新型模型预测乳腺癌 Oncotype DX 复发评分的临床影响。
Clinical Impact of a Novel Model Predictive of Oncotype DX Recurrence Score in Breast Cancer.
机构信息
Department of Breast Surgery, Yokohama Rosai Hospital, Yokohama, Japan.
Department of Breast and Thyroid Surgery, Yokohama City University Medical Center, Yokohama, Japan.
出版信息
In Vivo. 2021 Jul-Aug;35(4):2439-2444. doi: 10.21873/invivo.12522.
BACKGROUND/AIM: Oncotype DX recurrence score (RS) for breast cancer is a useful tool for determining chemotherapy indication but it is expensive and time-consuming. We determined whether four immuno-histochemical markers, namely human epidermal growth factor 2 (HER2), estrogen receptor (ER), progesterone receptor (PgR), and Ki-67, are predictive of an RS ≥26 in Japanese patients.
PATIENTS AND METHODS
The study included 95 Japanese patients evaluated for RS. A predictive model was created using logistic regression analysis.
RESULTS
The discriminant function was calculated as follows: p=1/{1+exp [-(4.611+1.2342×HER2-0.0813×ER- 0.0489 ×PgR+0.0857×Ki67)]}. Using a probability of 0.5 as the cutoff, the accuracy, sensitivity, specificity, positive predictive and negative predictive values were 90.5%, 72.2%, 94.8%, 76.4% and 93.5%, respectively.
CONCLUSION
The model had a high negative predictive value in predicting RS ≥26 in Japanese patients, indicating that Oncotype DX testing may be omitted in patients with a negative result according to the predictive model.
背景/目的：乳腺癌的 Oncotype DX 复发评分（RS）是确定化疗指征的有用工具，但它既昂贵又耗时。我们旨在确定四种免疫组织化学标志物，即人表皮生长因子 2（HER2）、雌激素受体（ER）、孕激素受体（PgR）和 Ki-67，是否可预测日本患者的 RS≥26。
患者和方法
该研究纳入了 95 名接受 RS 评估的日本患者。使用逻辑回归分析建立预测模型。
结果
判别函数计算如下：p=1/{1+exp [-(4.611+1.2342×HER2-0.0813×ER-0.0489×PgR+0.0857×Ki67)]}。以概率 0.5 作为截断值，该模型的准确性、敏感性、特异性、阳性预测值和阴性预测值分别为 90.5%、72.2%、94.8%、76.4%和 93.5%。
结论
该模型在预测日本患者 RS≥26 方面具有较高的阴性预测值，表明根据预测模型，阴性结果的患者可能无需进行 Oncotype DX 检测。
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