Intraoperative molecular analysis of total tumor load in sentinel lymph node: a new predictor of axillary status in early breast cancer patients

Objective To assess the intraoperative positive sentinel lymph node (SLN) total tumor load (TTL, defined as the amount of CK19 mRNA copies [copies/μL] in all positive SLNs) obtained by one-step nucleic acid amplification (OSNA) and to determine whether it is predictive of non-SLNs involvement. Summary background data The OSNA assay (Sysmex Corporation, Kobe, Japan) is a new diagnostic technique that uses molecular biological techniques to analyze SLN that has been validated as an accurate method for detection of positive SLN. Although the American College of Surgeons Oncology Group Z0011 trial has defined a select cohort of patients in whom a completion axillary lymph node dissection (cALND) may be safely omitted, there are a still a number of patients where prediction of non-SLN metastasis may be helpful for cALND decision making. Multiple studies suggest that specific pathologic characteristics of the primary tumor and the SLN metastases are associated with an increased likelihood of additional positive non-SLN. Methods This is a retrospective multicentric cohort study of 697 patients with cT1-3N0 breast cancer, who had had intraoperative SLN evaluation by OSNA assay with a cALND. TTL is defined as the amount of CK19 mRNA copies number in all positives SLN (copies/μL). Results Univariate logistic regression showed that, in addition to TTL (p < 0.001), the number of affected SLNs (p < 0.001), tumor size (p < 0.001), HER2 status (p = 0.007), and lymphovascular invasion (LVI, p < 0.001) were predictive of ALND status. The multivariate logistic regression analysis showed that TTL is an independent predictor of metastatic non-SLNs, after adjusting for the tumor size, HER2 status, LVI and, in particular, the number of affected SLNs. Conclusions TTL by OSNA is a newly standardized and automated tool that predicts axillary node status better and independently of the number of affected SLNs and the type of surgery. This value can then help clinicians to personalize surgical treatment. Prospective studies will be carried out to determine the clinical impact of this variable in the management of patients.     

术中快速预测乳腺癌非前哨淋巴结转移模型的建立与验证研究

背景与目的:大部分前哨淋巴结(sentinel lymph node,SLN)阳性而接受腋窝淋巴结清扫术(axillary lymph node dissection,ALND)的患者,腋窝非前哨淋巴结(non-sentinel lymph node,nSLN)并没有发生转移,因此准确预测nSLN转移至关重要.该研究将建立基于分子诊断一步核酸扩增法(one-step nucleic acid amplification,OSNA)的术中快速预测乳腺癌nSLN转移的模型,以期有效指导乳腺癌后续治疗.方法:利用2010年OSNA临床试验入组的552例患者中SLN阳性、并接受ALND的103例患者数据,建立基于分子诊断的乳腺癌NSLN转移的预测模型,并利用2015年OSNA临床试验入组的327例患者中61例符合相同条件的患者数据进行验证.结果:原发肿瘤大小、SLN总肿瘤负荷、SLN阳性数及阴性数是NSLN转移的四个独立相关因素,利用这四个因素建立预测列线图,得出建模组患者的受试者工作特征(receiver operating characteristic curve,ROC)曲线的曲线下面积(area under the ROC curve,AUC)为0.814,验证组患者的AUC为0.842.利用验证组61例患者影像学评估的肿瘤大小替代病理大小对本模型进行了验证,得出AUC为0.838,与模型验证性AUC相比差异无统计学意义(P=0.7406).结论:基于分子诊断的乳腺癌预测nSLN转移的模型既可以术中快速预测腋窝淋巴结转移风险,也可以术后常规预测,明显优于其他预测模型,对后续腋窝的处理及放疗靶区勾画具有更好的指导价值.     

Prediction of non-sentinel lymph node metastasis in early breast cancer by assessing total tumoral load in the sentinel lymph node by molecular assay

Introduction

The one-step nucleic acid amplification (OSNA) is a molecular procedure that yields a semiquantitative result for detection of nodal metastasis. Size of metastasis in the sentinel lymph node (SLN) by conventional histology has been described as a predictive factor for additional axillary metastasis. The objective of this study is to quantify intraoperatively the total tumoral load (TTL) in the positive SLNs assessed by OSNA and to determine whether this TTL predicts non-SLN metastasis in patients with clinically node negative early stage breast cancer.

Methods

306 patients with cT1-3N0 invasive breast cancer who had undergone intraoperative SLN evaluation by OSNA were included. TTL was defined as the addition of CK19 mRNA copies of each positive SLN (copies/μL).

Results

TTL was a predictive factor of additional non-SLN metastasis in the complete axillary lymph node dissection (cALND) (OR, 1.67; 95% CI, 1.18–2.35). In the multivariate analysis, the TTL was a predictor of non-SLN metastasis in HR positive patients (OR, 1.69; 95% CI, 1.19–2.41). In our cohort of patients, with a TTL ≤1.2 × 10⁵ copies/μL, there was a specificity of 85.3% and negative predictive value (NPV) of 80%. If we consider only the HR positive patients, with a TTL ≤5 × 10⁵ copies/μL there was a specificity of 86.7% and NPV of 83.7%.

Conclusions

TTL assessed by OSNA assay predicts for additional non-SLN metastasis and this intraoperative tool can help guiding decisions on performing a cALND in breast cancer patients.     

Intraoperative Molecular Analysis of Total Tumor Load in Sentinel Lymph Node: A Predictor of Axillary Status in Early Breast Cancer

Background: Axillary lymph node dissection (ALND) remains the standard of care in breast cancer patients with positive sentinel lymph node (SLN). However, approximately 40–60% of patients with positive SLNs have not developed to non-SLN metastasis and ALND seems to be an overtreatment. The purpose of this study was to analyze predictors and define a specific cut-off of total tumor load (TTL) of CK19 that can be used as a predictive factor of non-SLN metastasis in early breast cancer patients. Materials and Methods: The records of 238 patients with cT1-3N0 breast cancer who had an intraoperative SLN evaluation performed through One-Step nucleic acid (OSNA) assay at Songklanagarind Hospital between 1 January 2015 and 31 December 2019 were examined. Univariate and Multivariate analysis was used to identify clinicopathologic features in SLN-positive patients that predict metastasis to non-SLNs. Finally, receiver operative characteristics (ROC) curves were used to choose an optimal TTL cut-off value. Results: Of a total of 110 patients who had a positive SLN, only 48 (43.64%) were found to have positive nodes in non-SLN. Multivariate analysis revealed that lymphovascular invasion, type of SLN metastasis and SLN TTL (copies/μL) were independent predictors of positive non-SLNs.  TTL cut-off value was 19,000 copies/μL, with an AUC of 0.838 with 72.7% sensitivity and 84.7% specificity to predict non-SLN metastasis. Conclusions: The likelihood of positive non-SLNs in patients who showed a positive SLN correlates with lymphovascular invasion, type of SLN metastasis and SLN TTL (copies/μL). Our result revealed that the patients with a SLN TTL ≥19,000 copies/µl continue to attract the recommendation to proceed with ALND. This cut-off value can then help clinicians to assess which patients would benefit from ALND.     

The MSKCC nomogram for prediction the likelihood of non-sentinel node involvement in a German breast cancer population

Objective To assess whether the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram for prediction of NSLN metastasis is useful in a German breast cancer population and whether the characteristics of the breast tumor and the sentinel lymph node (SLN) are able to predict the likelihood of non-sentinel lymph node (NSLN) metastasis. Methods A total of 545 patients with primary breast cancer and SLN examination were evaluated. The MSKCC nomogram was applied to 98 patients with a positive SLN who subsequently had completion axillary lymph node dissection (ALND). Predictive accuracy was assessed by calculating the area under the receiver-operator characteristic (ROC) curve. The collective was evaluated by correlating the prevalence of NSLN and SLN metastasis to pathological features. Results The MSKCC nomogram achieved a ROC of 0.58 indicating a bad accuracy of the nomogram. Tumor size, histology, lymphovascular infiltration, multifocality, Her-2-neu positivity, and nuclear grade correlated with the probability of SLN metastasis. Histology and primary tumor localization correlated significantly with the probability of NSLN metastasis. Conclusions The MSKCC nomogram did not provide a reliable predictive model in our study population. However, the likelihood of SLN metastasis correlated with the presumed risk factors and no obvious differences between the MSKCC population and our population could be seen. In order to achieve interinstitutional reproducibility, standardization of surgical procedure and of the pathological assessment of the SLN is desirable.     

1个前哨淋巴结阳性乳腺癌患者的腋窝非前哨#br# 淋巴结转移情况及危险因素分析#br#

目的研究1个前哨淋巴结阳性的乳腺癌患者腋窝非前哨淋巴结（NSLN）转移情况及危险因素,为该类患者豁免腋窝淋巴结清扫（ALND）提供指导。方法选取2013年1月至2020年12月在哈尔滨医科大学附属肿瘤医院行前哨淋巴结活检（SLNB）证实仅有1个前哨淋巴结阳性且行ALND的乳腺癌患者465例,根据其腋窝NSLN转移情况,分为NSLN转移组104例,NSLN未转移组361例。比较两组的一般资料,采用二元Logistic回归分析腋窝NSLN转移的独立影响因素。结果465例仅1个前哨淋巴结转移的乳腺癌患者中,104例（224%）发生腋窝NSLN转移。其中,多个亚组患者的腋窝NSLN转移率<10%,如肿瘤T1a+b期的NSLN转移率仅91%、肿瘤T1期且前哨淋巴结数量＞5个的腋窝NSLN转移率仅70%等。单因素分析结果显示,NSLN转移组与NSLN未转移组前哨淋巴结数、肿瘤T分期差异有统计学意义（P<005）。前哨淋巴结2～5个、肿瘤分期为T2～T3期的患者更容易发生腋窝NSLN转移。多因素Logistic回归分析显示,肿瘤分期为T2～T3期、前哨淋巴结数≤5个是患者腋窝NSLN转移的独立危险因素。结论仅有1个前哨淋巴结转移的乳腺癌患者总体腋窝NSLN转移率为224%,肿瘤T分期和前哨淋巴结数为腋窝NSLN转移的影响因素,在对仅1个前哨淋巴结阳性的乳腺癌患者豁免ALND时应重点考虑。     

不同分子分型1～2枚前哨淋巴结阳性乳腺癌免行腋窝淋巴结清扫的多因素分析

目的探讨不同分子分型1～2枚前哨淋巴结（sentinel lymph nodes,SLNs）阳性乳腺癌免行腋窝淋巴结清扫（axillary lymph node dissection,ALND）的临床病理因素,并为临床精准化提供依据。方法回顾性分析2009年6月至2018年6月274例就诊于内蒙古医科大学附属医院和内蒙古医科大学附属人民医院经病理证实的乳腺癌患者的临床病理资料,采用单因素及Logistic多因素分析筛选1～2枚SLN阳性但非前哨淋巴结（nonsentinel lymph node,NSLN）转移率较低的患者,同时明确其与不同分子分型的关系。结果274例1～2枚SLN阳性乳腺癌患者中,NSLN转移率为36.9%（101/274）。HER-2阳性（HR阳性）患者NSLN转移率最高, 占55.3%（21/38）;三阴性乳腺癌（triple negative breast cancer,TNBC）患者中NSLN转移率最低,占18.5%（5/27）。Luminal B型（HER-2阴性）乳腺癌患者的NSLN转移率明显高于Luminal A型（P=0.010）和TNBC患者（P=0.011）;HER-2阳性（HR阳性）乳腺癌患者的NSLN转移率明显高于Luminal A型（P=0.002）和TNBC患者（P=0.003）。 Logistic多因素分析显示,SLN转移数目（OR=4.022, 95%CI为2.348～6.889,P<0.001）,SLN检测（OR=3.846, 95%CI为1.541～9.600,P=0.004）,组织学分级（P<0.001）和分子分型（P=0.004）是1～2枚SLN阳性乳腺癌NSLN转移的独立影响因素。结论Luminal B型（HER-2阴性）和HER-2阳性（HR阳性）患者的NSLN阳性率较高,SLN转移数目、SLN检测、组织学分级和分子分型是NSLN转移的独立影响因素。      

早期乳腺癌腋窝前哨淋巴结阳性患者腋窝非前哨淋巴结转移风险预测

目的 分析前哨淋巴结活检(SLNB)1~2个阳性乳腺癌患者中非前哨淋巴结(NSLN)转移的影响因素并构建预测模型。方法 回顾分析2008-2014年中国医学科学院北京协和医学院肿瘤医院未行新辅助化疗前哨淋巴结 1~2个阳性并行腋窝淋巴结清扫的乳腺癌患者的临床病理因素。计数资料组间比较采用χ²检验,多因素分析采用Logistic回归模型。以AUC值和校正曲线对Nomogram预测模型进行评估。结果 共 270例患者纳入研究,87例(32.2%)存在NSLN转移。中位年龄46(21~80)岁,中位SLN送检个数4(1~10)个,中位腋窝淋巴结清扫个数20(10~41)个。单因素分析结果显示病理分级、SLN宏转移、阳性SLN个数和阴性SLN个数是腋窝NSLN转移的影响因素(P=0.001~0.045)。多因素分析结果显示病理分级、阳性SLN个数和阴性SLN个数是NSLN转移的独立影响因素(P=0.000~0.041)。乳腺癌NSLN转移Nomogram预测模型AUC=0.70,当预测患者的NSLN转移率≤15%时,假阴性率仅为10.5%。结论 Nomogram预测模型可作为临床医师进行腋窝处理时的决策参考,对于NSLN转移概率低的患者可以避免行腋窝淋巴结清扫或腋窝放疗。     

Clinicopathological parameters and biological markers predicting non-sentinel node metastasis in sentinel node-positive breast cancer patients

The value of complete axillary lymph node dissection (ALND) has been questioned in invasive breast cancer (IBC) patients with positive sentinel lymph nodes (SLNs) who have no non-sentinel lymph node (NSLN) metastases. Because biological markers have not been systematically studied in this setting, we sought to identify clinicopathological characteristics and biological markers for predicting NSLN metastases in SLN-positive IBC patients. Two hundred and five IBC patients who had at least one positive SLN and received SLN biopsy and ALND were included in our study. We examined the clinicopathological characteristics of their primary tumors, SLNs and NSLNs. We also evaluated the biological markers of the primary tumors by tissue microarray and immunohistochemistry. Of the 205 patients with SLN metastases, 89 patients (43.4%) had additional metastases in NSLNs. The following factors were found to be associated with NSLN metastases: peritumoral lymphovascular invasion (p=0.01), two or more metastatic SLNs (p<0.01), SLN metastasis >2.0 mm (p<0.01) and extra-nodal extension (p<0.01). Primary tumors >2.0 cm showed more NSLN metastases, but the association was statistically insignificant (p=0.08). In contrast, NSLN metastases were not associated with histologic grade, histologic type, presence of extensive intraductal component, presence of high grade ductal carcinoma in situ and number of harvested SLNs. Biological markers such as E-cadherin, CD44, cyclin D1, p21, ER, PR, c-erbB2, p53, Ki-67, luminal (CK7, CK18, CK19) and basal (CK5, p63) markers were not useful predictors of NSLN metastasis in IBC patients with SLN metastases. Multivariate analysis revealed that SLN metastasis >2.0 mm (p=0.01), two or more metastatic SLNs (p=0.03) and extranodal extension (p<0.01) were independent predictors of NSLN metastasis. For the prediction of NSLN metastasis in IBC patients with SLN metastases, light microscopic evaluation of the number, size and extranodal extension of metastatic SLNs by hematoxylin and eosin staining appeared to be critical. However, the biological markers of primary tumor characterized by immunohistochemical staining, such as luminal and basal markers, hormone receptors, E-cadherin, CD44, cyclin D1, p21, c-erb-B2, p53 and Ki-67, did not appear to be helpful predictors.     

Treatment implications of a positive sentinel lymph node biopsy for patients with early-stage breast carcinoma.

BACKGROUND: Sentinel lymph node (SLN) mapping and biopsy is emerging as an alternative to axillary lymph node dissection (ALND) in determining the lymph node status of patients with early-stage breast carcinoma. The hypothesis of the technique is that the SLN is the first lymph node in the regional lymphatic basin that drains the primary tumor. Non-SLN (NSLN) metastasis in the axilla is unlikely if the axillary SLN shows no tumor involvement, and, thus, further axillary interference may be avoided. However, the optimal treatment of the axilla in which an SLN metastasis is found requires ongoing evaluation. The objectives of this study were to evaluate the predictors for NSLN metastasis in the presence of a tumor-involved axillary SLN and to examine the treatment implications for patients with early-stage breast carcinoma. METHODS: Between June 1998 and May 2000, 167 patients participated in the pilot study of SLN mapping and biopsy at Westmead Hospital. SLNs were identified successfully and biopsied in 140 axillae. All study patients also underwent ALND. The incidence of NSLN metastasis in the 51 patients with a SLN metastasis was correlated with clinical and pathologic characteristics. RESULTS: Of 51 patients with a positive SLN, 24 patients (47%) had NSLN metastases. The primary tumor size was the only significant predictor for NSLN involvement. NSLN metastasis occurred in 25% of patients (95% confidence interval [95%CI], 10-47%) with a primary tumor size 20 mm (P = 0.005). The size of the SLN metastasis was not associated significantly with NSLN involvement. Three of 7 patients (43%) with an SLN micrometastasis (< 1 mm) had NSLN involvement compared with 38 of 44 patients (48%) with an SLN macrometastasis (> or = 1 mm). CONCLUSIONS: The current study did not identify a subgroup of SLN positive patients in whom the incidence of NSLN involvement was low enough to warrant no further axillary interference. At present, a full axillary dissection should be performed in patients with a positive SLN.     

Multi-Institutional Comparison of Non-sentinel Lymph Node Predictive Tools in Breast Cancer Patients with High Predicted Risk of Further Axillary Metastasis

Although axillary lymph node dissection (ALND) has been the standard intervention in breast cancer patients with sentinel lymph node (SLN) metastasis, only a small proportion of patients benefit from this operation, because most do not harbor additional metastases in the axilla. Several predictive tools have been constructed to identify patients with low risk of non-SLN metastasis who could be candidates for the omission of ALND. In the present work, predictive nomograms were used to predict a high (>50 %) risk of non-SLN metastasis in order to identify patients who would most probably benefit from further axillary treatment. Data of 1000 breast cancer patients with SLN metastasis and completion ALND from 5 institutions were tested in 4 nomograms. A subset of 313 patients with micrometastatic SLNs were also tested in 3 different nomograms devised for the micrometastatic population (the high risk cut-off being 20 %). Patients with a high predicted risk of non-SLN metastasis had higher rates of metastasis in the non-SLNs than patients with low predicted risk. The positive predictive values of the nomograms ranged from 44 % to 64 % with relevant inter-institutional variability. The nomograms for micrometastatic SLNs performed much better in identifying patients with low risk of non-SLN involvement than in high-risk-patients; for the latter, the positive predictive values ranged from 13 % to 20 %. The nomograms show inter-institutional differences in their predictive values and behave differently in different settings. They are worse in identifying high risk patients than low-risk ones, creating a need for new predictive models to identify high-risk patients.     

Predictors of tumour involvement in remaining axillary lymph nodes of breast cancer patients with positive sentinel lymph node.

AIMS: To characterize the various clinicopathologic features in cases of breast cancer with positive sentinel lymph nodes (SLNs), in order to determine factors that might help in predicting the involvement of the non-SLNs. METHODS: A retrospective database review was performed of 726 breast cancer patients with stage 0-II, in whom SLNs were successfully identified. One hundred eighty-five of these patients showed positive SLNs, and subsequently underwent axillary lymph node dissection (ALND). These cases were divided into two groups based on the presence or absence of metastases in the non-SLNs, i.e. positive non-SLNs (NSLN+; 81 cases) and negative non-SLNs (NSLN-; 104 cases). RESULTS: Multivariate analysis revealed that a larger size of the primary tumour (>2.0cm), presence of lymphatic invasion, larger size of the largest SLN metastasis (>2mm), and a 100% metastatic rate in the SLNs (number of positive SLNs/number of harvested SLNs) were significantly associated with NSLN+. Among the cases in which all the four factors were present, 73% (30/41) were found to have NSLN+. CONCLUSION: We found four independent predictors in relation to non-SLN metastasis. Although these factors might be useful for determining the need of additional ALND, it would seem that even the presence of all of these four factors in combination may be insufficient to safely omit ALND. Thus, until further evidence is accumulated from the results of large clinical trials, ALND would still be recommended for patients with SLN metastasis.     

Routine clinical use of the one-step nucleic acid amplification assay for detection of sentinel lymph node metastases in breast cancer patients: results of a multicenter study in Japan

BACKGROUND:

The objective of this study was to confirm, by means of a multicenter study conducted in Japan, the reliability and usefulness of the one‐step nucleic acid amplification (OSNA) assay in routine clinical use for sentinel lymph node biopsy (SLNB) of breast cancer patients.

METHODS:

Patients with Tis‐T2N0M0 breast cancer who underwent SLNB before systemic chemotherapy comprised the study cohort. A whole sentinel lymph node (SLN) was examined intraoperatively with the OSNA assay except for a 1‐mm‐thick, central slice of the lymph node, which underwent pathologic examination after the operation. For patients who underwent axillary dissection, non‐SLNs were examined with routine pathologic examination.

RESULTS:

In total, 417 SLNBs from 413 patients were analyzed. SLN metastases were detected with greater sensitivity by the OSNA assay than by pathologic examination (22.5% vs 15.8%; P < .001), as expected from the difference in size of the specimens examined. Patients who had SLN metastases assessed with the OSNA assay proved to harbor non‐SLN metastases with an overall risk ratio of 33.7%. The risk of non‐SLN metastasis was significantly lower for patients who had positive SLNs assessed as OSNA+ than for those who had SLNs assessed as OSNA++ (17.6% vs 44%; P = .012).

CONCLUSIONS:

The OSNA assay can be used for routine clinical SLNB, and its assessment for volume of metastasis may be a powerful predictive factor for non‐SLN metastasis. Further studies with more patients are needed to confirm the usefulness of this assay for selection in the clinical setting of patients who do not need axillary dissection. Cancer 2012;3477–3483. © 2012 American Cancer Society.     

Impact of CD44+CD24- cells on non-sentinel axillary lymph node metastases in sentinel node-positive breast cancer

Although complete axillary lymph node dissection (ALND) is the standard for evaluating axillary status after the identification of a positive sentinel lymph node (SLN) in breast cancer; approximately 40-60% of SLN-positive patients have negative non-SLN. In this study, to explore putative breast cancer stem cells with CD44+CD24- in the SLN, we retrospectively analyzed the expression of CD44+CD24- on metastatic tumor cells within SLNs as a predictive factor for positive non-SLNs (NSLNs). We tested 271 patients for SLNs using serial sectioning with cytokeratin immunohistochemistry (IHC) and hematoxylin-eosin staining and identified 67 patients who had a positive SLN biopsy and complete ALND. CD44 and CD24 expression was detected using double-staining IHC. Twenty-eight (41.8%) out of 67 patients had positive NSLN metastases. Seven positive SLNs with micrometastases were not available for the evaluation of CD24 and CD44 expression. Out of the remaining 60?patients, 19?(31.7%), 44?(73.83%) and 37?(61.7%) patients had CD24+, CD44+ and CD44+CD24- metastatic tumor cells in SLNs, respectively. Positive NSLN metastasis was significantly associated with the primary tumor size (P=0.004), CD24- expression (P=0.04), CD44+ expression (P=0.01) and CD44+CD24- expression (P=0.02). This report provides the first evidence of the existence of a putative stem-like phenotype within the SLN, which is significantly associated with positive NSLN in early breast cancer patients.     

Sentinel lymph node analysis in breast cancer: contribution of one-step nucleic acid amplification (OSNA)

One-step nucleic acid amplification (OSNA, Sysmex, Kobe, Japan) offers an excellent opportunity for accurate exhaustive sentinel lymph node (SLN) examination in breast cancer patients. Calibrated with conventional postoperative histology, this molecular technique yields comparable results intraoperatively, expressed as micrometastasis, macrometastasis or no metastasis depending on the CK19 mRNA copy number amplified in SLN lysates. We applied OSNA to detect metastasis in 810 SLNs from 367 patients with early stage breast cancer. We compared the rate of OSNA-positive SLNs in patients with invasive breast cancer (< 2 cm) versus the rate observed in a historical cohort using conventional histological examination of SLNs. No significant difference was observed, the OSNA assay was positive in 24.4% of patients, compared with positive histology in 24.8% in the historical cohort if including patients with isolated tumour cell (ITC) and in 23.4% excluding them. Opportunities for optimised patient management using OSNA are discussed: intraoperative detection of OSNA-positive SLNs enables axillary lymph node dissection (ALND) during the same procedure; standard OSNA techniques enable the establishment of homogeneous groups based on examination of whole SLNs for valid comparisons between different centres.     

Three models for predicting the risk of non-sentinel lymph node metastasis in Japanese breast cancer patients

Background

Axillary lymph node dissection (ALND) is the standard procedure for breast cancer with sentinel lymph node (SLN) metastasis. However, additional nodal metastasis is occasionally detected (<40 % cases) during complete ALND in patients with SLN metastasis. Several models have been developed to predict the non-SLN status of patients with SLN involvement. We evaluated 3 of these mathematical models independently.

Patients and Methods

A retrospective review was performed for 102 consecutive breast cancer patients with positive SLN biopsy who underwent ALND. We evaluated the area under the receiver operating characteristic curve (AUC) to determine the predicted risk of non-SLN metastases by using 3 mathematical models (from Memorial Sloan-Kettering Cancer Center (MSKCC), Stanford University, and Cambridge University).

Results

Of the 102 patients who underwent SLN biopsy, 47 (46.0 %) had a positive non-sentinel axillary lymph node metastasis. The AUC values were 0.71, 0.65, and 0.62 for the MSKCC, Stanford, and Cambridge nomograms, respectively.

Conclusions

None of the 3 nomograms had reasonable predictive power for the Japanese population. However, these nomograms can help individualize the surgical treatment of patients with positive SLN when the likelihood of further axillary metastasis is low. Each nomogram has its own characteristics for prediction of the risk of non-SLN metastasis.     

MSKCC和SOC模型预测中国乳腺癌患者非前哨淋巴结转移的验证比较研究

  目的   验证纪念斯隆-凯特琳癌症中心（Memorial Sloan-Kettering Cancer Center,MSKCC）模型和斯坦福大学模型（Stanford Online Calculator,SOC）预测中国前哨淋巴结（sentinel lymph node,SLN）阳性乳腺癌患者非前哨淋巴结（non-sentinel lymph node,NSLN）转移的能力并进行比较。   方法   收集120例SLN阳性的乳腺癌病例验证MSKCC和SOC模型,通过受试者工作特征曲线（Receiver Operating Characteristic Curve,ROC曲线）下面积（Area Under the Curve,AUC）、不同截断值的预测能力来比较两个模型在中国乳腺癌患者中的应用价值。   结果   用MSKCC和SOC模型验证120例中国乳腺癌患者,AUC分别为0.688和0.734。取10%为截断值,MSKCC和SOC模型的假阴性率均为4.4%,阴性预测值分别为75.0%和90.0%。取90.0%为截断值,MSKCC和SOC模型的假阳性率分别为0.0%和6.7%,阳性预测值分别为100.0%和68.8%。   结论   用MSKCC和SOC模型预测中国乳腺癌NSLN转移,结果皆劣于原始研究,SOC模型的预测能力略优于MSKCC模型。      

Is it Possible to Predict Non Sentinel Node Positivity on the Basis of mRNA Copy Numbers of CK19 Receptor in Breast Cancer?

AimsTo determine if there is any correlation between the number of positive non-sentinel lymph nodes (NSLN) and the mRNA copy numbers of cytokeratin 19 receptor on one step nucleic acid amplification (OSNA) in the sentinel lymph node (SLN).MethodsAn 8-year retrospective study of consecutive patients who had primary surgery and sentinel node biopsy for breast cancer from January 2011 to December 2018 was carried out. All these patients had intra-operative analysis of sentinel lymph nodes by OSNA. Patients who had neoadjuvant chemotherapy or neoadjuvant endocrine therapy were excluded.ResultsThere were 1159 patients with an age range of 24 to 90 years and a mean age of 63 years in this study. A total of 1324 SLNs were analyzed by OSNA. Macrometastasis was found in 120 patients and they underwent axillary lymph node dissection (ALND). A total of 2405 NSLNs were analyzed. Of the patients who had ALND, 51 (43%) patients had negative NSLNs and 69 (57%) had positive NSLNs. The mean mRNA copy numbers respectively for the 2 groups were 853,665 and 609,855. The difference between the means is not statistically significant (P = 0.82). Also the Receiver Operating Characteristic (ROC) Curve of the total CK-19 mRNA copy number for both groups-negative and positive NSLN were almost identical (Figure 3) indicating mRNA copy numbers cannot be used to discriminate between positive and negative non-sentinel lymph nodes.ConclusionIt is clear from our study that in patients who have ALND due to macromets on OSNA, there is no correlation between the total tumor load as represented by mRNA copy numbers and the likelihood of positive non-sentinel lymph nodes. We therefore cannot rely solely on the mRNA copy numbers to decide on ALND.     

Validation of Three Breast Cancer Nomograms and a New Formula for Predicting Non-sentinel Lymph Node Status

Background: The aim of the study was to evaluate the available breast nomograms (MSKCC, Stanford, Tenon)to predict non-sentinel lymph node metastasis (NSLNM) and to determine variables for NSLNM in SLN positivebreast cancer patients in our population. Materials and Methods: We retrospectively reviewed 170 patientswho underwent completion axillary lymph node dissection between Jul 2008 and Aug 2010 in our hospital. Wevalidated three nomograms (MSKCC, Stanford, Tenon). The likelihood of having positive NSLNM based onvarious factors was evaluated by use of univariate analysis. Stepwise multivariate analysis was applied to estimatea predictive model for NSLNM. Four factors were found to contribute significantly to the logistic regressionmodel, allowing design of a new formula to predict non-sentinel lymph node metastasis. The AUCs of the ROCswere used to describe the performance of the diagnostic value of MSKCC, Stanford, Tenon nomograms and ournew nomogram. Results: After stepwise multiple logistic regression analysis, multifocality, proportion of positiveSLN to total SLN, LVI, SLN extracapsular extention were found to be statistically significant. AUC results wereMSKCC: 0.713/Tenon: 0.671/Stanford: 0.534/DEU: 0.814. Conclusions: The MSKCC nomogram proved to bea good discriminator of NSLN metastasis in SLN positive BC patients for our population. Stanford and Tenonnomograms were not as predictive of NSLN metastasis. Our newly created formula was the best predictiontool for discriminate of NSLN metastasis in SLN positive BC patients for our population. We recommend thatnomograms be validated before use in specific populations, and more than one validated nomogram may beused together while consulting patients.     

A Breast Cancer Nomogram for Prediction of Non-Sentinel Node Metastasis - Validation of Fourteen Existing Models

Background: To avoid performing axillary lymph node dissection (ALND) for non-sentinel lymph node(SLN)-negative patients with-SLN positive axilla, nomograms for predicting the status have been developed inmany centers. We created a new nomogram predicting non-SLN metastasis in SLN-positive patients with invasivebreast cancer and evaluated 14 existing breast cancer models in our patient group. Materials and Methods:Two hundred and thirty seven invasive breast cancer patients with SLN metastases who underwent ALND wereincluded in the study. Based on independent predictive factors for non-SLN metastasis identified by logisticregression analysis, we developed a new nomogram. Receiver operating characteristics (ROC) curves for themodels were created and the areas under the curves (AUC) were computed. Results: In a multivariate analysis,tumor size, presence of lymphovascular invasion, extranodal extension of SLN, large size of metastatic SLN,the number of negative SLNs, and multifocality were found to be independent predictive factors for non-SLNmetastasis. The AUC was found to be 0.87, and calibration was good for the present Ondokuz Mayis nomogram.Among the 14 validated models, the MSKCC, Stanford, Turkish, MD Anderson, MOU (Masaryk), Ljubljana,and DEU models yielded excellent AUC values of > 0.80. Conclusions: We present a new model to predict thelikelihood of non-SLN metastasis. Each clinic should determine and use the most suitable nomogram or shouldcreate their own nomograms for the prediction of non- SLN metastasis.