The value of multigene predictors of clinical outcome in breast cancer: An analysis of the evidence

Amalia M. Issa, Vivek S. Chaudhari, Gary Marchant

Research output: Contribution to journalReview article

6 Scopus citations

Abstract

Objective: Multigene predictors are being used increasingly in early-stage breast cancer patients for prediction and prognosis. However, one consequence of the increased use of multigene predictors, and the heightened efforts toward their incorporation into routine clinical practice, is the potential for future malpractice litigation. It is, therefore, important to ascertain the strength of the evidence for using the different commercially available multigene predictor assays clinically. We evaluated the literature for evidence of clinical validity of four currently available gene signatures and to assess the influence of the 21-gene-expression assay on changes in treatment recommendations. Methods: A systematic search of the peer-reviewed literature from January 2002 to March 2014 for multigene predictor assays was carried out, and a meta-analysis was conducted. Results: The adjusted Cox hazard ratio average for studies that met the eligibility criteria was 3.538 (95% CI: 1.513-8.469). The 21-gene signature showed the highest stability in the estimation of likelihood of distant risk of recurrence. Using the recurrence scores resulted in changes in treatment recommendations in 31.8% of all patients in the studies. Conclusion: This study may provide insight about the use of multigene predictors in clinical practice for prediction and prognosis of breast cancer.

Original languageEnglish (US)
Pages (from-to)277-286
Number of pages10
JournalExpert Review of Molecular Diagnostics
Volume15
Issue number2
DOIs
StatePublished - Feb 1 2015

Keywords

  • Cox hazard ratios
  • breast cancer
  • gene-expression profiling
  • meta-analysis
  • multigene predictors
  • recurrence score

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Molecular Medicine
  • Molecular Biology
  • Genetics

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