Nomograms to Predict Individual Prognosis of Patients with Primary Signet Ring Cell Carcinoma of the Urinary Bladder

Overview

Journal Transl Cancer Res

Specialty Oncology

Date 2022 Feb 4

PMID 35116694

Authors

Tianming Ma

Xiaonan Wang

Zijian Tian

Lingfeng Meng

Wei Zhang

Jiawen Wang

Xiaodong Liu

Yaoguang Zhang

Affiliations

Soon will be listed here.

Abstract

Background: Signet ring cell carcinoma (SRCC) is a rare but highly malignant variant of bladder carcinoma. Nomograms have demonstrated good accuracy in predicting the prognosis and guiding the management of pure urothelial carcinoma (UC). However, no accurate and applicable nomogram has been formulated for primary SRCC cases. This study aimed to determine significant prognostic factors and to construct nomograms for predicting the survival outcomes of patients with primary SRCCs of the urinary bladder.

Methods: A total of 317 eligible patients diagnosed with SRCC were analyzed using the 2004-2016 data from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate analyses were performed to explore the prognostic values. Nomograms were established to estimate the overall survival (OS) and cancer-specific survival (CSS) based on the Cox regression results. The performance of SRCC nomograms was evaluated using the concordance index and calibration curves. Survival curves were applied according to various surgical methods, lymph node status, and risk groups distinguished by nomograms.

Results: Two nomograms included common indicators that were significantly associated with OS and CSS, including T stage, M stage, tumor size, surgery, and the lymph node ratio (LNR). The nomograms indicated appreciable accuracy in predicting the OS and CSS, with concordance index of 0.723 [95% confidence interval (95% CI: 0.692-0.754] and 0.740 (95% CI: 0.701-0.779), respectively. The calibration curves revealed satisfactory consistency between the prediction of deviation correction and ideal reference line.

Conclusions: The two nomograms developed in this study showed high accuracy and reliability in predicting the survival outcomes of patients with SRCC and could be used to comprehensively assess the risk of SRCC. Moreover, they could assist in the optimal treatment selection for such patients.

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