AUTHOR=Bonello Francesca , Cani Lorenzo , D’Agostino Mattia TITLE=Risk Stratification Before and During Treatment in Newly Diagnosed Multiple Myeloma: From Clinical Trials to the Real-World Setting JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.830922 DOI=10.3389/fonc.2022.830922 ISSN=2234-943X ABSTRACT=

Multiple Myeloma (MM) is a hematologic malignancy characterized by a wide clinical and biological heterogeneity leading to different patient outcomes. Various prognostic tools to stratify newly diagnosed (ND)MM patients into different risk groups have been proposed. At baseline, the standard-of-care prognostic score is the Revised International Staging System (R-ISS), which stratifies patients according to widely available serum markers (i.e., albumin, β 2-microglobulin, lactate dehydrogenase) and high-risk cytogenetic abnormalities detected by fluorescence in situ hybridization. Though this score clearly identifies a low-risk and a high-risk population, the majority of patients are categorized as at “intermediate risk”. Although new prognostic factors identified through molecular assays (e.g., gene expression profiling, next-generation sequencing) are now available and may improve risk stratification, the majority of them need specialized centers and bioinformatic expertise that may preclude their broad application in the real-world setting. In the last years, new tools to monitor response and measurable residual disease (MRD) with very high sensitivity after the start of treatment have been developed. MRD analyses both inside and outside the bone marrow have a strong prognostic impact, and the achievement of MRD negativity may counterbalance the high-risk behavior identified at baseline. All these techniques have been developed in clinical trials. However, their efficient application in real-world clinical practice and their potential role to guide treatment-decision making are still open issues. This mini review will cover currently known prognostic factors identified before and during first-line treatment, with a particular focus on their potential applications in real-world clinical practice.