Locoregional stage assessment in clinically node negative breast cancer: Clinical, imaging, pathologic, and statistical methods

The locoregional staging remains an essential part of prognostication in breast cancer. Tumour size and biology, together with the number of lymph node metastases, guide the planning of appropriate treatments. Accurate clinical, imaging, pathologic, and statistical staging is needed as the surgical staging diminishes. In this study, 743 clinically lymph node negative breast cancer patients treated in 2009‒2017 were evaluated. Clinopathological factors were investigated in association with the number of lymph node metastases, the use of preoperative imaging methods and the surgical treatment method. A nomogram was developed and tested to predict the number of lymph node metastases after sentinel lymph node positivity. Three previously published models were validated to confirm their feasibility in the current population to predict nodal stage pN2a or pN3a. Tumour size, biologic subtype and proliferation associated with higher numbers of lymph node metastases. To predict stage pN2a or pN3a, the machine learning algorithms identified tumour size, invasive ductal histology, multifocality, lymphovascular invasion, oestrogen receptor status and the number of positive sentinel lymph nodes as risk factors. The nomograms performed well with favourable discrimination. Clinopathological factors seemed to guide preoperative magnetic resonance imaging (MRI) prior to more extensive surgery. MRI estimated the increasing tumour size more accurately than mammography or ultrasound. According to this study, clinopathological factors, additional preoperative MRI and modern statistics can be utilized in breast cancer staging without extensive surgical interference. The importance of non-surgical investigations in staging is growing in the planning of surgical, systemic and radiation treatments. Thus, maintaining the impressive survival outcomes of clinically node negative breast cancer patients can be achieved.Kliinisesti imusolmukenegatiivisen rintasyövän paikallislevinneisyyden arvioiminen. Kliiniset, kuvantamisen, patologian alan ja tilastotieteen menetelmät Kasvaimen paikallinen levinneisyys on tärkeä rintasyövän ennustetekijä. Kasvaimen koko ja biologia sekä imusolmukemetastaasien lukumäärä ohjaavat syöpähoitojen suunnittelua. Levinneisyyden selvittelyssä tarvitaan huolellista kliinistä tutkimusta sekä tarkkoja kuvantamisen, patologian alan ja tilastotieteen menetelmiä, kun kirurginen levinneisyysluokittelu vähenee. Tutkimuksessa arvioitiin vuosina 2009‒2017 hoidettujen 743 kliinisesti imusolmukenegatiivisen suomalaisen potilaan tietoja. Työssä selvitettiin kliinispatologisten tekijöiden ja kainaloimusolmukemetastaasien lukumäärän, leikkausta edeltävien kuvantamistutkimusten sekä leikkausmenetelmien yhteyttä. Ennustemalli kehitettiin ja koekäytettiin positiivisen vartijaimusolmuketutkimuksen jälkeisen imusolmukemetastaasien määrän arvioimiseksi. Kolme aiemmin julkaistua mallia validoitiin, jotta niiden käyttökelpoisuus imusolmukeluokan pN2a tai pN3a ennustamisessa varmistuisi tässä aineistossa. Kasvainkoko, biologinen alatyyppi ja jakautumisnopeus olivat yhteydessä suurempaan imusolmukemetastaasien määrään. Koneoppimisalgoritmit määrittivät levinneisyysluokan pN2a tai pN3a ennustamiseksi tarvittaviksi tekijöiksi kasvainkoon, invasiivisen duktaalisen histologian, monipesäkkeisyyden, suoni-invaasion, estrogeenireseptoristatuksen sekä positiivisten vartijaimusolmukkeiden määrän. Ennustemallit toimivat aineistossa hyvin osoittaen suotuisaa erotuskykyä. Kliinispatologiset tekijät näyttivät ohjaavan magneettikuvauspäätöstä ennen laajaa kirurgista hoitoa. Magneettikuvaus oli tarkin kuvantamismenetelmä suurenevan kasvainkoon arvioinnissa. Tämän tutkimuksen perusteella kliinispatologiset tekijät, leikkausta edeltävä täydentävä magneettikuvaus ja nykyaikaiset tilastotieteen menetelmät voivat hyödyttää rintasyövän levinneisyysluokittelua ilman laajoja kirurgisia toimenpiteitä. Kajoamattomien tutkimusten asema levinneisyysluokittelussa on vahvistumassa kirurgisten, lääkkeellisten ja sädehoitojen suunnittelun yhteydessä. Tarkka levinneisyysluokittelu edesauttaa kliinisesti imusolmukenegatiivisten rintasyöpäpotilaiden erinomaista ennustetta

Predictors of Auxillary Lymph Node Involvement in Screen Detected Breast Cancer

Background: Axillary lymph node dissection as routine part of breast cancer treatment has been questioned in relation to the balance between benefits and morbidity. The purpose of this study is to determine the association of tumor size, age and histological grade with axillary lymph node metastasis, to determine if some patients could be exempted from axillary dissection. Methods: The data are derived from BreastScreen NSW, the government sponsored population-based breast screening program. In New South Wales (NSW) Australia between 1995 and 2002, 7,221 patients with invasive breast carcinoma were diagnosed and 5,290 patients were eligible for this study. The relationship between incidence of positive axillary lymph nodes and three study factors (tumor size, age and histological grade) was investigated by univariate and multivariate analysis. Logistic regression models were used to predict probability of axillary metastases. Results: The incidence of axillary lymph node metastases was 28.6% (95% CI: 27.4%- 29.8%). Univariate analysis showed that age, tumor size and histological grade were significant predictors of axillary lymph node metastases (p<0.0001). Multivariate analysis identified age, tumor size and histological grade remained as independent predictors (p<0.0001). From multivariate analysis, patients with T1a (Less than or equal to 5mm) and grade I tumors regardless of age had 5.2% (95% CI: 1.2%- 9.3%) frequency of node metastases. Patients 70 years or older with grade I, T1a and T1b (6-10mm) tumors had 4.9% (95% CI: 3.2%- 7.5%) and 6.6% (95% CI: 5.3%-8.3%) predicted frequency of node metastases. Conclusions: Tumor size, age and histological grade are predictors of axillary lymph node metastases. Routine axillary lymph node dissection could be avoided in some patient groups with a low frequency of involved lymph nodes if the benefits are considered to exceed the risks

Predictors of Auxillary Lymph Node Involvement in Screen Detected Breast Cancer

Background: Axillary lymph node dissection as routine part of breast cancer treatment has been questioned in relation to the balance between benefits and morbidity. The purpose of this study is to determine the association of tumor size, age and histological grade with axillary lymph node metastasis, to determine if some patients could be exempted from axillary dissection. Methods: The data are derived from BreastScreen NSW, the government sponsored population-based breast screening program. In New South Wales (NSW) Australia between 1995 and 2002, 7,221 patients with invasive breast carcinoma were diagnosed and 5,290 patients were eligible for this study. The relationship between incidence of positive axillary lymph nodes and three study factors (tumor size, age and histological grade) was investigated by univariate and multivariate analysis. Logistic regression models were used to predict probability of axillary metastases. Results: The incidence of axillary lymph node metastases was 28.6% (95% CI: 27.4%- 29.8%). Univariate analysis showed that age, tumor size and histological grade were significant predictors of axillary lymph node metastases (p<0.0001). Multivariate analysis identified age, tumor size and histological grade remained as independent predictors (p<0.0001). From multivariate analysis, patients with T1a (Less than or equal to 5mm) and grade I tumors regardless of age had 5.2% (95% CI: 1.2%- 9.3%) frequency of node metastases. Patients 70 years or older with grade I, T1a and T1b (6-10mm) tumors had 4.9% (95% CI: 3.2%- 7.5%) and 6.6% (95% CI: 5.3%-8.3%) predicted frequency of node metastases. Conclusions: Tumor size, age and histological grade are predictors of axillary lymph node metastases. Routine axillary lymph node dissection could be avoided in some patient groups with a low frequency of involved lymph nodes if the benefits are considered to exceed the risks

Breast Cancer Subtypes Can Be Determinant in The Decision Making Process to Avoid Surgical Axillary Staging: A retrospective cohort study

Purpose: The need for performing axillary lymph-node dissection in early breast cancer when the sentinel lymph node (SLN) is positive has been questioned in recent years. The purpose of this study was to identify a lowrisk subgroup of early breast cancer patients in whom surgical axillary staging could be avoided, and to assess the probability of having a positive lymph-node (LN). Methods: We retrospectively evaluated 612 consecutive women affected by early breast cancer. We considered age, tumour size, histological grade, vascular invasion, lymphatic invasion and cancer subtype (Luminal A, Luminal B HER-2+, Luminal B HER-2-, HER-2+, and Triple Negative) as variables for univariate and multivariate analyses to assess probability of there being a positive SLN o non-sentinel lymph node (NSLN). Chi-square, Fisher’s Exact test and Student’s t tests were used to investigate the relationship between variables; whereas logit models were used to estimate and quantify the strength of the relationship among some covariates and SLN or the number of metastases. Results: A significant positive effect of vascular invasion and lymphatic invasion, and a negative effect of TN were noted. With respect to positive NSLN, size alone has a significant (positive) effect on tumour presence, but focusing on the number of metastases, also age has a (negative) significant effect. Conclusion: This work shows correlation between subtypes and the probability of having positive SLN. Patients not expressing vascular invasion, lymphatic invasion and, moreover, a triple-negative tumor subtype may be good candidates for breast conservative surgery without axillary su

Management of the axilla in breast cancer:\ua0outcome analysis in a series of ductal versus lobular invasive cancers

Introduction: Axillary lymph node dissection (ALND) has been considered essential for the staging of breast cancer (BC). As the impact of tumor biology on clinical outcomes is recognized, a surgical de-escalation approach is being implemented. We performed a retrospective study focused on surgical management of the axilla in invasive lobular carcinoma (ILC) versus invasive ductal carcinoma (IDC). Materials and methods: 1151 newly diagnosed BCs, IDCs (79.6%) or ILCs (20.4%), were selected among patients treated at our Breast Cancer Unit from 2012 to 2018. Tumor characteristics and clinical information were collected and predictors of further metastasis after positive sentinel lymph node biopsy (SLNB) analyzed in relation to disease-free survival (DFS) and overall survival (OS). Results: 27.5% of patients with ILC had 65 3 metastatic lymph nodes at ALND after positive SLNB versus 11.48% of IDCs (p = 0.04). Risk predictors of further metastasis at ALND were the presence of > 2 positive lymph nodes at SLNB (OR = 4.72, 95% CI 1.15\u201319.5 p = 0.03), T3\u2013T4 tumors (OR = 4.93, 95% CI 1.10\u201322.2, p = 0.03) and Non-Luminal BC (OR = 2.74, 95% CI 1.16\u20136.50, p = 0.02). The lobular histotype was not associated with the risk of further metastasis at ALND (OR = 1.62, 95% CI 0.77\u20133.41, p = 0.20). Conclusions: ILC histology is not associated with higher risk of further metastasis at ALND in our analysis. However, surgical management decisions should be taken considering tumor histotype, biology and expected sensitivity to adjuvant therapies

A nomogram to predict the probability of axillary lymph node metastasis in early breast cancer patients with positive axillary ultrasound

Among patients with a preoperative positive axillary ultrasound, around 40% of them are pathologically proved to be free from axillary lymph node (ALN) metastasis. We aimed to develop and validate a model to predict the probability of ALN metastasis as a preoperative tool to support clinical decision-making. Clinicopathological features of 322 early breast cancer patients with positive axillary ultrasound findings were analyzed. Multivariate logistic regression analysis was performed to identify independent predictors of ALN metastasis. A model was created from the logistic regression analysis, comprising lymph node transverse diameter, cortex thickness, hilum status, clinical tumour size, histological grade and estrogen receptor, and it was subsequently validated in another 234 patients. Coefficient of determination (R-2) and the area under the ROC curve (AUC) were calculated to be 0.9375 and 0.864, showing good calibration and discrimination of the model, respectively. The false-negative rates of the model were 0% and 5.3% for the predicted probability cut-off points of 7.1% and 13.8%, respectively. This means that omission of axillary surgery may be safe for patients with a predictive probability of less than 13.8%. After further validation in clinical practice, this model may support increasingly limited surgical approaches to the axilla in breast cancer

New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients

<p>Abstract</p> <p>Background</p> <p>Current practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.</p> <p>Methods</p> <p>We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.</p> <p>Results</p> <p>285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.</p> <p>Conclusion</p> <p>We present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets. </p

Prognostic impact of macrometastasis linear size in sentinel node biopsy for breast carcinoma

AIM: The aim of the present study was to evaluate the risk of axillary non-sentinel lymph-node metastases (ALN) in breast cancer patients presenting macrometastasis (Mac-m) in the sentinel lymph node (SN). MATERIALS AND METHODS: A retrospective series of 1464 breast cancers from patients who underwent ALN dissection following the diagnosis of Mac-m in the sentinel node (SN) was studied. In all the cases the MAC-m linear size was evaluated and correlated with presence or absence of non-SN ALN metastases. RESULTS: Non-SN metastases were detected in 644\1464 cases (43.98%). The risk of further axillary metastases ranged from 20.2% (37/183) in cases with Mac-m between 2 and 2.9 mm, to 65.3% (262/401) in cases with Mac-m measuring > 10 mm. The risk of non-SN ALN metastases showed a 3% increase, parallel to each mm increment in SN metastasis size. The data evaluated with the receiver operating characteristic (ROC) curve showed that the Mac-m could be subdivided according to a new cut-off of 7 mm. pT1 tumours, with Mac-m < 7 mm had a risk of non-SN ALN metastases of <30%. Furthermore 109/127 of these (85.8%) had 3 or less non-SN ALN -metastases. CONCLUSIONS: The present data give a detailed description on the risk of non-SN ALN involvement, that may be useful in the evaluation of breast cancer patients. It is suggested that a Mac-m size of <7 mm is related to a low residual axillary disease burden in breast cancer patients with small (pT1) tumours