超声评估乳腺癌新辅助化疗早期疗效的多因素分析

Multivariate analysis of ultrasound evaluation of early response of breast cancer to neoadjuvant chemotherapy

摘要:

目的  分析和筛选评估乳腺癌新辅助化疗（NAC）早期疗效的超声指标，建立数学模型并进行初步评价。方法  对79例乳腺癌患者于化疗前及每2个疗程后行超声检查，监测血流阻力指数（RI）、收缩期最高血流速度（PSV）、弹性应变率（SR）、弹性评分、血流分级。采用单因素和多因素Logistic回归分析方法，筛选出可对乳腺癌NAC疗效做出早期评估的因素，建立数学模型，利用受试者工作曲线（ROC）检验回归模型的诊断效能。结果  单因素分析结果显示，5项指标比较差异有统计学意义；其中RI、PSV、SR被纳入多因素Logistic回归方程。同时ROC方法评价显示，所建立的模型能提高诊断的敏感性和特异性。结论  RI、PSV、SR可对乳腺癌NAC早期疗效做出可靠性评估；多因素回归模型较单因素指标在预测乳腺癌NAC早期疗效中有更高的诊断符合率。

Abstract:

Objective To analyze and screen the ultrasonic parameters of evaluating the early response of breast cancer to neoadjuvant chemotherapy (NAC), and to build a mathematical model for preliminary evaluation. Methods Seventy-nine patients with primary breast carcinoma received unltrosound examination before NAC and after 2 cycles. The parameters of resistance index (RI), peak systole velocity (PSV), strain ratio (SR), the color flow grade and elastic score were obtained. Both single and multiple logistic regression analyses were applied. After the factors with statistical significance were selected, the relevant mathematical model was built and then was evaluated by means of receiver operating characteristic (ROC) analysis. Results The univariate analysis showed significant difference in every factor. A mathematical diagnostic model was established based on RI, PSV and SR. And the result of ROC analysis showed it could improve the diagnostic sensitivity and specificity compared with the single-factor mathematical diagnostic model. Conclusions RI, PSV and SR can predict final pathologic response in primary breast cancers after early cycles of NAC. Multivariate regression model has a higher accurate rate of diagnosis than a single factor in predicting the early efficacy of NAC.