Mass-Fix better predicts for PFS and OS than standard methods among multiple myeloma patients participating on the STAMINA trial (BMT CTN 0702 /07LT)

Angela Dispenzieri, Amrita Krishnan, Bonnie Arendt, Beth Blackwell, Paul K. Wallace, Surendra Dasari, Dan T. Vogl, Yvonne Efebera, Mingwei Fei, Nancy Geller, Sergio Giralt, Theresa Hahn, Alan Howard, Mindy Kohlhagen, Heather Landau, Parameswaran Hari, Marcelo C. Pasquini, Muzaffar H. Qazilbash, Philip McCarthy, Nina ShahDavid H. Vesole, Edward Stadtmauer, David Murray

Research output: Contribution to journalArticlepeer-review

Abstract

Measuring response among patients with multiple myeloma is essential for the care of patients. Deeper responses are associated with better progression free survival (PFS) and overall survival (OS). To test the hypothesis that Mass-Fix, a mass spectrometry-based means to detect monoclonal proteins, is superior to existing methodologies to predict for survival outcomes, samples from the STAMINA trial (NCT01109004), a trial comparing three transplant approaches, were employed. Samples from 575 patients from as many as three time points (post-induction [post-I; pre-maintenance [pre-M]; 1 year post enrollment [1YR]) were tested when available. Four response parameters were assessed: Mass-Fix, serum immunofixation, complete response, and measurable residual disease (MRD) by next generation flow cytometry. Of the four response measures, only MRD and Mass-Fix predicted for PFS and OS at multiple testing points on multivariate analyses. Although MRD drove Mass-Fix from the model for PFS at post-I and pre-M, 1YR Mass-Fix was independent of 1YR MRD. For OS, the only prognostic pre-I measure was Mass-Fix, and the only 1YR measures that were prognostic on multivariate analysis were 1YR MRD and 1YR Mass-Fix. SIFE and CR were not. Mass-Fix is a powerful means to track response.

Original languageEnglish (US)
Article number27
JournalBlood cancer journal
Volume12
Issue number2
DOIs
StatePublished - Feb 2022

ASJC Scopus subject areas

  • Hematology
  • Oncology

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