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MammaPrint Pre-screen Algorithm (MPA) reduces chemotherapy in patients with early-stage breast cancer


KA Grant
JP Apffelstaedt
C Wright
E Myburgh
R Pienaar
M de Klerk
MJ Kotze

Abstract

Background. Clinical and pathological parameters may overestimate the need for chemotherapy in patients with early-stage breast cancer. More
accurate determination of the risk of distant recurrence is now possible with use of genetic tests, such as the 70-gene MammaPrint profile.
Objectives. A health technology assessment performed by a medical insurer in 2009 introduced a set of test eligibility criteria – the MammaPrint Pre-screen Algorithm (MPA) – applied in this study to determine the clinical usefulness of a pathology-supported genetic testing strategy, aimed at the reduction of healthcare costs.
Methods. An implementation study was designed to take advantage of the fact that the 70-gene profile excludes analysis of hormone receptor and
human epidermal growth factor receptor 2 (HER2) status, which form part of the MPA based partly on immunohistochemistry routinely performed
in all breast cancer patients. The study population consisted of 104 South African women with early-stage breast carcinoma referred for MammaPrint.
For the MammaPrint test, RNA was extracted from 60 fresh tumours (in 58 patients) and 46 formalin-fixed, paraffin-embedded (FFPE) tissue samples.
Results. When applying the MPA for selection of patients eligible for MammaPrint testing, 95 of the 104 patients qualified. In this subgroup
62% (59/95) were classified as low risk. Similar distribution patterns for risk classification were obtained for RNA extracted from fresh tumours v. FFPE tissue samples.
Conclusions. The 70-gene profile classifies approximately 40% of  early-stage breast cancer patients as low-risk compared with 15% using
conventional criteria. In comparison, more than 60% were shown to be low risk with use of the MPA validated in this study as an appropriate strategy to prevent chemotherapy overtreatment in patients with early-stage breast cancer.

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eISSN: 2078-5135
print ISSN: 0256-9574