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Prognostic model for survival in patients with neuroendocrine carcinomas of the cervix: SEER database analysis and a single-center retrospective study.
- Source :
- PLoS ONE, Vol 19, Iss 1, p e0296446 (2024)
- Publication Year :
- 2024
- Publisher :
- Public Library of Science (PLoS), 2024.
-
Abstract
- ObjectiveNeuroendocrine carcinoma of the cervix (NECC) is extremely rare in clinical practice. This study aimed to methodologically analyze the clinicopathological factors associated with NECC patients and to develop a validated survival prediction model.MethodsA total of 535 patients diagnosed with NECC between 2004 and 2016 were identified from the Surveillance, Epidemiology and End Results (SEER) database, while 122 patients diagnosed with NECC at Yunnan Cancer Hospital (YCH) from 2006 to 2019 were also recruited. Patients from the SEER database were divided into a training cohort (n = 376) and a validation cohort (n = 159) in a 7:3 ratio for the construction and internal validation of the nomogram. External validation was performed in a cohort at YCH. The Kaplan-Meier method was used for survival analysis, the Log-rank method test was used for univariate analysis of prognostic influences, and the Cox regression model was used for multivariate analysis.ResultsThe 3-year and 5-year overall survival (OS) rates for patients with NECC in SEER were 43.6% and 39.7%, respectively. In the training cohort, multivariate analysis showed independent prognostic factors for NECC patients including race, tumor size, distant metastasis, stage, and chemotherapy (pConclusionWe successfully constructed a nomogram that precisely predicts the OS for patients with NECC based on the SEER database and a large single-center retrospective cohort. The visualized and practical model can distinguish high-risk patients for recurrence and death who may benefit from clinical trials of boost therapy effectively. We also found that patients who received more than 4 cycles of chemotherapy acquired survival benefits than those who received less than 4 cycles.
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 19
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- PLoS ONE
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.be266ab308f04523b31b617f653befd6
- Document Type :
- article
- Full Text :
- https://doi.org/10.1371/journal.pone.0296446&type=printable