Development and validation of a nomogram for predicting survival of advanced breast cancer patients in China
Development and validation of a nomogram for predicting survival of advanced breast cancer patients in China
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DOI：
10.1016/j.breast.2020.08.004
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发表时间：
2020-10-01
期刊：
影响因子：
3.9
通讯作者：
Xu, Binghe
中科院分区：
文献类型：
--
作者：
Lin, Shaoyan;Mo, Hongnan;Xu, Binghe
背景资料：方法：从中国国家癌症中心数据库中提取1987年至2019年期间记录的4039例确诊为乳腺癌的患者的数据，共2263例ABC参与者入组本研究，这些参与者进一步随机分为3组：1分为训练组（n = 1706）和验证组（n = 557）。诺模图建立在单变量和多变量考克斯回归分析确定的独立预测因子的基础上。通过Harrell一致性指数（C-index）和校准图评估列线图的区分和预测能力。单因素和多因素分析发现，年龄、东部肿瘤协作组（ECOG）评分、T分期、N分期、肿瘤亚型、远处淋巴结（DLN）/肝/脑转移的存在、局部治疗、一线治疗有效率和无转移间隔期（MFI）与OS显著相关（均P < 0.05）。将这些变量纳入列线图中，以预测ABC患者的2年和3年OS。列线图的C指数为0.700（95%置信区间[CI]：0.683-0.717）（训练集）和0.686（95% CI：0.652-0.719）（验证集）。校准曲线显示，在内部和外部验证中，实际生存率和列线图预测值之间具有令人满意的一致性。诺模图是能够分层患者到不同的风险cohols.Conclusions：我们构建并验证了诺模图，可能作为一个有效的工具，为ABC患者提供预后预测，并指导医生作出个性化的治疗决策。(C)2020作者（S）由爱思唯尔有限公司发布
Background: There is a lack of prognostic models predicting the overall survival (OS) of advanced breast cancer (ABC) patients in China.Methods: Data from the China National Cancer Center database that recorded 4039 patients diagnosed with breast cancer between 1987 and 2019 were extracted and a total of 2263 ABC participants were enrolled in this study, which were further randomized 3:1 and divided into training (n = 1706) and validation (n = 557) groups. The nomogram was built based on independent predictors identified by univariate and multivariate cox regression analyses. The discriminatory and predictive capacities of the nomogram were assessed by Harrell's concordance index (C-index) and calibration plots.Results: Univariate and multivariate analyses found that age, Eastern Cooperative Oncology Group (ECOG) score, T-stage, N-stage, tumor subtype, the presence of distant lymph node (DLN)/liver/brain metastasis, local therapy, efficacy of first-line therapy and metastatic-free interval (MFI) were significantly related to OS (all P < 0.05). These variables were incorporated into a nomogram to predict the 2-year and 3-year OS of ABC patients. The C-indexes of the nomogram were 0.700 (95% confidence interval [CI]: 0.683-0.717) for the training set and 0.686 (95% CI: 0.652-0.719) for the validation set. The calibration curves revealed satisfactory consistency between actual survival and nomogram prediction in both the internal and external validations. The nomogram was capable of stratifying patients into different risk cohorts.Conclusions: We constructed and validated a nomogram that might serve as an efficient tool to provide prognostic prediction for ABC patients and guide the physicians to make personalized treatment decisions. (C) 2020 The Author(s). Published by Elsevier Ltd.