Predicting Non-Sentinel Node Metastasis in Breast Cancer Patients

描述（由申请人提供）：前哨淋巴结（SLN）活检是一种准确对乳腺癌患者腋窝进行分期的微创方法。虽然发现阴性SLN避免了腋窝淋巴结清扫术（ALND），但发现SLN中的微转移要求完成ALND。高达80%的所有SLN阳性患者的腋窝将没有进一步的疾病。在预测哪些SLN阳性患者非SLN转移的可能性较低并因此可以避免ALND方面，我们目前的知识存在显著差距。一种用于检测前哨淋巴结微转移的新型术中RT-PCR检测方法（GeneSearch（r））已被证明与乳腺癌患者的前哨淋巴结肿瘤负荷相关。尚未研究这项新技术在预测哪些患者的非前哨淋巴结不会出现进一步疾病方面的潜在效用。使用这些数据开发一个强大的非SLN状态的临床预测规则将填补我们知识的这一空白，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，我们提出以下具体目标：（1）使用双变量和多变量逻辑回归分析确定GeneSearch（r）测定的定量循环时间值对非SLN状态的影响，（2）创建和验证（使用bootstrap技术）使用术前和术中-可用的临床病理学因素，包括从GeneSearch（r）分析获得的数据。我们假设，使用GeneSearch（r）分析作为连续值评估的乳腺珠蛋白（MMG）和细胞角蛋白19（CK 19）的定量RT-PCR循环时间与双变量分析中的非SLN转移显著相关。此外，这些标志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学因素创建有效的临床预测规则，包括从GeneSearch（r）检测中获得的数据，该检测将识别非SLN转移可能性≥ 5%的患者子集。预计添加来自GeneSearch（r）分析的数据将显著提高预测这组患者的能力，而不是单独使用临床病理学因素。创建和验证一个强大的临床预测规则，结合新的分子数据，以确定一个亚组的患者在低风险的非SLN转移将填补一个显着的差距，在我们目前的知识，并将减少不必要的发病率ALND，有助于满足NCI的挑战，消除痛苦，由于癌症到2015年。公共卫生相关性：高达80%的乳腺癌患者在其第一引流（前哨）淋巴结中有轻微疾病，其腋窝将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疾病，因此，所有在前哨淋巴结中有肿瘤存款= 0.2 mm的患者都将切除剩余的淋巴结-这是一种与相当高的发病率相关的手术。我们试图创建和验证一个临床预测规则，结合新的分子数据，以确定一个亚组的患者在低风险的非SLN转移，从而填补了我们目前的知识和减少不必要的发病率乳腺癌患者的显着差距。

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.