CanAssist Breast对早期乳腺癌(HR +/HER 2 -)的风险分层及其与其他在线预后工具的相关性:来自单一中心的经验

A. Bapna, S. Patni, N. Patni, A. Gupta, A. Samar, Naresh Ledwani, T. Gupta, P. Agarwal
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引用次数: 0

摘要

采用各种方法对HR +/HER2 -早期乳腺癌(EBC)患者进行风险评估,有助于临床医生对风险进行分层和定制个体化治疗。多种预后检测是可用的,既有免费的,也有昂贵的。免费的预后工具,诺丁汉预后指数(NPI)和改进的辅助在线(mAOL)依赖于临床参数。CanAssist Breast (CAB)考虑临床参数和肿瘤生物学来评估复发风险。目的是通过CAB、NPI和mAOL评估风险,并辨别印度拉贾斯坦邦斋浦尔Bhagwan Mahaveer癌症医院和研究中心EBC队列中风险分层的差异。方法研究队列包括100例患者。采用kappa相关系数评价CAB、NPI和mAOL风险组间的风险一致性,采用双侧p值评价风险组间的一致性。结果本组以年龄≥50岁、T2/N0/G2肿瘤患者为主。CAB、NPI和mAOL的低危(LR)和高危(HR)比例分别为67:33、19:81和14:86。在两个年龄组中,与NPI和mAOL相比,CAB将更多的患者分层为LR。在N0、G2和T2肿瘤患者亚组中,CAB识别出的LR显著(p < 0.0001)高于NPI和mAOL(3-8倍)。在T1/G1肿瘤患者中,所有三种工具的风险比例相似。有趣的是,在N1亚组中,CAB LR(57%)是NPI(14%)的四倍。G3肿瘤的CAB LR为13%。mAOL无法识别N1和G3亚组的LR和G3亚组的NPI。CAB与NPI/mAOL之间的一致性较差(k值为0.14[95%可信区间:0.03-0.24]/0.11[0.02-0.20])。高达11%的mAOL/NPI LR被CAB检测为HR,高达63%的mAOL和NPI HR被CAB检测为LR。结论单纯使用临床参数的预测工具可能存在不足。结合肿瘤生物学和临床参数的关键生物标志物的CAB预测可能是有意义的。早期发表的关于不同种族人群的CAB数据及其与Oncotype DX的可比较性能使CAB成为HR +/HER2 - EBC的相关预后测试,以决定化疗的使用。
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Risk Stratification of Early Breast Cancer (HR +/HER 2–) by CanAssist Breast and Its Corelation with Other Online Prognostic Tools: Experience from a Single Center
Abstract Introduction  Risk assessment by various methods for HR +/HER2– early-stage breast cancer (EBC) patients help clinicians stratify risk and tailor individual treatment. Multiple prognostic tests are available, both free and expensive. Free prognostic tools, the Nottingham Prognostic Index (NPI), and modified Adjuvant Online (mAOL) rely on clinical parameters. CanAssist Breast (CAB) considers both clinical parameters and tumor biology for assessing the risk of recurrence. Objectives  The objective is to assess risk by CAB, NPI, and mAOL and discern the differences in the risk stratification in the EBC cohort of Bhagwan Mahaveer Cancer Hospital and Research Centre, Jaipur, Rajasthan, India. Methods  Study cohort comprises 100 patients. Risk concordance was assessed by the kappa correlation coefficient and restratification analysis between risk groups of CAB, NPI, and mAOL was assessed using a two-sided p -value. Results  Cohort was predominated by patients aged above 50, with T2/N0/G2 tumors. Low-risk (LR) and high-risk (HR) proportions by CAB, NPI, and mAOL were 67:33, 19:81, and 14:86, respectively. Across both age groups, CAB stratified more patients as LR compared with NPI and mAOL. In subgroups of patients with N0, G2, and T2 tumors, CAB identified significantly ( p  < 0.0001) higher (3–8 times) patients as LR than NPI and mAOL. In patients with T1/G1 tumors, risk proportions were similar by all three tools. Interestingly, CAB LR (57%) was four times that of NPI (14%) in the N1 subgroup. In G3 tumors CAB LR was 13%. mAOL failed to identify LR in the N1 and G3 subgroups and NPI in the G3 subgroup. There was poor agreement between CAB and NPI/mAOL (k 0.14 [95% confidence interval: 0.03–0.24]/0.11 [0.02–0.20]). Up to 11% of mAOL/NPI LR were detected as HR by CAB and up to 63% of mAOL and NPI HR as LR by CAB. Conclusion  Prognostication by tools that use clinical parameters alone might be inadequate. Prognostication using CAB that integrates critical biomarkers indicative of tumor biology along with clinical parameters could be significant. The earlier published data on CAB across various ethnic cohorts and its comparable performance with Oncotype DX makes CAB a relevant prognostic test in HR +/HER2– EBC to make decisions on chemotherapy use.
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期刊介绍: The journal will cover technical and clinical studies related to medical and pediatric oncology in human well being including ethical and social issues. Articles with clinical interest and implications will be given preference.
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