A Nomogram Model Based on Neuroendocrine Markers for Predicting the Prognosis of Neuroendocrine Carcinoma of Cervix.
J Clin Med 2023;
12:jcm12031227. [PMID:
36769874 PMCID:
PMC9917535 DOI:
10.3390/jcm12031227]
[Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/30/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND
Combining traditional clinical parameters with neuroendocrine markers to construct a nomogram model to predict the postoperative recurrence of neuroendocrine carcinoma of cervix (NECC).
METHODS
A total of 257 patients were included in this study. Univariate and multivariate Cox regression analyses were used to establish a nomogram model in the training cohorts, which was further validated in the validation cohorts. The calibration curve was used to conduct the internal and external verification of the model.
RESULTS
Overall, 41 relapse cases were observed in the training (23 cases) and validation (18 cases) cohorts. The univariate analysis preliminarily showed that FIGO stage, stromal invasion, nerve invasion, lymph vascular space invasion, lymph node involvement, cervical-uterine junction invasion and CgA were correlated with NECC recurrence. The multivariate analysis further confirmed that FIGO stage (p = 0.023), stromal invasion (p = 0.002), lymph vascular space invasion (p = 0.039) and lymph node involvement (p = 0.00) were independent risk factors for NECC recurrence, which were ultimately included in the nomogram model. In addition, superior consistency indices were demonstrated in the training (0.863, 95% CI 0.784-0.942) and validation (0.884, 95% CI 0.758-1.010) cohorts.
CONCLUSIONS
The established nomogram model combining traditional clinical parameters with neuroendocrine markers can reliably and accurately predict the recurrence risks in NECC patients.
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