Prognostic Validation of SKY92 and Its Combination With ISS in an Independent Cohort of Patients With Multiple Myeloma

Clin Lymphoma Myeloma Leuk. 2017 Sep;17(9):555-562. doi: 10.1016/j.clml.2017.06.020. Epub 2017 Jul 4.

Abstract

Background: High risk and low risk multiple myeloma patients follow a very different clinical course as reflected in their PFS and OS. To be clinically useful, methodologies used to identify high and low risk disease must be validated in representative independent clinical data and available so that patients can be managed appropriately. A recent analysis has indicated that SKY92 combined with the International Staging System (ISS) identifies patients with different risk disease with high sensitivity.

Patients and methods: Here we computed the performance of eight gene expression based classifiers SKY92, UAMS70, UAMS80, IFM15, Proliferation Index, Centrosome Index, Cancer Testis Antigen and HM19 as well as the combination of SKY92/ISS in an independent cohort of 91 newly diagnosed MM patients.

Results: The classifiers identified between 9%-21% of patients as high risk, with hazard ratios (HRs) between 1.9 and 8.2.

Conclusion: Among the eight signatures, SKY92 identified the largest proportion of patients (21%) also with the highest HR (8.2). Our analysis also validated the combination SKY92/ISS for identification of three classes; low risk (42%), intermediate risk (37%) and high risk (21%). Between low risk and high risk classes the HR is >10.

Keywords: Biomarker; Gene expression; In vitro diagnostic clinical assay; Signature.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers, Tumor
  • Cohort Studies
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Neoplastic
  • Humans
  • In Situ Hybridization, Fluorescence
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Multiple Myeloma / diagnosis*
  • Multiple Myeloma / genetics*
  • Multiple Myeloma / mortality
  • Neoplasm Staging / methods*
  • Prognosis
  • Proportional Hazards Models

Substances

  • Biomarkers, Tumor