Modeling progression risk for smoldering multiple myeloma: Results from a prospective clinical study

Benjamin M. Cherry, Neha Korde, Mary Kwok, Elisabet E. Manasanch, Manisha Bhutani, Marcia Mulquin, Diamond Zuchlinski, Mary Ann Yancey, Irina Maric, Katherine R. Calvo, Raul Braylan, Maryalice Stetler-Stevenson, Constance Yuan, Prashant Tembhare, Adriana Zingone, Rene Costello, Mark J. Roschewski, Ola Landgren*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

79 Scopus citations

Abstract

The risk of progression to multiple myeloma (MM) from the precursor condition smoldering MM (SMM) varies considerably among individual patients. Reliable markers for progression to MM are vital to advance the understanding of myeloma precursor disease and for the development of intervention trials designed to delay/prevent MM. The Mayo Clinic and Spanish PETHEMA have proposed models to stratify patient risk based on clinical parameters. The aim of our study was to define the degree of concordance between these two models by comparing the distribution of patients with SMM classified as low, medium and high risk for progression. A total of 77 patients with SMM were enrolled in our prospective natural history study. Per study protocol, each patient was assigned risk scores based on both the Mayo and the Spanish models. The Mayo Clinic model identified 38, 35 and four patients as low, medium and high risk, respectively. The Spanish PETHEMA model classified 17, 22 and 38 patients as low, medium and high risk, respectively. There was significant discordance in overall patient risk classification (28.6% concordance) and in classifying patients as low versus high (p < 0.0001), low versus non-low (p = 0.0007) and high versus non-high (p < 0.0001) risk. There is a need for prospectively validated models to characterize individual patient risk of transformation to MM.

Original languageEnglish
Pages (from-to)2215-2218
Number of pages4
JournalLeukemia and Lymphoma
Volume54
Issue number10
DOIs
StatePublished - Oct 2013
Externally publishedYes

Keywords

  • Disease classification
  • Multiple myeloma
  • Smoldering myeloma

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