Surgical procedure examined in detecting cancer in lymph nodes near breast

By | October 9, 2013

Axillary (the armpit region) lymph node status is an important prognostic factor in breast cancer and is used to guide local, regional, and systemic treatment decisions. Accurate determination of axillary involvement after chemotherapy is important; however, removing all axillary nodes to assess for residual nodal disease exposes many patients to the potential side effects of surgery and, potentially, only a subset will benefit. To avoid the complications associated with axillary lymph node dissection (ALND), it is preferable to identify nodal disease with the less invasive sentinel lymph node (SLN) surgical procedure, which results in fewer side effects, according to background information in the article.

The American College of Surgeons Oncology Group (ACOSOG) Z1071 trial enrolled women from 136 institutions from July 2009 to June 2011 who had various stages of breast cancer and received neoadjuvant (before surgery) chemotherapy. Following chemotherapy, patients underwent both SLN surgery and ALND. The primary end point for the study was the false-negative rate of SLN surgery after chemotherapy in women who presented with cN1 disease (disease in movable axillary lymph nodes). The researchers evaluated the likelihood that the false-negative rate in patients with 2 or more SLNs examined was greater than 10 percent, the rate expected for women undergoing SLN surgery who present with clinical node-negative (cNO) disease.

Seven hundred fifty-six women were enrolled in the study. Of 663 evaluable patients with cN1 disease, 649 underwent chemotherapy followed by both SLN surgery and ALND. The researchers found that the false-negative rate was 12.6 percent with SLN surgery and exceeded the prespecified threshold of 10 percent. "Given this [10 percent] threshold, changes in approach and patient selection that result in greater sensitivity would be necessary to support the use of SLN surgery as an alternative to ALND in this patient population."

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