Tumour location and axillary lymph node involvement in breast cancer: a series of 3472 cases from Sweden

Prediction of Axillary Lymph Node Metastasis in Invasive Breast Cancer by Sound Touch Elastography

The aims of this study were to investigate the value of sound touch elastography (STE) in predicting axillary lymph node metastasis (ALNM) in patients with invasive breast cancer (IBC) and to explore whether lysyl oxidase (LOX) is correlated with increasing stiffness and promotion of metastasis in IBC. A total of 142 lesions in 142 patients were assessed by STE. The STE values of IBCs in the two groups were compared and the best cutoff values for diagnosing ALNM determined. Immunohistochemistry was used to detect LOX expression. Collagen fiber and elastic fiber content was determined by Masson and Weigert elastic fiber staining. Correlation analyses were performed to identify the associations of the data. The optimal cutoff values of E_max (maximum stiffness value of the tumor) and S_max (maximum stiffness value of the shell) for predicting ALNM of IBC were 94.58 and 148.78 kPa. Immunohistochemistry and Masson and Weigert elastic fiber staining were performed on 67 samples. LOX expression and collagen volume fraction were significantly higher in the ALNM+ group than in the ALNM- group (p = 0.04 and 0.03), except for elastic fiber content (p = 0.628). Moreover, E_max, S_max and LOX expression were positively correlated with collagen volume fraction (r = 0.624, 0.512, and 0.533, respectively). E_max and S_max were found to be predictors for ALNM of IBC. STE could serve as a non-invasive method for assessing lymph node status before surgery. Overexpression of LOX and increased collagen fiber contributed to the increased stiffness in the lesions and metastases of IBC.

Risk factors for axillary lymph node metastases in clinical stage T1-2N0M0 breast cancer patients

Axillary lymph node metastasis (ALNM) is commonly the earliest detectable clinical manifestation of breast cancer when distant metastasis emerges. This study aimed to explore the influencing factors of ALNM and develop models that can predict its occurrence preoperatively.Cases of sonographically visible clinical stage T1-2N0M0 breast cancers treated with breast and axillary surgery at West China Hospital were retrospectively reviewed. Univariate and multivariate logistic regression analyses were performed to evaluate associations between ALNM and variables. Decision tree analyses were performed to construct predictive models using the C5.0 packages.Of the 1671 tumors, 541 (32.9%) showed axillary lymph node positivity on final surgical histopathologic analysis. In multivariate logistic regression analysis, tumor size (P < .001), infiltration of subcutaneous adipose tissue (P < .001), infiltration of the interstitial adipose tissue (P = .031), and tumor quadrant locations (P < .001) were significantly correlated with ALNM. Furthermore, the accuracy in the decision tree model was 69.52%, and the false-negative rate (FNR) was 74.18%. By using the error-cost matrix algorithm, the FNR significantly decreased to 14.75%, particularly for nodes 5, 8, and 13 (FNR: 11.4%, 9.09%, and 14.29% in the training set and 18.1%,14.71%, and 20% in the test set, respectively).In summary, our study demonstrated that tumor lesion boundary, tumor size, and tumor quadrant locations were the most important factors affecting ALNM in cT1-2N0M0 stage breast cancer. The decision tree built using these variables reached a slightly higher FNR than sentinel lymph node dissection in predicting ALNM in some selected patients.

Pre-operative Conventional Ultrasound and Sonoelastography Evaluation for Predicting Axillary Lymph Node Metastasis in Patients with Malignant Breast Lesions

The objective of our study was to evaluate the association between the sonoelastography features of breast tumor and axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 106 women with breast cancer, the conventional ultrasound features and elasticity parameters by elasticity imaging and Virtual Touch Tissue Imaging & Quantification (VTIQ) were retrospectively analyzed. Ultrasound and elastography findings were compared with pathologic axillary lymph node status. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Pathologically, the overall incidence of ALNM was 39.6% (42/106) in the final analysis. ALNM was significantly more frequent in tumors with elasticity imaging scores >4.5, maximal shear wave velocity values (Smax) >6.42 m/s and mean shear wave velocity values (Smean) >5.66 m/s, respectively. The sensitivity, specificity and accuracy were 78.6%, 54.7% and 64.2% for elasticity imaging score; 85.7%, 54.7% and 67.0% for Smax; and 59.5%, 79.7% and 71.7% for Smean, respectively Elastography features, including elasticity imaging score and VTIQ, can be used to supplement conventional ultrasound to predict ALNM in patients with breast cancers.

Location of triple-negative breast cancers: comparison with estrogen receptor-positive breast cancers on MR imaging

There has been a major need to better understand the biological characteristics of triple-negative breast cancers. Compared with estrogen receptor (ER)-positive cancers, several magnetic resonance (MR) imaging findings have been reported as characteristic findings. However, information regarding their location has not been described. Our study was to compare the location of triple-negative breast cancers with that of ER-positive breast cancers using magnetic resonance (MR) imaging. The locations of 1102 primary breast cancers (256 triple-negative and 846 ER-positive) in 1090 women (mean, 52.1 years) were reviewed using three-dimensional (3D) coordinates. The x-axis measurement was recorded as the transverse distance from the posterior nipple line; y-axis measurement as the anteroposterior distance from the chest wall; z-axis measurement as the superoinferior distance from the posterior nipple line. The association between breast cancer subtype and tumor location was evaluated using multiple linear regression analysis. Triple-negative breast cancers were significantly closer to the chest wall than ER-positive breast cancers in absolute (1.8 cm vs. 2.3 cm, P < .0001) and normalized (0.21 vs. 0.25, P < .0001) y-axis distances. The x- and z-axes distances were not significantly different between triple-negative and ER-positive breast cancers. Multiple linear regression analysis revealed that age, mammographic density, axillary nodal status, and triple-negative subtype were significantly associated with absolute and normalized distances from the chest wall (all P < .05). Our results show that triple-negative breast cancers have a tendency toward a posterior or prepectoral location compared with ER-positive breast cancers.

Statistical models for predicting number of involved nodes in breast cancer patients

Clinicians need to predict the number of involved nodes in breast cancer patients in order to ascertain severity, prognosis, and design subsequent treatment. The distribution of involved nodes often displays over-dispersion-a larger variability than expected. Until now, the negative binomial model has been used to describe this distribution assuming that over-dispersion is only due to unobserved heterogeneity. The distribution of involved nodes contains a large proportion of excess zeros (negative nodes), which can lead to over-dispersion. In this situation, alternative models may better account for over-dispersion due to excess zeros. This study examines data from 1152 patients who underwent axillary dissections in a tertiary hospital in India during January 1993-January 2005. We fit and compare various count models to test model abilities to predict the number of involved nodes. We also argue for using zero inflated models in such populations where all the excess zeros come from those who have at some risk of the outcome of interest. The negative binomial regression model fits the data better than the Poisson, zero hurdle/inflated Poisson regression models. However, zero hurdle/inflated negative binomial regression models predicted the number of involved nodes much more accurately than the negative binomial model. This suggests that the number of involved nodes displays excess variability not only due to unobserved heterogeneity but also due to excess negative nodes in the data set. In this analysis, only skin changes and primary site were associated with negative nodes whereas parity, skin changes, primary site and size of tumor were associated with a greater number of involved nodes. In case of near equal performances, the zero inflated negative binomial model should be preferred over the hurdle model in describing the nodal frequency because it provides an estimate of negative nodes that are at "high-risk" of nodal involvement.

Parity in relation to survival following breast cancer

AIM

The present study examines the association between parity and survival following breast cancer diagnosis.

METHODS

Medical records of 4453 women diagnosed with breast cancer in Malmö, Sweden, between 1961 and 1991 were analysed. All women were followed until 31 December 2003, using the Swedish Cause-of-Death Registry. Breast cancer specific mortality rate was calculated in different levels of parity. Corresponding relative risks, with 95% confidence intervals (CI), were obtained using Cox's proportional hazards analysis. All analyses were adjusted for potential prognostic factors and stratified for age, menopausal status and diagnostic period.

RESULTS

As compared to women with one child, nulliparity (RR 1.27: 95% CI 1.09-1.47), and high parity (four or more children) (1.49: 1.20-1.85) were positively associated with a high mortality from breast cancer. When adjusted for potential confounders, the association was only statistically significant for high parity (1.33: 1.07-1.66). In the analyses stratified on age and menopausal status, there was a similar positive association between high parity and breast cancer death in all strata, although only statistically significant among women older than 45 years of age or postmenopausal. Nulliparity was associated with breast cancer death in women that were younger than 45 years of age (1.28: 0.79-2.09) or premenopausal (1.30: 0.95-1.80), but these associations did not reach statistical significance. There was no association between nulliparity and breast cancer death in women older than 45 years of age or postmenopausal. All associations were similar in analyses stratified for diagnostic period.

CONCLUSION

Women with four or more children have a poor breast cancer survival as compared to women with one child.

Breast cancer sagittal/horizontal plane location influences axillary lymph node involvement

AIM

To assess the influence of tumour location on axillary lymph node involvement (ALNI) and prognosis in breast cancer by evaluating the significance of the sagittal/horizontal alignment.

METHODS

We compared 57 patients with superficially located breast carcinomas up to 3.0 cm with patients having lesions in posterior planes of the breast. Both groups were matched according to age, time of diagnosis, tumour size, grade, hormonal receptor status and tumour site within the frontal plane. Histologic evidence of skin involvement, excluding tumours fulfilling the criteria for pT4b, was defined as inclusion criteria and reference plane for superficial tumour location.

RESULTS

Tumours situated in the superficial region of the breast, compared to those located in deeper planes, have an increased risk of ALNI (p=0.023), whereas no difference was observed with reference to disease-specific survival (p=0.203).

CONCLUSION

This study shows that ALNI is dependent on sagittal/horizontal as well as frontal tumour location. Clinicians should be aware that tumours lying posteriorly may be at increased risk of occult spread outside axillary lymph nodes.