ArticleThoracic cancer2020
Development and validation of a nomogram prognostic model for patients with neuroendocrine tumors of the thymus.
Article in Thoracic cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 6 citations in OpenAlex.
- Recurrent Thymic Carcinoma Treated With Median Sternotomy, Innominate Vein Replacement for Superior Vena Cava, and Iodide Implantation: A Case Report and Review of the Literature.Cancer reports (Hoboken, N.J.) · 2025Review
- The combination of etoposide and platinum for the treatment of thymic neuroendocrine neoplasms: A retrospective analysis.Cancer medicine · 2023Article
- Surgical treatment of intermediate to high grade thymic neuroendocrine neoplasms: case series of five patients and literature review.Translational cancer research · 2022Article
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7 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe purpose of this study was to analyze the clinical characteristics and prognostic survival of patients with neuroendocrine tumors of the thymus (NETTs), and to develop and validate a nomogram model for predicting the prognosis of patients.
methodsWe conducted a retrospective analysis of patients with neuroendocrine tumors of the thymus in the Surveillance, Epidemiology, and End Results (SEER) database in the United States between 1988 and 2016. Cox scale risk regression analysis, the Kaplan-Meier method and log-rank test were used to carry out the significance test to determine the independent prognostic factors, from which a nomogram for NETTs was established. C-index and calibration curve were used to evaluate the prediction accuracy of the model. External validation of the nomogram was performed using data from our center.
resultsA total of 254 patients with NETTs were collected in the SEER database. In the multivariable analysis, T stage, tumor grade, surgery, and chemotherapy were found to be independent factors affecting the prognosis of patients (all P < 0.05). A nomogram model was constructed based on these variables, and its c-index was 0.707 (0.661-0.752). The c-index results showed that the nomogram model had better authentication capability than the eighth edition of the tumor, node, metastasis (TNM) staging system and Masaoka-Koga (MK) staging system. The calibration curve showed that the model could accurately predict patient prognosis.
conclusionsThe study established a nomogram model that predicted the overall survival rate of one-, three- and five-years, and used the survival prediction model to optimize individualized therapy and prognostic follow-up through risk stratification.
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