initial diagnosis were included as covariates. Several survival models were created and the performance of each was evaluated. The most effective model was then validated by internal bootstrap resampling and by using an independent external cohort. A nomogram was created based on this survival model and the predictive accuracy of the nomogram was evaluated by calibration plots. Data from 10,268 patients with lung cancer with MPE or MPCE at initial diagnosis were collected. The multivariate analysis with a lognormal model suggested that age, race, sex, histology, stage and status of MPE or MPCE at initial diagnosis were significant independent factors to predict survival. A nomogram was constructed based on the lognormal survival model, which showed the best performance. The concordance index of the survival model in the SEER cohort was 0.736. Both internal and external validation showed an acceptable level of agreement between the nomogram-predicted survival probability and actual survival. The nomogram of the present study based on a large cohort from the SEER database may improve prognostic prediction of patients with NSCLC with MPE or MPCE at initial diagnosis, and allow physicians to make appropriate decisions for disease management of their patients.
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