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Development and validation of a prognostic nomogram model incorporating routine laboratory biomarkers for preoperative patients with endometrial cancer

BACKGROUND: Some biomarkers collected from routine laboratory tests have shown important value in cancer prognosis. The study aimed to evaluate the prognostic significance of routine laboratory biomarkers in patients with endometrial cancer (EC) and to develop credible prognostic nomogram models for...

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Detalles Bibliográficos
Autores principales: Cong, Rong, Li, Mingyang, Xu, Wan, Ma, Xiaoxin, Wang, Shuhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688010/
https://www.ncbi.nlm.nih.gov/pubmed/38031022
http://dx.doi.org/10.1186/s12885-023-11497-8
Descripción
Sumario:BACKGROUND: Some biomarkers collected from routine laboratory tests have shown important value in cancer prognosis. The study aimed to evaluate the prognostic significance of routine laboratory biomarkers in patients with endometrial cancer (EC) and to develop credible prognostic nomogram models for clinical application. METHODS: A total of 727 patients were randomly divided into a training set and a validation set. Cox proportional hazards models were used to evaluate each biomarker’s prognostic value, and independent prognostic factors were used to generate overall survival (OS) and progression-free survival (PFS) nomgrams. The efficacy of the nomograms were evaluated by Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, X-tile analysis and Kaplan‒Meier curves. RESULTS: Ten significant biomarkers in multivariate Cox analysis were integrated to develop OS and PFS nomograms. The C-indices of the OS- nomogram in the training and validation sets were 0.885 (95% confidence interval (CI), 0.810–0.960) and 0.850 (95% CI, 0.761–0.939), respectively; those of the PFS- nomogram in the training and validation sets were 0.903 (95% CI, 0.866–0.940) and 0.825 (95% CI, 0.711–0.939), respectively. ROC, DCA and calibration curves showed better clinical application value for the nomograms incorporating routine laboratory biomarkers. X-tile analysis and Kaplan‒Meier curves showed that the nomograms were stable and credible in evaluating patients at different risks. CONCLUSIONS: Nomogram models incorporating routine laboratory biomarkers, including NLR, MLR, fibrinogen, albumin and AB blood type, were demonstrated to be simple, reliable and favourable in predicting the outcomes of patients with EC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11497-8.