Researchers presented late breaking five-year data from the TEAM (Tamoxifen Exemestane Adjuvant Multinational) trial, a prospective, randomised trial comparing initial therapy with the steroidal aromatase inhibitor exemestane vs. a switch from initial therapy of tamoxifen to exemestane after a few years, at the annual CTRC-AACR San Antonio Breast Cancer Symposium, USA.
"This is the only aromatase inhibitor study that has used exemestane as initial endocrine therapy compared to tamoxifen followed by exemestane," said study author Dr. Daniel Rea, senior lecturer in medical oncology at the University of Birmingham, United Kingdom. "This is also the only study with sufficient power to reliably determine if an aromatase inhibitor as initial therapy is superior to a sequential approach starting with tamoxifen."
In the TEAM trial, researchers randomly assigned 9,775 postmenopausal women with hormone receptor-positive early breast cancer to exemestane 25 mg per day or tamoxifen 20 mg per day. The trial began in 2001, and in 2004 the researchers reassigned all women who were initially receiving tamoxifen to switch to exemestane after 2.5 to three years. All women had undergone surgery with curative intent for invasive breast cancer. All tumors were hormone receptor positive, 50 percent were node negative and 36 percent had received chemotherapy.
The trial's two primary endpoints were disease-free survival for tamoxifen vs. exemestane at 2.75 years - data that were presented at the 2008 CTRC-AACR San Antonio Breast Cancer Symposium - and disease-free survival at five years for women initially receiving exemestane vs. those who switched from tamoxifen to exemestane.
"Our hypothesis under examination in this presentation is that exemestane taken as initial endocrine therapy will improve relapse-free survival compared with starting tamoxifen," Rea said.
He also explained that the TEAM trial is large enough for researchers to potentially identify subgroups that might benefit from different treatment approaches.
"In addition to analysis by traditional prognostic features, we may be able to identify subgroups defined by relatively simple biomarkers which can be used or combined with standard prognostic variables to rationally select optimal treatment strategies," Rea said.