Relapse-free survival of statistically standardized continuous RT-PCR estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2): NCIC CTG MA.14 Academic Article uri icon

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  • Recent ASCO/CAP guidelines focus on decision making associated with the presence/absence of continuous breast biomarkers. Statistical standardization (SS) is demonstrated as a method to evaluate the effects of continuous RT-PCR biomarker expression levels on breast cancer outcomes. MA.14 allocated 667 postmenopausal patients to tamoxifen based on locally determined ER/PR. Of 299 available patient tumor samples, 292 passed internal quality control. All tumors were centrally assessed by RT-PCR ER/PR/HER2 with each biomarker's z-scores categorized: ≥1.0 standard deviation (SD) below mean; <1.0 SD below mean; ≤1.0 SD above mean; >1.0 SD above mean. Log-rank statistics tested univariate differences in breast cancer relapse-free survival (RFS). Continuous SS-ER/PR/HER2 were assessed in multivariate Cox step-wise forward regression, adding a factor if p ≤ 0.05. Sensitivity analyses examined an external HER2+ cut-point of 1.32. Patients whose tumors were tested were representative of the MA.14 population (p values = 0.18-0.90). At 9.8 years median follow-up, SS-ER did not univariately impact RFS (p = 0.31). SS-PR values above the mean (z ≥ 0.0) had the best univariate RFS (p = 0.03). SS-HER2 also univariately impacted RFS (p = 0.004) with lowest (z-scores ≤ -1.0) and highest (z-scores > 1.0) having shortest RFS. Multivariate stratified/unstratified Cox models indicated patients with T1 tumors (p = 0.02/p = 0.0002) and higher SS-PR (p = 0.02/p = 0.01) had longer RFS; node-negative patients had better RFS (in unstratified analysis, p < 0.0001). Local ER/PR status did not impact RFS (p > 0.05). Patients with SS HER2+ ≥ 1.32 had worse RFS (univariate, p = 0.05; multivariate, p = 0.06). We demonstrated that higher SS-PR, and SS HER2 levels, measured by RT-PCR impacted breast cancer RFS outcomes. Evaluation in other trials may provide support for this methodology.


  • Chapman, Judith-Anne W
  • Sgroi, Dennis C
  • Goss, Paul E
  • Zarella, Elizabeth
  • Binns, Shemeica
  • Zhang, Yi
  • Schnabel, Catherine A
  • Erlander, Mark G
  • Pritchard, Kathleen
  • Han, Lei
  • Badovinac-Crnjevic, Tanja
  • Shepherd, Lois E
  • Pollak, Michael N

publication date

  • May 2016