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使用临床病理数据预测Oncotype DX复发评分的算法:一项使用独立数据集的综述与比较

Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset.

作者信息

Harowicz Michael R, Robinson Timothy J, Dinan Michaela A, Saha Ashirbani, Marks Jeffrey R, Marcom P Kelly, Mazurowski Maciej A

机构信息

Department of Radiology, Duke University Medical Center, 2424 Erwin Road Suite 302, Durham, NC, 27705, USA.

Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.

出版信息

Breast Cancer Res Treat. 2017 Feb;162(1):1-10. doi: 10.1007/s10549-016-4093-4. Epub 2017 Jan 7.

Abstract

PURPOSE

Given the potential savings in cost and resource utilization, several algorithms have been proposed to predict Oncotype DX recurrence score (ODX RS) using commonly acquired histopathologic variables. Although it is promising, additional independent validation of these surrogate markers is needed prior to guide the patient management.

METHODS

In this retrospective study, we analyzed 305 patients with invasive breast cancer at our institution who had ODX RS available. We selected five equations that provide a surrogate measure of ODX as previously published by Klein et al. (Magee equations 1-3), Gage et al., and Tang et al. All equations used estrogen receptor status and progesterone receptor status along with different combinations of grade, proliferation indices (Ki-67, mitotic rate), HER2 status, and tumor size.

RESULTS

Of all surrogate scores tested, the Magee equation 2 provided the highest correlation with ODX both with regard to raw score (Pearson's correlation coefficient = 0.66 95% CI 0.59-0.72) and categorical correlation (Cohen's kappa = 0.43, 95% CI 0.33-0.53). Although Magee equation 2 provided a way to reliably identify high-risk disease by assigning 95% of the patients with high ODX RS to either the intermediate- or high-risk group, it was unable to reliably identify the potential for patients to have intermediate- or high-risk disease by ODX (66% of such patients identified).

CONCLUSIONS

Although commonly available surrogates for ODX appear to predict high-risk ODX RS, they are unable to reliably rule out the presence of patients with intermediate-risk disease by ODX. Given the potential benefit of adjuvant chemotherapy in women with intermediate-risk disease by ODX, current surrogates are unable to safely substitute for ODX. Characterizing the true recurrence risk in patients with intermediate-risk disease by ODX is critical to the clinical adoption of current surrogate markers and is an area of ongoing clinical trials.

摘要

目的

鉴于在成本和资源利用方面可能实现的节省,已提出多种算法,利用常见的组织病理学变量来预测Oncotype DX复发评分(ODX RS)。尽管前景乐观,但在指导患者管理之前,需要对这些替代标志物进行额外的独立验证。

方法

在这项回顾性研究中,我们分析了我院305例有ODX RS数据的浸润性乳腺癌患者。我们选择了五个方程,这些方程可作为ODX的替代指标,如Klein等人(Magee方程1 - 3)、Gage等人以及Tang等人之前发表的那样。所有方程均使用雌激素受体状态、孕激素受体状态以及分级、增殖指数(Ki - 67、有丝分裂率)、HER2状态和肿瘤大小的不同组合。

结果

在所有测试的替代评分中,Magee方程2与ODX的相关性最高,无论是原始评分(Pearson相关系数 = 0.66,95% CI 0.59 - 0.72)还是分类相关性(Cohen's kappa = 0.43,95% CI 0.33 - 0.53)。尽管Magee方程2提供了一种可靠地识别高危疾病的方法,可将95%的高ODX RS患者归为中危或高危组,但它无法可靠地识别患者具有中危或高危疾病的可能性(仅识别出66%的此类患者)。

结论

尽管常见的ODX替代指标似乎可以预测高风险的ODX RS,但它们无法可靠地排除ODX中危疾病患者的存在。鉴于辅助化疗对ODX中危疾病女性可能有益,目前的替代指标无法安全地替代ODX。通过ODX表征中危疾病患者的真正复发风险对于当前替代标志物的临床应用至关重要,并且是正在进行的临床试验领域。

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