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View Full Version : not a big study but good news--prognosis for those with lots of+lymph nodes improving


Lani
05-03-2006, 10:56 AM
Breast Cancer Survival Better With Extensive Axillary Disease Than Historically Reported: Presented at ASBD [Doctor's Guide]
LAS VEGAS, N.V. — May 1, 2006 — Although earlier studies reported that the number of lymph nodes involved predicts survival in breast cancer patients, modern treatment options appear to have improved the prognosis in patients with extensive axillary involvement, researchers said here at the annual American Society of Breast Disease (ASBD) annual meeting.

"Estrogen receptor positivity and the use of adjuvant chemotherapy were significantly associated with improved survival," said lead author Francesca M. Hoehne, MD, breast fellow, John Wayne Cancer Institute, Santa Monica, California, United States, in a presentation April 28th and 29th.

Dr. Hoehne and colleagues compared a cohort of 53 patients with breast cancer and at least 10 positive axillary lymph nodes in their prospectively collected database to historical controls in the literature.

Patients were treated from 1991 to 2005 with a median follow up of 5 years, had primary invasive breast cancer and did not present evidence of distant metastatic disease. The average tumor size was 4.87 cm. Most tumors were estrogen receptor positive (81%) and progesterone receptor positive (60%), while 19% were human epithelial growth factor receptor (HER2) positive.

Overall 5-year survival was 71.9% while 5-year disease-free survival was similar, at 71.4%. By comparison, studies from the 1980s reported 5-year survival rates for patients with at least 10 positive axillary nodes to be from 0% to 28%.

In Dr. Hoehne's cohort, age younger than 50 years and adjuvant chemotherapy were associated with survival. Adjuvant hormone therapy was significantly higher in patients who were living than those who died.

Progesterone positive breast cancer and adjuvant hormonal therapy were significantly associated with survival in a univariate analysis but dropped out of significance when other factors were included.