Competing-risks nomogram for predicting cancer-specific death in upper tract urothelial carcinoma: a population-based analysis

Author:

Li Chengzhuo,Han Didi,Huang Qiao,Xu Fengshuo,Zheng Shuai,Li Xiang,Zhao Fanfan,Feng Xiaojie,Lyu JunORCID

Abstract

ObjectiveThis study aimed to use a competing-risks model to establish a nomogram to accurately analyse the prognostic factors for upper tract urothelial carcinoma (UTUC) cancer-specific death (CSD).DesignRetrospective observational cohort study.SettingThe programme has yielded a database of all patients with cancer in 18 defined geographical regions of the USA.ParticipantsWe selected patients with UTUC from the latest edition of the Surveillance, Epidemiology, and End Results database from 1975 to 2016. After excluding patients with unknown histological grade, tumour size and lymph node status, 2576 patients were finally selected.Primary and secondary outcome measuresWe used the Fine-Gray proportional subdistribution hazards model for multivariate analysis and compared the results with cause-specific hazards model. We finally constructed a nomogram for 3-year, 5-year and 8-year CSD rates and tested these rates in a validation cohort.ResultsThe proportional subdistribution hazards model showed that sex, tumour size, distant metastasis, surgery status, number of lymph nodes positive (LNP) and lymph nodes ratio (LNR) were independent prognostic factors for CSD. All significant factors associated with CSD were included in the nomogram. The 3-year, 5-year and 8-year concordance indexes were 0.719, 0.702 and 0.692 in the training cohort and 0.701, 0.675 and 0.668 in the validation cohort, respectively.ConclusionsThe competing-risks model showed that sex, tumour size, distant metastasis, surgery status, LNP and LNR were associated with CSD. The nomogram predicts the probability of CSD in patients with UTUC at 3, 5 and 8 years, which may help clinicians in predicting survival probabilities in individual patients.

Funder

National Social Science Foundation of China

Publisher

BMJ

Subject

General Medicine

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