Predicting Pathological Complete Response in Breast Cancer After Two Cycles of Neoadjuvant Chemotherapy by Tumor Reduction Rate: A Retrospective Case-Control Study.

IF 2.2 4区 医学 Q3 ONCOLOGY Journal of Breast Cancer Pub Date : 2023-04-01 DOI:10.4048/jbc.2023.26.e12
Litong Yao, Xiaoyan Liu, Mozhi Wang, Keda Yu, Shouping Xu, Pengfei Qiu, Zhidong Lv, Xinwen Zhang, Yingying Xu
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引用次数: 1

Abstract

Purpose: We aimed to identify effectiveness-associated indicators and evaluate the optimal tumor reduction rate (TRR) after two cycles of neoadjuvant chemotherapy (NAC) in patients with invasive breast cancer.

Methods: This retrospective case-control study included patients who underwent at least four cycles of NAC at the Department of Breast Surgery between February 2013 and February 2020. A regression nomogram model for predicting pathological responses was constructed based on potential indicators.

Results: A total of 784 patients were included, of whom 170 (21.68%) reported pathological complete response (pCR) after NAC and 614 (78.32%) had residual invasive tumors. The clinical T stage, clinical N stage, molecular subtype, and TRR were identified as independent predictors of pCR. Patients with a TRR > 35% were more likely to achieve pCR (odds ratio, 5.396; 95% confidence interval [CI], 3.299-8.825). The receiver operating characteristic (ROC) curve was plotted using the probability value, and the area under the ROC curve was 0.892 (95% CI, 0.863-0.922).

Conclusion: TRR > 35% is predictive of pCR after two cycles of NAC, and an early evaluation model using a nomogram based on five indicators, age, clinical T stage, clinical N stage, molecular subtype, and TRR, is applicable in patients with invasive breast cancer.

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通过肿瘤减少率预测乳腺癌在两周期新辅助化疗后病理完全缓解:一项回顾性病例对照研究。
目的:探讨浸润性乳腺癌患者新辅助化疗(NAC)两周期后的疗效相关指标及最佳肿瘤减除率(TRR)。方法:这项回顾性病例对照研究包括2013年2月至2020年2月期间在乳腺外科接受至少四个周期NAC的患者。基于潜在指标构建预测病理反应的回归模态图模型。结果:共纳入784例患者,其中170例(21.68%)报告NAC术后病理完全缓解(pCR), 614例(78.32%)存在浸润性肿瘤残留。临床T分期、临床N分期、分子亚型和TRR被确定为pCR的独立预测因子。TRR > 35%的患者更有可能实现pCR(优势比5.396;95%可信区间[CI], 3.299-8.825)。采用概率值绘制受试者工作特征(ROC)曲线,ROC曲线下面积为0.892 (95% CI, 0.863-0.922)。结论:两周期NAC后TRR > 35%可预测pCR,基于年龄、临床T分期、临床N分期、分子亚型、TRR五项指标的nomogram早期评价模型适用于浸润性乳腺癌患者。
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来源期刊
Journal of Breast Cancer
Journal of Breast Cancer 医学-肿瘤学
CiteScore
3.80
自引率
4.20%
发文量
43
审稿时长
6-12 weeks
期刊介绍: The Journal of Breast Cancer (abbreviated as ''J Breast Cancer'') is the official journal of the Korean Breast Cancer Society, which is issued quarterly in the last day of March, June, September, and December each year since 1998. All the contents of the Journal is available online at the official journal website (http://ejbc.kr) under open access policy. The journal aims to provide a forum for the academic communication between medical doctors, basic science researchers, and health care professionals to be interested in breast cancer. To get this aim, we publish original investigations, review articles, brief communications including case reports, editorial opinions on the topics of importance to breast cancer, and welcome new research findings and epidemiological studies, especially when they contain a regional data to grab the international reader''s interest. Although the journal is mainly dealing with the issues of breast cancer, rare cases among benign breast diseases or evidence-based scientifically written articles providing useful information for clinical practice can be published as well.
期刊最新文献
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