Predictive algorithms for adjuvant therapy: TransATAC

Mitch Dowsett, Janine Salter, Lila Zabaglo, Elizabeth Mallon, Antony Howell, Aman U. Buzdar, John Forbes, S. Pineda, Jack Cuzick

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)777-780
Number of pages4
Issue number8
Publication statusPublished - 1 Jul 2011


  • Aromatase inhibitor
  • Endocrine therapy
  • Predictive algorithm

Research Beacons, Institutes and Platforms

  • Manchester Cancer Research Centre


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