ReviewFrontiers in oncology2022
Based on the Development and Verification of a Risk Stratification Nomogram: Predicting the Risk of Lung Cancer-Specific Mortality in Stage IIIA-N2 Unresectable Large Cell Lung Neuroendocrine Cancer Compared With Lung Squamous Cell Cancer and Lung Adenocarcinoma.
Review in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- Oncological outcome and survival predictors of widowed patients with bladder cancer in special populations.Scientific reports · 2025Article
- Case Report: Three cases of lung large cell neuroendocrine carcinoma with clinicopathological features of SMARCA4 (BRG1) deficiency.Frontiers in oncology · 2025Article
- Identifying the key hub genes linked with lung squamous cell carcinoma by examining the differentially expressed and survival genes.Molecular genetics and genomics : MGG · 2024Article
- Article
- A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma.Cancer science · 2024Article
- Enhancing prognostic accuracy: a SEER-based analysis for overall and cancer-specific survival prediction in cervical adenocarcinoma patients.Journal of cancer research and clinical oncology · 2023Article
- Development and validation of a nomogram for predicting overall survival in patients with stage III-N2 lung adenocarcinoma based on the SEER database.Translational cancer research · 2023Article
- Mutant-allele dispersion correlates with prognosis risk in patients with advanced non-small cell lung cancer.Journal of cancer research and clinical oncology · 2023Article
- Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer.Journal of thoracic disease · 2023Article
- Smoking Habit and Respiratory Function Predict Patients' Outcome after Surgery for Lung Cancer, Irrespective of Histotype and Disease Stage.Journal of clinical medicine · 2023Article
- A practical nomogram and risk stratification system predicting the cancer-specific survival for patients aged >50 with advanced melanoma.Frontiers in oncology · 2023Article
- Development and Validation of Prognostic Nomograms for Lung Squamous Cell Carcinoma With Brain Metastasis in Patients Aged 45 Years or Older: A Population-Based Study.Cancer control : journal of the Moffitt Cancer CenterArticle
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The purpose of this study is to predict overall survival (OS) and lung cancer-specific survival (LCSS) in patients with stage IIIA-N2 unresectable lung squamous cell cancer (LUSC), lung adenocarcinoma (LUAD), and large cell neuroendocrine cancer (LCNEC) by constructing nomograms and to compare risk and prognostic factors affecting survival outcomes in different histological subtypes. Methods: We included 11,505 unresectable NSCLC patients at stage IIIA-N2 between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Moreover, competition models and nomograms were developed to predict prognostic factors for OS and LCSS. Results: Analysis of the SEER database identified 11,505 NSCLC patients, of whom 5,559 (48.3%) have LUAD, 5,842 (50.8%) have LUSC, and 104 (0.9%) have LCNEC. Overall, both OS and LCSS were significantly better in stage IIIA-N2 unresectable LUAD than in LCNEC, while there was no statistically significant difference between LUSC and LCNEC. Age, gender, T stage, chemotherapy, and radiotherapy were significantly associated with OS rates in LUAD and LUSC. However, chemotherapy was the only independent factor for LCNEC ( Conclusion: Our study reports that unresectable patients with stage IIIA-N2 LCNEC and LUSC have worse LCSS than LUAD. The study's first prognostic nomogram constructed for patients with unresectable stage IIIA-N2 NSCLC can accurately predict the survival of different histological types, which may provide a practical tool to help clinicians assess prognosis and stratify these prognostic risks to determine which patients should be given an optimized individual treatment strategy based on histology.
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