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影像生物标志物作为乳腺癌死亡的预测指标

Imaging Biomarkers as Predictors for Breast Cancer Death.

作者信息

Wu Wendy Yi-Ying, Tabar Laszlo, Tot Tibor, Fann Ching-Yuan, Yen Amy Ming-Fang, Chen Sam Li-Sheng, Chiu Sherry Yueh-Hsia, Ku May Mei-Sheng, Hsu Chen-Yang, Beckmann Kerri R, Smith Robert A, Duffy Stephen W, Chen Hsiu-Hsi

机构信息

Department of Radiation Sciences, Oncology, Umeå University, Sweden.

Department of Mammography, County Hospital Falun, Falun, Sweden.

出版信息

J Oncol. 2019 Apr 10;2019:2087983. doi: 10.1155/2019/2087983. eCollection 2019.

Abstract

BACKGROUND

To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes.

METHODS

Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010.

RESULTS

Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death.

CONCLUSION

Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients.

摘要

背景

利用肿瘤范围和生物学的影像生物标志物,特别是乳房X线摄影表现、基底表型、组织学肿瘤分布和传统肿瘤特征,区分纵向队列中乳腺癌死亡风险。

方法

采用前瞻性队列研究设计,将1996年至1998年间诊断的498例浸润性乳腺癌患者作为测试队列,评估影像生物标志物和其他预测因素对乳腺癌死亡风险的独立影响。对2006年至2010年间诊断的848例患者队列进行外部验证。

结果

在控制传统肿瘤特征和治疗方式后,乳房X线摄影肿瘤表现是乳腺癌死亡风险的独立预测因素(P = 0.0003)。铸型钙化和结构扭曲分别与乳腺癌死亡风险3.13倍和3.19倍相关。与非基底表型相比,基底表型独立赋予2.68倍风险。验证队列中观察到的死亡与预期死亡无显著差异。影像生物标志物与其他预测因素的联合应用将乳腺癌死亡风险分为十二类。

结论

将肿瘤的乳房X线摄影表现等影像生物标志物与组织病理学分布和基底表型相结合,准确预测了乳腺癌死亡的长期风险。该信息可能与确定分子检测需求、规划治疗以及确定乳腺癌患者最合适的临床监测方案相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/caa2/6481030/ecf7ccfa514d/JO2019-2087983.001.jpg

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