ArticleInternational journal of general medicine2021
A Clinical Nomogram for Predicting Cancer-Specific Survival in Pulmonary Large-Cell Neuroendocrine Carcinoma Patients: A Population-Based Study.
Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.Scientific reports · 2025Article
- A prognostic nomogram based on least absolute shrinkage and selection operator Cox regression in patients with pulmonary large-cell neuroendocrine carcinoma.Translational cancer research · 2024Article
- Metastasis pattern and prognosis of large cell neuroendocrine carcinoma: a population-based study.Journal of cancer research and clinical oncology · 2023Article
- Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study.Journal of clinical medicine · 2023Article
- Risk factors, survival analysis, and nomograms for distant metastasis in patients with primary pulmonary large cell neuroendocrine carcinoma: A population-based study.Frontiers in endocrinology · 2022Article
- Establishment and Validation of Prognostic Nomograms for Patients with Metastatic Pulmonary Large Cell Neuroendocrine Carcinoma.Cancer control : journal of the Moffitt Cancer CenterArticle
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Authors and funding
8 authors.
Funding
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Abstract
purposeThis study was designed to construct and validate a nomogram that was available for predicting cancer-specific survival (CSS) in patients with pulmonary large-cell neuroendocrine carcinoma (LCNEC). PATIENTS AND
methodsUsing the US Surveillance, Epidemiology, and End Results (SEER) database, we identified patients pathologically diagnosed as LCNEC from 1975 to 2016. Univariate and multivariate Cox regression was conducted to assess prognostic factors of CSS. A novel nomogram model was constructed and validated by the concordance index (C-index), calibration curves and decision curve analysis (DCA).
resultsA total of 624 LCNEC patients were enrolled. Five prognostic factors for CSS were identified and merged to establish nomograms. In the training and validation cohorts, calibration curves displayed the nomogram predictions are in a good agreement with the actual survival. The C-Index of the training and validation cohorts were both higher than 0.8, and the DCA results showed that the nomogram has clinical validity and utility.
conclusionThe proposed nomogram resulted in accurate CSS prognostic prediction for patients with LCNEC.
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