Validation of the IHC4 breast cancer prognostic algorithm using multiple approaches on the multinational TEAM clinical trial

Research output: Contribution to journalArticlepeer-review

Authors

  • John M S Bartlett
  • Jason Christiansen
  • Mark Gustavson
  • David L. Rimm
  • Tammy Piper
  • Cornelis J H Van De Velde
  • Annette Hasenburg
  • Dirk G. Kieback
  • Hein Putter
  • Christos J. Markopoulos
  • Luc Y. Dirix
  • Caroline Seynaeve

Colleges, School and Institutes

External organisations

  • EDINBURGH UNIVERSITY
  • Inc
  • Diagnostics Department at MetaStat, Inc
  • Department of Pathology, Yale University, School of Medicine, New Haven, CT 06520, USA.
  • Leiden University Medical Center - LUMC
  • University Hospital
  • Klinikum Vest Medical Center
  • Athens University Medical School
  • Sint-Augustinus
  • Erasmus University Medical Center
  • Department of Obstetrics and Gynecology
  • Elblandklinikum

Abstract

Context. - Hormone receptors HER2/neu and Ki-67 are markers of residual risk in early breast cancer. An algorithm (IHC4) combining these markers may provide additional information on residual risk of recurrence in patients treated with hormone therapy. Objective. - To independently validate the IHC4 algorithm in the multinational Tamoxifen Versus Exemestane Adjuvant Multicenter Trial (TEAM) cohort, originally developed on the trans-ATAC (Arimidex, Tamoxifen, Alone or in Combination Trial) cohort, by comparing 2 methodologies. Design. - The IHC4 biomarker expression was quantified on TEAM cohort samples (n = 2919) by using 2 independent methodologies (conventional 3,3′-diaminobezidine [DAB] immunohistochemistry with image analysis and standardized quantitative immunofluorescence [QIF] by AQUA technology). The IHC4 scores were calculated by using the same previously established coefficients and then compared with recurrence-free and distant recurrence- free survival, using multivariate Cox proportional hazards modeling. Results. - The QIF model was highly significant for prediction of residual risk (P <.001), with continuous model scores showing a hazard ratio (HR) of 1.012 (95% confidence interval [95% CI]: 1.010-1.014), which was significantly higher than that for the DAB model (HR: 1.008, 95% CI: 1.006-1.009); P <.001). Each model added significant prognostic value in addition to recognized clinical prognostic factors, including nodal status, in multivariate analyses. Quantitative immunofluorescence, however, showed more accuracy with respect to overall residual risk assessment than the DAB model. Conclusions. - The use of the IHC4 algorithm was validated on the TEAM trial for predicting residual risk in patients with breast cancer. These data support the use of the IHC4 algorithm clinically, but quantitative and standardized approaches need to be used.

Details

Original languageEnglish
Pages (from-to)66-74
Number of pages9
JournalArchives of Pathology and Laboratory Medicine
Volume140
Issue number1
Publication statusPublished - 1 Jan 2016