Oncologic outcomes of de-escalating axillary treatment in clinically node-positive breast cancer patients treated with neoadjuvant systemic therapy - A two center cohort study.

BACKGROUND: The aim of the present study was to report the 5-year axillary recurrence-free interval (aRFI) in clinically node-positive breast cancer patients treated according to a de-escalating axillary treatment protocol after neoadjuvant systemic therapy (NST). METHODS: All patients diagnosed in two hospitals between October 2014 and March 2021 were identified retrospectively. Data on diagnostic workup, treatment and follow-up was collected. Adjuvant axillary treatment was considered based on the initial staging using 18F-FDG PET/CT and the results of axillary lymph node marking with a radioactive-iodine seed protocol or a targeted axillary dissection procedure. Follow-up was updated until 27th April 2024. Kaplan-Meier curves were calculated to report the 5-year aRFI with corresponding 95 % confident intervals (95%-CI). RESULTS: A total of 199 patients were included. Axillary pathological complete response was reported in 66 (33.2 %). Based on the treatment protocol and initial clinical staging, no adjuvant axillary treatment was indicated in 30 patients (15 %), while 139 (70 %) received axillary radiotherapy without performance of an axillary lymph node dissection (ALND). The remaining 30 patients (15 %) underwent an ALND with additional locoregional radiotherapy. A median follow-up of 62 months (30-106) showed that 4 (2 %) patients experienced an axillary recurrence after 7, 8, 36 and 36 months, respectively. In all 4 patients, synchronous distant metastases were diagnosed. The estimated 5-year aRFI was 97.8 % (95%-CI 95.6-99.9 %) CONCLUSION: Although longer follow-up should be awaited before final conclusions can be drawn regarding the oncological safety of this approach, the implementation of a de-escalating axillary treatment protocol appears to be safe since the estimated 5-year aRFI is 97.8 %.

Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool.

BACKGROUND: This study aimed to develop an easy to use prediction model to predict the risk of having a total of 1 to 2, ≥3, or ≥4 positive axillary lymph nodes (LNs), for patients with sentinel lymph node (SLN) positive breast cancer. METHODS: Data of 911 SLN positive breast cancer patients were used for model development. The model was validated externally in an independent population of 180 patients with SLN positive breast cancer. RESULTS: Final pathology after ALND showed additional positive LN for 259 (28%) of the patients. A total of 726 (81%) out of 911 patients had a total of 1 to 2 positive nodes, whereas 175 (19%) had ≥3 positive LNs. The model included three predictors: the tumor size (in mm), the presence of a negative SLN, and the size of the SLN metastases (in mm). At external validation, the model showed a good discriminative ability (area under the curve = 0.82; 95% confidence interval = 0.74-0.90) and good calibration over the full range of predicted probabilities. CONCLUSION: This new and validated model predicts the extent of nodal involvement in node-positive breast cancer and will be useful for counseling patients regarding their personalized axillary treatment.

Emergent Treatment of Ruptured Axillary Artery Aneurysm.

The axillary artery aneurysm (AxAA) is a rare entity, with a diverse range of proposed etiologic mechanisms. Although usually asymptomatic, thromboembolic or hemorrhagic complications leave many with vascular and neurologic compromise. Both open and endovascular treatment approaches have been reported. However, no consensus has been reached on the management of AxAAs. This case illustrates a unique emergent treatment approach for a ruptured AxAA, involving endovascular plugging and immediate subsequent open hematoma evacuation. Although there was no restoration of vessel continuity, reasonable recovery of motor function on follow-up suggests this treatment approach may be considered in emergent settings.

A Dutch Prediction Tool to Assess the Risk of Additional Axillary Non-Sentinel Lymph Node Involvement in Sentinel Node-Positive Breast Cancer Patients.

BACKGROUND: Multiple predictive systems have previously been developed to identify the sentinel lymph node (SLN)-positive patients at low risk of additional axillary non-SLN involvement and for whom completion axillary lymph node dissection (ALND) could be avoided. However, previous studies showed that these tools had poor performance in Dutch patients with breast cancer, probably owing to variations in pathology settings and differences in population characteristics. The aim of the present study was to develop a predictive tool for the risk of non-SLN involvement in a Dutch population with SLN-positive breast cancer. MATERIALS AND METHODS: The data from 513 patients with SLN-positive breast cancer at 10 participating hospitals, who had undergone ALND from January 2007 to December 2008 were studied. The uni- and multivariable associations of predictors for non-SLN metastases were analyzed, and a predictive model was developed. The discriminatory ability of the model was measured by the area under the receiver operating characteristic curve (AUC) and the agreement between predicted probabilities and observed frequencies was visualized by a calibration plot. RESULTS: A predictive model was developed that included the 2 strongest predictors: the size of the SLN metastases in millimeters and the presence of a negative sentinel lymph node. The model showed good discriminative ability (AUC, 0.75) and good calibration over the complete range of predicted probabilities. CONCLUSION: We have developed a tool to predict additional non-SLN metastases in Dutch patients with SLN-positive breast cancer that is easy to use in daily clinical breast cancer practice.

A Paradigm Shift in Axillary Breast Cancer Treatment; From "Treat All-Except," Toward "Treat None-Unless".

The various pitfalls that exist in using predictive systems for sentinel node-positive breast cancer are described, to give insight into the background and building stones of these systems. The aim of this article was to make clinicians aware of these pitfalls before using them in the clinical decision-making process in individual patients with positive sentinel nodes. Besides these pitfalls, the implications concerning the results of the Z0011 trial as presented by Giuliano et al (Giuliano AE, et al. Locoregional recurrence after sentinel lymph node dissection with or without axillary dissection in patients with sentinel lymph node metastases: The American College of Surgeons Oncology Group Z0011 randomized trial. Ann Surg 2010; 252:426-32, discussion 432-3) are addressed, and we point out some important issues for debate, before implementation of the conclusions of that practice-changing trial into daily clinical breast cancer practice.

A head to head comparison of nine tools predicting non-sentinel lymph node status in sentinel node positive breast cancer women.

BACKGROUND AND OBJECTIVES: This study was conducted to evaluate the performance of available tools predicting non-sentinel lymph node (non-SLN) status in women with SLN positive breast cancer and to see if they can be safely used in everyday clinical practice. METHODS: Data of 220 women with breast cancer who underwent a SLN biopsy at the Máxima Medical Centre between 2000-2008 were analysed. Tools evaluated were: the models from Memorial Sloan Kettering Cancer Centre, Stanford, Mayo, Cambridge, Gur, and MOU, and the scores from Saidi, Tenon, and MDA. Model performance was assessed using calibration, discrimination and Nagelkerke's explained variation. RESULTS: The MSKCC nomogram showed best overall performance with best discrimination (AUC 0.69), second best calibration, and highest explained variation (31%). The 10% low risk threshold led to defining only 22% (38/176) of the women as being low risk while in fact 66% (116/176) were non-SLN negative. The false negative rate was 13% (5/38). CONCLUSIONS: Current models for predicting non-SLN metastases in SLN positive breast cancer are not yet ready for implementation in general practice. Further research efforts should improve model performance in selecting patients or perhaps find a role in support in the paradigm shift to a "treat none unless" approach.

High intersystem variability for the prediction of additional axillary non-sentinel lymph node involvement in individual patients with sentinel node-positive breast cancer.

PURPOSE: To compare the outcomes of the available systems that predict the risk of non-sentinel lymph node (non-SLN) metastasis and to evaluate the variability within a group of SLN-positive breast cancer patients. METHODS: Predicted probabilities and scores for non-SLN metastasis were calculated with nine predictive systems for 120 SLN-positive patients who underwent a completion axillary lymph node dissection. The number of patients was calculated that were considered low risk or had a probability of ≤ 10% by at least one of the systems. For each nomogram, a box plot was constructed. All patients with a predicted probability of ≤ 10% according to the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram were selected, and a comparison was made with the probabilities predicted by the other systems. RESULTS: Nearly two-thirds (64.2%, n = 77) of patients with SLN-positive breast cancer were allocated to a low-risk or low-probability group by at least one of the predictive systems. No patients were uniformly classified as low risk by all nine prediction models. At the group level, a considerable variation in the distribution of the predicted probabilities was observed. At the individual level, calculation of the predicted probabilities for the selected patients who were considered low risk (≤ 10%) according to the MSKCC nomogram, showed even larger variations, ranging from 4 to 94%. CONCLUSIONS: This study shows that there is an unacceptably high variability in individual predictions when the predictive systems that are currently available are used to predict non-SLN metastasis in patients with SLN-positive breast cancer.