A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study

European Journal of Medical Research

Research

Liang Liu¹  Chuangui Li¹  Haibo Yuan¹  Qiang Wang¹  Yuanyuan Wang¹ 

[1] Department of Urology, Prostate & Andrology Key Laboratory of Baoding, Baoding No. 1 Central Hospital, No. 320 Changcheng North Street, Lianchi District, 071000, Baoding, Hebei, China;

关键词: Signet ring cell carcinoma;    Urinary bladder neoplasms;    Nomogram;    OS;    SEER;   

DOI  :  10.1186/s40001-022-00970-y

 received in 2022-10-17, accepted in 2022-12-23,  发布年份 2022

来源: Springer

【 摘 要 】

IntroductionThis study is to examine the predictors of survival and to construct a nomogram for predicting the overall survival (OS) of primary bladder signet ring cell carcinoma (SRCC) patients based on the analysis of the Surveillance, Epidemiology, and End Results (SEER) database.MethodsA total of 219 eligible patients diagnosed with SRCC were analyzed using the 2004–2015 data from SEER database. Univariate and multivariate Cox regression were used to determine independent prognostic factors, followed by development of a nomogram based on the multivariate Cox regression models. The consistency index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to validate the prognostic nomogram.ResultsThe nomograms indicated appreciable accuracy in predicting the OS, with C-index of 0.771 and 0.715, respectively. The area under the curve (AUC) of the nomogram was 0.713 for 1 year, 0.742 for 3 years, and 0.776 for 5 years in the training set, while was 0.730 for 1 year, 0.727 for 3 years, and 0.697 for 5 years in the validation set. The calibration curves revealed satisfactory consistency between the prediction of deviation correction and ideal reference line.ConclusionsThe prognostic nomogram developed in the analytical data of SEER it provided high accuracy and reliability in predicting the survival outcomes of primary bladder SRCC patients and could be used to comprehensively assess the risk of SRCC. Moreover, they could enable clinicians to make more precise treatment decisions for primary bladder SRCC patients.

【 授权许可】

CC BY   
© The Author(s) 2023

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