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通过将诊断时的年龄纳入临床预后分期来细化乳腺癌预后:介绍一种新的在线计算器。

Refining breast cancer prognosis by incorporating age at diagnosis into clinical prognostic staging: introduction of a novel online calculator.

机构信息

Department of Surgery, East Carolina University Brody School of Medicine, 600 Moye Blvd, Greenville, NC, 27834, USA.

出版信息

Breast Cancer Res Treat. 2021 Jun;187(3):805-814. doi: 10.1007/s10549-021-06113-x. Epub 2021 Feb 20.

Abstract

PURPOSE

American Joint Committee on Cancer (AJCC) clinical staging is used to estimate breast cancer prognosis, but individual patient survival within each stage varies considerably by age at diagnosis. We hypothesized that the addition of age at diagnosis to the staging schema will enable more refined risk stratification.

METHODS

We performed a retrospective population analysis of adult women diagnosed with invasive breast cancer between 2010 and 2015 registered in SEER. Multivariable Cox hazards models were used to evaluate the association of AJCC 8th edition clinical prognostic stage (CPS) and age with risk of overall mortality. Separate hierarchical models were fit to the data: Model 1: CPS alone; Model 2: CPS + age + age; and Model 3: CPS + age + age + CPS x age + CPS x age. Models were compared by the Akaike information criterion (AIC), the c-statistic for time-dependent receiver operator characteristic curves, and category-free net reclassification improvement (NRI). Internal validation was performed using bootstrapping samples.

RESULTS

Among 86,637 women, the median follow-up was 36 months and 3-year overall survival was 91.9% ± 0.1%. Age significantly modified the effect of CPS on survival (p < 0.0001). Model 3 was the most precise, with the lowest AIC (126,619.63), the highest c-statistic (0.8212, standard error 0.0187), and superior NRI indices.

CONCLUSION

Age at diagnosis is a highly prognostic variable that warrants consideration for inclusion in future editions of the AJCC Breast Cancer Staging Manual.

摘要

目的

美国癌症联合委员会(AJCC)临床分期用于估计乳腺癌预后,但每个分期内的患者生存情况因诊断时的年龄而异。我们假设在分期方案中加入诊断时的年龄将能够实现更精细的风险分层。

方法

我们对 2010 年至 2015 年在 SEER 中登记的诊断为浸润性乳腺癌的成年女性进行了回顾性人群分析。使用多变量 Cox 风险模型评估 AJCC 第 8 版临床预后分期(CPS)和年龄与总死亡率风险的关联。分别对数据进行分层模型拟合:模型 1:仅 CPS;模型 2:CPS+年龄+年龄;模型 3:CPS+年龄+年龄+CPS×年龄+CPS×年龄。通过 Akaike 信息准则(AIC)、时间依赖性接受者操作特征曲线的 c 统计量和无类别净重新分类改善(NRI)来比较模型。内部验证采用自举抽样法。

结果

在 86637 名女性中,中位随访时间为 36 个月,3 年总生存率为 91.9%±0.1%。年龄显著改变了 CPS 对生存的影响(p<0.0001)。模型 3 最精确,AIC 最低(126619.63),c 统计量最高(0.8212,标准误差 0.0187),且 NRI 指数更高。

结论

诊断时的年龄是一个高度预后变量,值得考虑纳入未来版的 AJCC 乳腺癌分期手册。

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