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用于确定乳腺浸润性小叶癌疾病特异性生存率的列线图:一项人群研究。

A nomogram for determining the disease-specific survival in invasive lobular carcinoma of the breast: A population study.

作者信息

Fu Rong, Yang Jin, Wang Hui, Li Lin, Kang Yuzhi, Kaaya Rahel Elishilia, Wang ShengPeng, Lyu Jun

机构信息

Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province.

School of Public Health, Xi'an Jiaotong University Health Science Center.

出版信息

Medicine (Baltimore). 2020 Oct 23;99(43):e22807. doi: 10.1097/MD.0000000000022807.

Abstract

We aimed to establish and validate a nomogram for predicting the disease-specific survival of invasive lobular carcinoma (ILC) patients.The Surveillance, Epidemiology, and End Results program database was used to identify ILC from 2010 to 2015, in which the data was extracted from 18 registries in the US. Multivariate Cox regression analysis was performed to identify independent prognostic factors and a nomogram was constructed to predict the 3-year and 5-year survival rates of ILC patients based on Cox regression. Predictive values were compared between the new model and the American Joint Committee on Cancer staging system using the concordance index, calibration plots, integrated discrimination improvement, net reclassification improvement, and decision-curve analyses.In total, 4155 patients were identified. After multivariate Cox regression analysis, nomogram was established based on a new model containing the predictive variables of age, the primary tumor site, histology grade, American Joint Committee on Cancer TNM (tumor node metastasis) stages II, III, and IV, breast cancer subtype, therapy modality (surgery and chemotherapy). The concordance index for the training and validation cohorts were higher for the new model (0.781 and 0.832, respectively) than for the old model (0.733 and 0.779). The new model had good performance in the calibration plots. Net reclassification improvement and integrated discrimination improvement were also improved. Finally, decision-curve analyses demonstrated that the nomogram was clinically useful.We have developed a reliable nomogram for determining the prognosis and treatment outcomes of ILC. The new model facilitates the choosing of superior medical examinations and the optimizing of therapeutic regimens with cooperation among oncologists.

摘要

我们旨在建立并验证一种用于预测浸润性小叶癌(ILC)患者疾病特异性生存率的列线图。利用监测、流行病学和最终结果(SEER)计划数据库来识别2010年至2015年的ILC病例,其中的数据来自美国18个登记处。进行多变量Cox回归分析以确定独立的预后因素,并基于Cox回归构建列线图来预测ILC患者的3年和5年生存率。使用一致性指数、校准图、综合判别改善、净重新分类改善和决策曲线分析,比较新模型与美国癌症联合委员会(AJCC)分期系统之间的预测价值。

总共识别出4155例患者。经过多变量Cox回归分析后,基于一个新模型建立了列线图,该模型包含年龄、原发肿瘤部位、组织学分级、AJCC TNM(肿瘤-淋巴结-转移)分期II、III和IV期、乳腺癌亚型、治疗方式(手术和化疗)等预测变量。新模型在训练队列和验证队列中的一致性指数分别为0.781和0.832,高于旧模型(分别为0.733和0.779)。新模型在校准图中表现良好。净重新分类改善和综合判别改善也有所提高。最后,决策曲线分析表明该列线图具有临床实用性。

我们开发了一种可靠的列线图来确定ILC的预后和治疗结果。新模型有助于在肿瘤学家的协作下选择更优的医学检查并优化治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e2/7581138/46c7074f15c8/medi-99-e22807-g003.jpg

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