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Worse characteristics can predict survival effectively in bilateral primary breast cancer: A competing risk nomogram using the SEER database
Author(s) -
Shen Kaiwen,
Yao Longdi,
Wei Jinli,
Luo Zhou,
Yu Wang,
Zhai Huamin,
Wang Jianwen,
Chen Luhong,
Fu Deyuan
Publication year - 2019
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.2662
Subject(s) - nomogram , medicine , concordance , proportional hazards model , hazard ratio , multivariate statistics , oncology , cohort , breast cancer , population , multivariate analysis , confidence interval , cancer , database , statistics , mathematics , computer science , environmental health
Abstract Objective There is limited information from population‐based cancer registries regarding prognostic features of bilateral primary breast cancer (BPBC). Methods Female patients diagnosed with BPBC between 2004 and 2014 were randomly divided into training (n = 7740) and validation (n = 2579) cohorts from the Surveillance, Epidemiology, and End Results Database. We proposed five various models. Multivariate Cox hazard regression and competing risk analysis were to explore prognosis factors in training cohort. Competing risk nomograms were constructed to combine significant prognostic factors to predict the 3‐year and the 5‐year survival of patients with BPBC. At last, in the validation cohort, the new score performance was evaluated with respect to the area under curve, concordance index, net reclassification index and calibration curve. Results We found out that age, interval time, lymph nodes invasion, tumor size, tumor grade and estrogen receptor status were independent prognostic factors in both multivariate Cox hazard regression analysis and competing risk analysis. Concordance index in the model of the worse characteristics was 0.816 (95% CI: 0.791‐0.840), of the bilateral tumors was 0.819 (95% CI: 0.793‐0.844), of the worse tumor was 0.807 (0.782‐0.832), of the first tumor was 0.744 (0.728‐0.763) and of the second tumor was 0.778 (0.762‐0.794). Net reclassification index of the 3‐year and the 5‐year between them was 2.7% and −1.0%. The calibration curves showed high concordance between the nomogram prediction and actual observation. Conclusion The prognosis of BPBC depended on bilateral tumors. The competing risk nomogram of the model of the worse characteristics may help clinicians predict survival simply and effectively. Metachronous bilateral breast cancer presented poorer survival than synchronous bilateral breast cancer.

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