Nomogram for Predicting Breast Cancer-Specific Mortality of Elderly Women with Breast Cancer.
Nomogram for Predicting Breast Cancer-Specific Mortality of Elderly Women with Breast Cancer.
复制标题
预测老年乳腺癌女性乳腺癌特异性死亡率的列线图
DOI：
10.12659/msm.925210
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发表时间：
2020-09-13
期刊：
影响因子：
--
通讯作者：
Hu X
中科院分区：
文献类型：
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作者：
Lu X;Li X;Ling H;Gong Y;Guo L;He M;Sun H;Hu X
本研究的目的是评估老年乳腺癌患者乳腺癌特异性死亡（BCSD）和其他原因特异性死亡（BC）的累积发生率，并建立一个个性化的nomogram来估计BCSD。数据来自监测、流行病学和最终结果项目。在2004年至2008年期间，共有25241名年龄大于65岁的I-III期BC患者被纳入研究队列。我们使用累积发生率函数（CIF）来描述病因特异性死亡率，并使用Gray检验来比较各组间CIF的差异。采用Fine and Gray比例子分布风险模型对独立预后因素进行验证，并在此基础上建立竞争风险图和基于网络的计算器。用c -指数和校准图评估nomogram的性能。经资料筛选，纳入25241例进行统计分析。在培训队列中，BCSD的5年、8年和10年累积发病率分别为5.7、8.1和9.1%。确定了10个与BCSD相关的独立预后因素。训练组c -指数为0.818(0.804-0.831)，验证组c -指数为0.808（0.783-0.833）。校正图显示预测概率与实际观测值接近理想的一致性。我们建立了一个可靠的预测老年BCSD的动态nomogram，这一个性化的预测工具有利于临床实践中的风险分类和复杂的个性化治疗决策。
The objectives of this study were to evaluate the cumulative incidence of breast cancer-specific death (BCSD) and other cause-specific death in elderly patients with breast cancer (BC) and to develop an individualized nomogram for estimating BCSD. Data were retrieved from the Surveillance, Epidemiology, and End Results program. A total of 25 241 patients older than 65 years with stage I–III BC diagnosed between 2004 and 2008 was included in the study cohort. We used the cumulative incidence function (CIF) to describe the cause-specific mortality and Gray’s test to compare the differences in CIF among the groups. Fine and Gray’s proportional subdistribution hazard model was applied to validate the independent prognostic factors, upon which the competing-risks nomogram and web-based calculator was built. The performance of the nomogram was assessed with the C-indexes and calibration plot diagrams. After data screening, 25 241 cases were included for statistical analysis. In the training cohort, the 5-, 8-, and 10-year cumulative incidence of BCSD was 5.7, 8.1, and 9.1%, respectively. Ten independent prognostic factors associated with BCSD were identified. The C-index of the nomogram was 0.818 (0.804–0.831) in the training cohort and 0.808 (0.783–0.833) in the validation cohort. Calibration plot diagrams showed near-ideal consistency between the predicted probabilities and actual observations. We built a reliable dynamic nomogram for predicting BCSD in elderly patients, and this individualized predictive tool is favorable for risk classification and complex personalized treatment decision making in clinical practice.