Tekirdağ Namık Kemal University, Faculty of Medicine, Department of Medical Oncology - Tekirdag, Turkey.
Tekirdağ Namık Kemal University, Faculty of Medicine, Department of Radiation Oncology - Tekirdag, Turkey.
Rev Assoc Med Bras (1992). 2023 Mar 10;69(3):434-439. doi: 10.1590/1806-9282.20221255. eCollection 2023.
The aim of this study was to investigate the predictive importance of the previously validated log(ER)*log(PgR)/Ki-67 predictive model in a larger patient population.
Patients with hormone receptor positive/HER-2 negative and clinical node positive before chemotherapy were included. Log(ER)*log(PgR)/Ki-67 values of the patients were determined, and the ideal cutoff value was calculated using a receiver operating characteristic curve analysis. It was analyzed with a logistic regression model along with other clinical and pathological characteristics.
A total of 181 patients were included in the study. The ideal cutoff value for pathological response was 0.12 (area under the curve=0.585, p=0.032). In the univariate analysis, no statistical correlation was observed between luminal subtype (p=0.294), histological type (p=0.238), clinical t-stage (p=0.927), progesterone receptor level (p=0.261), Ki-67 cutoff value (p=0.425), and pathological complete response. There was a positive relationship between numerical increase in age and residual disease. As the grade of the patients increased, the probability of residual disease decreased. Patients with log(ER)*log(PgR)/Ki-67 above 0.12 had an approximately threefold increased risk of residual disease when compared to patients with 0.12 and below (odds ratio: 3.17, 95% confidence interval: 1.48-6.75, p=0.003). When age, grade, and logarithmic formula were assessed together, the logarithmic formula maintained its statistical significance (odds ratio: 2.47, 95% confidence interval: 1.07-5.69, p=0.034).
In hormone receptor-positive breast cancer patients receiving neoadjuvant chemotherapy, the logarithmic model has been shown in a larger patient population to be an inexpensive, easy, and rapidly applicable predictive marker that can be used to predict response.
本研究旨在探讨先前验证的 log(ER)*log(PgR)/Ki-67 预测模型在更大患者群体中的预测重要性。
纳入激素受体阳性/HER-2 阴性且化疗前临床淋巴结阳性的患者。测定患者的 log(ER)*log(PgR)/Ki-67 值，并使用受试者工作特征曲线分析计算理想的截断值。使用逻辑回归模型结合其他临床和病理特征进行分析。
共纳入 181 例患者。病理反应的理想截断值为 0.12（曲线下面积=0.585，p=0.032）。单因素分析显示，腔型（p=0.294）、组织学类型（p=0.238）、临床 t 分期（p=0.927）、孕激素受体水平（p=0.261）、Ki-67 截断值（p=0.425）与病理完全缓解之间无统计学相关性。年龄的数值增加与残留疾病呈正相关。随着患者分级的增加，残留疾病的概率降低。log(ER)*log(PgR)/Ki-67 值高于 0.12 的患者与值低于 0.12 的患者相比，残留疾病的风险增加约三倍（比值比：3.17，95%置信区间：1.48-6.75，p=0.003）。当评估年龄、分级和对数公式时，对数公式仍然具有统计学意义（比值比：2.47，95%置信区间：1.07-5.69，p=0.034）。
在接受新辅助化疗的激素受体阳性乳腺癌患者中，该对数模型在更大的患者群体中已被证明是一种廉价、简便、快速适用的预测标志物，可用于预测反应。
