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Predictive algorithms for adjuvant therapy: TransATAC |
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| Authors: | Dowsett Mitch Salter Janine Zabaglo Lila Mallon Elizabeth Howell Antony Buzdar Aman U Forbes John Pineda S Cuzick Jack |
| Institution: | a Academic Department of Biochemistry, Royal Marsden Hospital, Fulham Road, London SW3 6JJ, UK b Pathology Department, Western Infirmary, Glasgow, UK c Manchester Breast Centre, University of Manchester, The Christie NHS Trust, Manchester, UK d UT MD Anderson Cancer Center, 1515 Holcombe Blvd - 424, Houston, TX 77030, USA e School of Medical Practice and Population Health, University of Newcastle, NSW, Australia f CR UK Centre for Epidemiology, Mathematics and Statistics, Queen Mary University of London, Wolfson Institute of Preventive Medicine, London EC1M 6BQ, UK |
| Abstract: | Estrogen receptor (ER) positive primary breast cancers have a wide range of clinical outcomes. Prediction of the likely course of the disease aids treatment decision-making. In the translational arm of the ATAC (anastrozole or tamoxifen alone or combined) trial (TransATAC) we have assessed individual and multiparameter biomarkers for their prediction of overall and distant recurrence. None of the biomarkers identified differential benefit for anastrozole versus tamoxifen. Each of ER, PgR, HER2 and Ki67 was associated with risk of recurrence. A combination of these to create a single predictor IHC4 was as informative as the 21-gene recurrence score (RS). Integration of each of these molecular profiles with classical clinicopathologic variables provided the most accurate prediction of outcome. |
| Keywords: | Predictive algorithm Endocrine therapy Aromatase inhibitor |
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