Development, verification, and comparison of a risk stratification model integrating residual cancer burden to predict individual prognosis in early-stage breast cancer treated with neoadjuvant therapy.
Development, verification, and comparison of a risk stratification model integrating residual cancer burden to predict individual prognosis in early-stage breast cancer treated with neoadjuvant therapy.
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开发、验证和比较整合残余癌症负担的风险分层模型，以预测接受新辅助治疗的早期乳腺癌的个体预后
DOI：
10.1016/j.esmoop.2021.100269
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发表时间：
2021-10
期刊：
影响因子：
7.3
通讯作者：
Ling R
中科院分区：
文献类型：
--
作者：
Hou N;Wu J;Xiao J;Wang Z;Song Z;Ke Z;Wang R;Wei M;Xu M;Wei J;Qian X;Xu X;Yi J;Wang T;Zhang J;Li N;Fan J;Hou G;Wang Y;Wang Z;Ling R
目前尚缺乏一个预测乳腺癌新辅助化疗（NAC）患者无病生存期（DFS）和预后风险分层的有利模型。本研究的目的是制定一个很好的模型，专门用于预测这些患者的预后。2012年1月至2015年12月，749例在西京医院接受NAC治疗的早期BC患者被纳入。患者被随机分配到一个培训队列（n = 563）和一个独立队列（n = 186）。建立了一个预测模型，随后进行了验证。进一步测量预测性能和区分度，并与其他模型进行比较。临床美国癌症联合委员会分期、分级、雌激素受体表达、人表皮生长因子受体2（HER 2）状态和治疗、Ki-67表达、淋巴血管浸润和残留癌负荷被确定为NAC治疗BC的独立预后变量。该模型的C指数始终优于其他可用模型以及单个独立因素，在训练队列、独立队列、管腔BC、HER 2阳性BC和三阴性BC中分别为0.78、0.80、0.75、0.82和0.77。根据X-tile选择的最佳临界值（280和360），患者被分为低风险（总分≤280）、中等风险（280 <总分≤ 360）和高风险（总分>360）组，5年DFS分别为89.9%、56.9%和27.7%，差异显著。在BC患者中，第一个模型包括残余癌症负荷指数，证明可以预测具有良好表现和区分度的个体的生存。此外，它产生的风险分层可以确定整个早期BC队列和特定亚型队列的复发风险水平，帮助定制个性化的强化治疗，并在临床试验中选择可比的研究队列。建立NAC治疗BC的第一个风险分层列线图，并验证其在BC队列中的表现。首次将残余癌症负荷指数应用于预测诺模图。预测模型可用于预测用NAC治疗的所有早期BC的DFS。执行连续而不是分类模型来预测个体生存。风险分层可用于在试验设计中选择可比人群。
A favorable model for predicting disease-free survival (DFS) and stratifying prognostic risk in breast cancer (BC) treated with neoadjuvant chemotherapy (NAC) is lacking. The aim of the current study was to formulate an excellent model specially for predicting prognosis in these patients. Between January 2012 and December 2015, 749 early-stage BC patients who received NAC in Xijing hospital were included. Patients were randomly assigned to a training cohort (n = 563) and an independent cohort (n = 186). A prognostic model was created and subsequently validated. Predictive performance and discrimination were further measured and compared with other models. Clinical American Joint Committee on Cancer stage, grade, estrogen receptor expression, human epidermal growth factor receptor 2 (HER2) status and treatment, Ki-67 expression, lymphovascular invasion, and residual cancer burden were identified as independent prognostic variables for BC treated with NAC. The C-index of the model consistently outperformed other available models as well as single independent factors with 0.78, 0.80, 0.75, 0.82, and 0.77 in the training cohort, independent cohort, luminal BC, HER2-positive BC, and triple-negative BC, respectively. With the optimal cut-off values (280 and 360) selected by X-tile, patients were categorized as low-risk (total points ≤280), moderate-risk (280 < total points ≤ 360), and high-risk (total points >360) groups presenting significantly different 5-year DFS of 89.9%, 56.9%, and 27.7%, respectively. In patients with BC, the first model including residual cancer burden index was demonstrated to predict the survival of individuals with favorable performance and discrimination. Furthermore, the risk stratification generated by it could determine the risk level of recurrence in whole early-stage BC cohort and subtype-specific cohorts, help tailor personalized intensive treatment, and select comparable study cohort in clinical trials. Establishing the first risk stratification nomogram for BC treated with NAC and validate its performance in BC cohorts. Incorporating residual cancer burden index into predictive nomogram for the first time. Predictive model can be utilized to predict DFS for all early-stage BC treated with NAC. Performing a continuous rather than categorized model to predict individual survival. The risk stratification can be used to select comparable population in trial design.
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影响因子：
50.5
作者：
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