Cargando…

Testing Mayo Clinic’s New 20/20/20 Risk Model in Another Cohort of Smoldering Myeloma Patients: A Retrospective Study

Background—smoldering multiple myeloma (SMM) risk of progression to multiple myeloma (MM) is highly heterogeneous and several models have been suggested to predict this risk. Lakshman et al. recently proposed a model based on three biomarkers: bone marrow plasma cell (BMPC) percentage > 20%, free...

Descripción completa

Detalles Bibliográficos
Autores principales: Tessier, Camille, Allard, Thomas, Boudreault, Jean-Samuel, Kaedbey, Rayan, Éthier, Vincent, Fortin, Fléchère, Pavic, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161809/
https://www.ncbi.nlm.nih.gov/pubmed/34073289
http://dx.doi.org/10.3390/curroncol28030188
Descripción
Sumario:Background—smoldering multiple myeloma (SMM) risk of progression to multiple myeloma (MM) is highly heterogeneous and several models have been suggested to predict this risk. Lakshman et al. recently proposed a model based on three biomarkers: bone marrow plasma cell (BMPC) percentage > 20%, free light chain ratio (FLCr) > 20 and serum M protein > 20 g/L. The goal of our study was to test this “20/20/20” model in our population and to determine if similar results could be obtained in another cohort of SMM patients. Method—we conducted a retrospective, single center study with 89 patients diagnosed with SMM between January 2008 and December 2019. Results—all three tested biomarkers were associated with an increased risk of progression: BMPC percentage ≥ 20% (hazard ratio [HR]: 4.28 [95%C.I., 1.90–9.61]; p < 0.001), serum M protein ≥ 20 g/L (HR: 4.20 [95%C.I., 1.90–15.53]; p = 0.032) and FLCr ≥ 20 (HR: 3.25 [95%C.I., 1.09–9.71]; p = 0.035). The estimated median time to progression (TTP) was not reached for the low and intermediate risk groups and was 29.1 months (95%C.I., 3.9–54.4) in the high-risk group (p = 0.006). Conclusions—the 20/20/20 risk stratification model adequately predicted progression in our population and is easy to use in various clinical settings.