Validating the MSKCC nomogram and a clinical decision rule in the prediction of non-sentinel node metastases in a Portuguese population of breast cancer patients

Total Tumor Load to assist in the decision for additional axillary surgery in the positive sentinel node breast cancer patients

The Total Tumor Load (TTL) concept has been demonstrated to accurately predict the status of the non-sentinel lymph nodes (NSLN) in breast cancer patients. In 2019, our center implemented the TTL cut-off of 30,000 CK19 mRNA copies/μL as sole criterion for deciding on performing ALND. This retrospective, unicentric, study analyzed 87 cT1-3N0 breast cancer patients treated consecutively in a period of two years and aimed to evaluate the performance of this criterion. Secondary objectives included the comparison of the criterion versus our previous Clinical Decision Rule (CDR) versus ACOSOG Z0011 criteria for avoiding an ALND in proportion of patients spared an ALND and in proportion of patients left with a surgically untreated metastasized axilla. An interim analysis revealed new TTL cut-offs for deciding on performing an ALND. The 30,000 CK19 mRNA copies/μL criterion yielded an area under the ROC Curve (AUC) of 0.849, a false positive (FP) rate of 30.1% and a positive predictive value (PPV) of 38.9%. The 30,000 CK19 mRNA copies/μL criterion spared 58.6% of the patients an ALND versus 41.4% with CDR versus 73.6% with Z0011 and left 0.0% patients with a surgically untreated metastasized axilla versus 21.4% with CDR versus 42.9% with Z0011. The new TTL cut-off of 260,000 CK19 mRNA copies/μL for deciding on an ALND yielded an AUC of 0.753, a FP rate of 13.7% and a PPV of 47.4%. This new criterion spared 78.2% of the study sample an ALND and left 35.7% of metastasized axillae surgically untreated. This study emphasizes the need to find a new balance between locoregional control and the morbidity associated with Berg levels I + II axillary lymph node dissection.

Development of a prediction model based on LASSO regression to evaluate the risk of non-sentinel lymph node metastasis in Chinese breast cancer patients with 1-2 positive sentinel lymph nodes

This study aimed to develop an intraoperative prediction model to evaluate the risk of non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer patients with 1–2 positive sentinel lymph nodes (SLNs). The clinicopathologic data of 714 patients with 1–2 positive SLNs were investigated. Univariate and multivariate analyses were performed to identify the risk factors of NSLN metastasis. A new mathematical prediction model was developed based on LASSO and validated in an independent cohort of 131 patients. The area under the receiver operating characteristic curve (AUC) was used to quantify performance of the model. Patients with NSLN metastasis accounted for 37.3% (266/714) and 34.3% (45/131) of the training and validation cohorts, respectively. A LASSO regression-based prediction model was developed and included the 13 most powerful factors (age group, clinical tumour stage, histologic type, number of positive SLNs, number of negative SLNs, number of SLNs dissected, SLN metastasis ratio, ER status, PR status, HER2 status, Ki67 staining percentage, molecular subtype and P53 status). The AUCs of training and validation cohorts were 0.764 (95% CI 0.729–0.798) and 0.777 (95% CI 0.692–0.862), respectively. We presented a new prediction model with excellent clinical applicability and diagnostic performance for use by clinicians as an intraoperative clinical tool to predict risk of NSLN metastasis in Chinese breast cancer patients with 1–2 positive SLNs and make the final decisions regarding axillary lymph node dissection.

Sentinel node total tumour load as a predictive factor for non-sentinel node status in early breast cancer patients - The porttle study

OSNA is a molecular assay for the detection of sentinel node metastasis. TTL emerged as a concept that seems to accurately predict the status of the NSN. Authors tried to confirm this motion. This is a retrospective and multicentric study that analyzed 2164 patients, 579 of whom had positive SN and completion AD. Logistic regression models were performed in order to identify a suitable cutoff to identify patients who benefit from AD. Univariate and multivariate regression analysis showed a relationship between TTL>30000 and the presence of NSN metastasis (OR 2.84, CI 1.99-4.08, p < 0.001). Logistic regression indicated that the cutoff of 30000 copies/μL better discriminates patients with NSN positivity and allows wide use of these criteria. This cutoff value may safely assist clinicians and patients to decide to proceed or not with an AD.

Factors associated with locoregional and metastatic breast cancer at diagnosis in a Southern Portuguese registry in the period 2005-2012

Breast cancer (BC) is the most frequent malignancy in Portuguese women, and more than half of the registered cases live in the south of the country. The main of this study was to characterize patients with locoregional and metastatic incident BC living in the Southern Portuguese and Madeira regions in 2005-2012 according to demographic, clinical and contextual characteristics. Additionally it aimns to find the associations and relative influences of these factors with locoregional or metastatic disease at diagnosis. After a descriptive approach, binary logistic regression models were used to estimate factors related to the presence of metastatic disease at diagnosis. A final multiple regression model was developed and presented graphically as a nomogram. The median age at diagnosis was 60.84 years, being statistically lower in locoregional cases (P < 0.001). Most patients presented a locoregional disease (78.4%) of unspecified location (44.5%) and had a ductal carcinoma (73.1%). The Lisbon region represented 50.5% of the analyzed cases. Metastatic disease significantly decreased over the period under analysis ( ≈ 7%/year). Demographic (age at diagnosis ≥ 50 years), clinical (lobular and 'other' morphologies, unspecified location) and contextual (residence in Portalegre) characteristics were statistically correlated with the presence of metastatic disease at the time of BC diagnosis in univariate logistic regression, with all but the last maintaining their significance in a multivariate model. Cases with metastatic BC disease at diagnosis are decreasing; however, additional information on their characteristics can improve the alignment of public health strategies, thus strengthening this trend, and contributing to the development of a graphically tailored screening tool.

Factors Influencing Non-sentinel Node Involvement in Sentinel Node Positive Patients and Validation of MSKCC Nomogram in Indian Breast Cancer Population

Current guidelines recommend completion axillary lymphnode dissection (ALND) when sentinel lymphnode (SLN) contains metastatic tumor deposit. In consequent ALND sentinel node is the only node involved by tumor in 40-70 % of cases. Recent studies demonstrate the oncologic safety of omitting completion ALND in low risk patients. Several nomograms (MSKCC, Stanford, MD Anderson score, Tenon score) had been developed in predicting the likelihood of additional nodes metastatic involvement. We evaluated accuracy of MSKCC nomogram and other clinicopathologic variables associated with additional lymph node metastasis in our patients. A total of 334 patients with primary breast cancer patients underwent SLN biopsy during the period Jan 2007 to June 2014. Clinicopathologic variables were prospectively collected. Completion ALND was done in 64 patients who had tumor deposit in SLN. The discriminatory accuracy of nomogram was analyzed using Area under Receiver operating characteristic curve (ROC). SLN was the only node involved with tumor in 69 % (44/64) of our patients. Additional lymph node metastasis was seen in 31 % (20/64). On univariate analysis, extracapsular infiltration in sentinel node and multiple sentinel nodes positivity were significantly associated (p < 0.05) with additional lymph node metastasis in the axilla. Area under ROC curve for nomogram was 0.58 suggesting poor performance of the nomogram in predicting NSLN involvement. Sentinel nodes are the only nodes to be involved by tumor in 70 % of the patients. Our findings indicate that multiple sentinel node positivity and extra-capsular invasion in sentinel node significantly predicted the likelihood of additional nodal metastasis. MSKCC nomogram did not reliably predict the involvement of additional nodal metastasis in our study population.

Risk factors for sentinel lymph node metastasis and validation study of the MSKCC nomogram in breast cancer patients

OBJECTIVE

To evaluate the risk factors for sentinel lymph node metastasis and validate the value of the Memorial Sloan-Kettering Cancer Center nomogram for the prediction of sentinel lymph node metastasis in breast cancer patients.

METHODS

A sentinel lymph node biopsy database containing 1227 consecutive breast cancer patients (416 patients with at least one positive sentinel lymph node) was retrospectively analyzed. The predictive value of the Memorial Sloan-Kettering Cancer Center nomogram was calculated by the trend line and the area under the receiver-operator characteristic curve. Meanwhile, predictors for sentinel lymph node metastasis were also evaluated.

RESULTS

Tumor size, histological grade, lymphovascular invasion, mulifocality, estrogen receptor and progesterone receptor status were significant independent predictors for sentinel lymph node metastasis (all P<0.01). The Memorial Sloan-Kettering Cancer Center nomogram presented an area under the receiver-operator characteristic curve value of 0.730. Patients with predictive value<16% had a frequency of sentinel lymph node metastasis of 0.9%. Those with values larger than 70% had a frequency of 96.2%.

CONCLUSIONS

The risk factors for sentinel lymph node metastasis in our study were consistent with those in the Memorial Sloan-Kettering Cancer Center nomogram. The Memorial Sloan-Kettering Cancer Center nomogram is a useful tool that could accurately predict the probability of sentinel lymph node metastasis in our breast cancer patients. Axillary surgical staging might be avoided in patients with a predictive value of <16% and axillary lymph node dissection might be done directly in those with a predictive value >70%, while other patients should still accept sentinel lymph node biopsy.