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在多元逻辑模型中,临床病理学和社会人口学因素与晚期复发三阴性乳腺癌相关:一项多机构队列研究。

Clinicopathologic and sociodemographic factors associated with late relapse triple negative breast cancer in a multivariable logistic model: A multi-institution cohort study.

发表日期:2023 Feb
作者: Adith Abraham, Carlos H Barcenas, Richard J Bleicher, Adam L Cohen, Sara H Javid, Ellis G Levine, Nancy U Lin, Beverly Moy, Joyce C Niland, Antonio C Wolff, Michael J Hassett, Sarah Asad, Daniel G Stover
来源: BREAST

摘要:

三阴性乳腺癌(TNBC)多发性复发大多在诊断后五年内发生,但晚期复发的TNBC(lrTNBC)也可能发生。我们的目标是利用易获取的临床病理和社会人口学特征建立lrTNBC的风险预测模型。我们在十个学术性癌症中心收集了1998年至2012年期间诊断为I-III期TNBC的患者。将大于5年的复发或死亡定义为lrTNBC。使用多元逻辑回归模型进行反向淘汰筛选,筛选出与lrTNBC相关的特征(p <0.10),并将最终的多元逻辑回归模型应用于训练组(70%)和独立验证组(30%)。共纳入至少有五年随访且在五年内未出现复发的2210例TNBC患者。在最终的多元逻辑回归模型中,lrTNBC与较高的诊断阶段(与I期相比调整后几率比[aOR]为10.9,95%置信区间[CI]为7.5-15.9,p <0.0001)和BMI(肥胖者与正常体重比起来的aOR为1.4,95%CI为1.0-1.8,p = 0.03)显著相关。最终的模型表现在训练组(70%)和验证组(30%)之间保持一致。结合诊断阶段、BMI和年龄建立的风险预测模型可以帮助识别具有lrTNBC发展风险的患者,并值得进一步研究。版权所有 © 2023作者。由Elsevier Ltd.出版。保留所有权利。
Most metastatic recurrences of triple negative breast cancer (TNBC) occur within five years of diagnosis, yet late relapses of TNBC (lrTNBC) do occur. Our objective was to develop a risk prediction model of lrTNBC using readily available clinicopathologic and sociodemographic features.We included patients diagnosed with stage I-III TNBC between 1998 and 2012 at ten academic cancer centers. lrTNBC was defined as relapse or mortality greater than 5 years from diagnosis. Features associated with lrTNBC were included in a multivariable logistic model using backward elimination with a p < 0.10 criterion, with a final multivariable model applied to training (70%) and independent validation (30%) cohorts.A total 2210 TNBC patients with at least five years follow-up and no relapse before 5 years were included. In final multivariable model, lrTNBC was significantly associated with higher stage at diagnosis (adjusted Odds Ratio [aOR] for stage III vs I, 10.9; 95% Confidence Interval [CI], 7.5-15.9; p < 0.0001) and BMI (aOR for obese vs normal weight, 1.4; 95% CI, 1.0-1.8; p = 0.03). Final model performance was consistent between training (70%) and validation (30%) cohorts.A risk prediction model incorporating stage, BMI, and age at diagnosis offers potential utility for identification of patients at risk of development of lrTNBC and warrants further investigation.Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.