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MammaPrint

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MammaPrint is a prognostic and predictive diagnostic test for early stage breast cancer patients that assess the risk that a tumor will metastasize to other parts of the body. It gives a binary result, high-risk or low-risk classification, and helps physicians determine whether or not a patient will benefit from chemotherapy. Women with a low risk result can safely forego chemotherapy without decreasing likelihood of disease free survival. MammaPrint is part of the personalized medicine portfolio marketed by Agendia.

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19 sections
Contents
  • Development
  • Implications for utility
  • Clinical Utility
  • Guideline Inclusion
  • Ordering indications
  • USA-
  • International-
  • Pakistan-
  • Tissue sampling technique
  • Cost and Cost-Effectiveness
  • Key Clinical trials
  • MINDACT
  • PROMIS
  • I-SPY I and I-SPY II
  • MINT
  • NBRST
  • See also
  • External links
  • References

MammaPrint is a prognostic and predictive diagnostic test for early stage breast cancer patients that assess the risk that a tumor will metastasize to other parts of the body. It gives a binary result, high-risk or low-risk classification, and helps physicians determine whether or not a patient will benefit from chemotherapy. Women with a low risk result can safely forego chemotherapy without decreasing likelihood of disease free survival. MammaPrint is part of the personalized medicine portfolio marketed by Agendia.

MammaPrint is based on the Amsterdam 70-gene breast cancer gene signature and uses formalin-fixed-paraffin-embedded (FFPE) or fresh tissue for microarray analysis. It is a laboratory developed test (LDT) which falls into the class of In Vitro Diagnostic Multivariate Index Assays (IVDMIA). MammaPrint was the first (2007) IVDMIA to be cleared by the Food and Drug Administration (FDA) in a De Novo Classification Process (Evaluation of Automatic Class III Designation) and is the only molecular diagnostic test with a randomized prospective clinical trial validating clinical utility. The test uses RNA isolated from tumor samples and run on custom glass microarray slides in order to determine the expression of a 70-gene signature. The expression profile is then used in a proprietary algorithm to categorically classify the patient as being at either high or low risk of breast cancer recurrence.

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