Predicting Non-Sentinel Node Metastasis in Breast Cancer Patients

描述(申请人提供)：前哨淋巴结(SLN)活检是一种微创手段，可以准确地对乳腺癌患者的腋窝进行分期。虽然发现阴性的SLN可以避免腋窝淋巴结清扫(ALND)，但SLN中微转移的发现要求完成ALND。在所有SLN阳性患者中，高达80%的患者腋下不会有进一步的疾病。我们目前的知识在预测SLN阳性患者非SLN转移的可能性较低方面存在显著差距，因此可以避免ALND。一种新的术中基于RT-PCR的检测SLN微转移的方法(GeneSearch(R))已被证明与乳腺癌患者SLN的肿瘤负担相关。这项新技术在预测哪些患者在他们的非SLN中不会有进一步的疾病方面的潜在效用还没有被调查。使用这些数据开发一种针对非SLN状态的强大临床预测规则将填补我们知识中的这一空白，并提供及时的结论，这将对患者护理产生直接影响。为了实现这一总体目标，我们提出了以下具体目标：(1)使用双变量和多变量Logistic回归分析来确定GeneSearch(R)分析的定量周期时间值对非SLN状态的影响，以及(2)创建和验证(使用Bootstrap技术)临床预测规则，以使用术前和术中可用的临床病理因素，包括从GeneSearch(R)分析获得的数据来预测SLN阳性患者的非SLN状态。我们假设乳珠蛋白(MMG)和细胞角蛋白19(CK19)的定量RT-PCR周期时间，通过GeneSearch(R)分析评估为连续值，在双变量分析中将与非SLN转移显著相关。此外，这些标记物的周期时间将独立于其他因素预测非SLN转移。我们假设，可以使用术前和术中可用的临床病理因素创建有效的临床预测规则，包括从GeneSearch(R)测试获得的数据，该数据将识别其中非SLN转移可能性为5%的患者子集。预计GeneSearch(R)测试数据的增加将大大提高单独使用临床病理因素来预测这一组患者的能力。创建和验证一个结合了新的分子数据的强大的临床预测规则，以确定具有非SLN转移风险的亚组患者，将填补我们目前知识中的一个重大空白，并将减少ALND的不必要发病率，帮助满足NCI在2015年前消除癌症痛苦的挑战。与公共卫生相关：多达80%的乳腺癌患者的第一个引流(哨兵)淋巴结病变很小，他们的腋窝不会有进一步的疾病。然而，目前还没有准确的方法来预测哪些患者不会有残留的疾病，因此所有前哨淋巴结中有0.2毫米肿瘤沉积的患者都会切除剩余的淋巴结--这一过程与相当高的发病率有关。我们试图创建和验证一个结合了新的分子数据的临床预测规则，以确定低风险非SLN转移的患者亚群，从而填补我们目前知识中的一个重大空白，并减少乳腺癌患者不必要的发病率。

DESCRIPTION (provided by applicant): Sentinel lymph node (SLN) biopsy is a minimally invasive means of accurately staging the axilla in breast cancer patients. While finding negative SLNs avoids axillary lymph node dissection (ALND), the finding of micrometastasis in the SLN mandates a completion ALND. Up to 80% of all SLN-positive patients will have no further disease in the axilla. There is a significant gap in our current knowledge in predicting which SLN- positive patients have a low likelihood of non-SLN metastasis and can therefore avoid ALND. A novel intra- operative RT-PCR based assay (GeneSearch(r)) for detecting SLN micrometastases has been shown to correlate with SLN tumor burden in breast cancer patients. The potential utility of this new technology in predicting which patients will not have further disease in their non-SLNs has not been investigated. Developing a robust clinical prediction rule for non-SLN status using these data will fill this gap in our knowledge and provide timely conclusions, which will have a direct impact on patient care. In order to achieve this over-arching objective, we propose the following specific aims: (1) To determine the impact of quantitative cycle time values of the GeneSearch(r) assay on non-SLN status using both bivariate and multivariable logistic regression analyses, and (2) to create and validate (using bootstrap techniques) a clinical prediction rule to predict non-SLN status in SLN-positive patients using preoperatively- and intraoperatively-available clinicopathologic factors, including data obtained from the GeneSearch(r) assay. We hypothesize that the quantitative RT-PCR cycle time for both mammoglobin (MMG) and cytokeratin 19 (CK19), as evaluated as continuous values using the GeneSearch(r) assay, will be significantly associated with non-SLN metastasis on bivariate analyses. In addition, the cycle time for these markers will predict non-SLN metastasis independent of other factors. We hypothesize that a valid clinical prediction rule can be created using preoperatively- and intraoperatively-available clinicopathologic factors, including data obtained from the GeneSearch(r) assay that will identify a subset of patients in whom the likelihood of non-SLN metastasis is = 5%. It is anticipated that the addition of data from the GeneSearch(r) assay will significantly improve the ability to predict this group of patients over the use of clinicopathologic factors alone. The creation and validation of a robust clinical prediction rule that incorporates novel molecular data to identify a subgroup of patients at low risk of having non-SLN metastasis will fill a significant gap in our current knowledge and will reduce unnecessary morbidity of ALND, helping to meet the NCI's Challenge of eliminating suffering due to cancer by 2015. PUBLIC HEALTH RELEVANCE: Up to 80% of breast cancer patients who have minimal disease in their first draining (sentinel) lymph nodes will have no further disease in their axilla. However, currently there is no accurate means of predicting which patients will not have residual disease, and therefore all patients who have a tumor deposit = 0.2 mm in their sentinel lymph nodes will have the remaining lymph nodes removed -- a procedure that is associated with considerable morbidity. We seek to create and validate a clinical prediction rule, incorporating novel molecular data, to identify a subgroup of patients at low risk of having non-SLN metastasis, thereby filling a significant gap in our current knowledge and reducing unnecessary morbidity for breast cancer patients.