Evidence map›Paper›PMID 35116694›Full record

ArticleTranslational cancer research2021

Nomograms to predict individual prognosis of patients with primary signet ring cell carcinoma of the urinary bladder.

Tianming Ma, Xiaonan Wang, Zijian Tian, Lingfeng Meng, Wei Zhang, Jiawen Wang, Xiaodong Liu, Yaoguang Zhang

Abstract read
In one paragraph

Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Tianming Ma *Department of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Xiaonan Wang *Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Zijian TianDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Lingfeng MengDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Wei ZhangDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Jiawen WangDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Xiaodong LiuDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Yaoguang ZhangDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSignet 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.

methodsA 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.

resultsTwo 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.

conclusionsThe 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.

Indexed as

nomogramprognosisSignet ring cell carcinoma of the bladdersurvival analysis

Identifiers

PMID35116694
PMCPMC8797849

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