The outcome of sentinel node biopsy in breast cancer patients with preoperative surgical biopsy

Sentinel Lymph Node Methods in Breast Cancer

Breast cancer is the most frequent cancer diagnosed in women worldwide. Accurate lymph node staging is essential for both prognosis (of early-stage disease) and treatment (for regional control of disease) in patients with breast cancer. The sentinel lymph nodes are the regional nodes that directly drain lymph from the primary tumor. No imaging modality is accurate enough to detect lymph node metastases when a primary breast cancer is at an early stage (I or II), but sentinel lymph node biopsy is a highly reliable method for screening axillary nodes and for identifying metastatic (including micro-metastatic) disease in regional lymph nodes. Despite the widespread use of sentinel lymph node biopsy for early-stage breast cancer, relevant variations have been described regarding practical aspects of the procedure, and some variability has initially been reported regarding the rates of intraoperative sentinel lymph node identification and of false-negative findings, most likely because of differences in the size of the populations being investigated and in lymphatic mapping techniques. Nevertheless, using adequate learning curves and once a multidisciplinary team is experienced with the procedure, improved levels of accuracy are achieved.

Time from breast cancer diagnosis to therapeutic surgery and breast cancer prognosis: A population-based cohort study

Theoretically, time from breast cancer diagnosis to therapeutic surgery should affect survival. However, it is unclear whether this holds true in a modern healthcare setting in which breast cancer surgery is carried out within weeks to months of diagnosis. This is a population- and register-based study of all women diagnosed with invasive breast cancer in the Stockholm-Gotland healthcare region in Sweden, 2001-2008, and who were initially operated. Follow-up of vital status ended 2014. 7,017 women were included in analysis. Our main outcome was overall survival. Main analyses were carried out using Cox proportional hazards models. We adjusted for likely confounders and stratified on mode of detection, tumor size and lymph node metastasis. We found that a longer interval between date of morphological diagnosis and therapeutic surgery was associated with a poorer prognosis. Assuming a linear association, the hazard rate of death from all causes increased by 1.011 (95% CI 1.006-1.017) per day. Comparing, for example, surgery 6 weeks after diagnosis to surgery 3 weeks after diagnosis, thereby confers a 1.26-fold increased hazard rate. The increase in hazard rate associated with surgical delay was strongest in women with largest tumors. Whilst there was a clear association between delays and survival in women without lymph node metastasis, the association may be attenuated in subgroups with increasing number of lymph node metastases. We found no evidence of an interaction between time to surgery and mode of detection. In conclusion, unwarranted delays to primary treatment of breast cancer should be avoided.

A predictive tool to estimate the risk of axillary metastases in breast cancer patients with negative axillary ultrasound

BACKGROUND

Sentinel node biopsy (SNB) is the "gold standard" in axillary staging in clinically node-negative breast cancer patients. However, axillary treatment is undergoing a paradigm shift and studies are being conducted on whether SNB may be omitted in low-risk patients. The purpose of this study was to evaluate the risk factors for axillary metastases in breast cancer patients with negative preoperative axillary ultrasound.

METHODS

A total of 1,395 consecutive patients with invasive breast cancer and SNB formed the original patient series. A univariate analysis was conducted to assess risk factors for axillary metastases. Binary logistic regression analysis was conducted to form a predictive model based on the risk factors. The predictive model was first validated internally in a patient series of 566 further patients and then externally in a patient series of 2,463 patients from four other centers. All statistical tests were two-sided.

RESULTS

A total of 426 of the 1,395 (30.5 %) patients in the original patient series had axillary lymph node metastases. Histological size (P < 0.001), multifocality (P < 0.001), lymphovascular invasion (P < 0.001), and palpability of the primary tumor (P < 0.001) were included in the predictive model. Internal validation of the model produced an area under the receiver operating characteristics curve (AUC) of 0.731 and external validation an AUC of 0.79.

CONCLUSIONS

We present a predictive model to assess the patient-specific probability of axillary lymph node metastases in patients with clinically node-negative breast cancer. The model performs well in internal and external validation. The model needs to be validated in each center before application to clinical use.