Year: 2020
Type: article
Abstract: The treatment of multiple myeloma (MM) continues to evolve rapidly with arrival of multiple new drugs, and emerging data from randomized trials to guide therapy. Along the disease course, the choice of specific therapy is affected by many variables including age, performance status, comorbidities, and eligibility for stem cell transplantation. In addition, another key variable that affects treatment strategy is risk stratification of patients into standard and high-risk MM. High-risk MM is defined by the presence of t(4;14), t(14;16), t(14;20), gain 1q, del(17p), or p53 mutation. In this paper, we provide algorithms for the treatment of newly diagnosed and relapsed MM based on the best available evidence. We have relied on data from randomized controlled trials whenever possible, and when appropriate trials to guide therapy are not available, our recommendations reflect best practices based on non-randomized data, and expert opinion. Each algorithm has been designed to facilitate easy decision-making for practicing clinicians. In all patients, clinical trials should be considered first, prior to resorting to the standard of care algorithms we outline.
Source: Blood Cancer Journal
Authors: S. Vincent Rajkumar, Shaji Kumar
Institution: Mayo Clinic
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,580
Awards: G1016754749, G1487322093, G2269554244, Mayo Clinic Multiple Myeloma SPORE, G243382380, G2638436676, G4027776925, G555916542, G6618388271, G686564698, Prevalence and Progression of Monoclonal Gammopathies, Onset and biomarkers for progression of monoclonal gammopathies, G9000011126, G9000167924, G9000284860
OpenAlex ID: W3091008757