Association between excess body mass index trajectory and change in monoclonal protein level in patients diagnosed with monoclonal gammopathy of undetermined significance.

person Lawrence Liu City of Hope National Comprehensive Cancer Center, Duarte, CA info_outline Lawrence Liu, Nikhil Grandhi, Mei Wang, Theodore Seth Thomas, Akhil Kumar, Kristen Marie Sanfilippo, Graham A. Colditz, Su-Hsin Chang

Authors person Lawrence Liu City of Hope National Comprehensive Cancer Center, Duarte, CA info_outline Lawrence Liu, Nikhil Grandhi, Mei Wang, Theodore Seth Thomas, Akhil Kumar, Kristen Marie Sanfilippo, Graham A. Colditz, Su-Hsin Chang Organizations City of Hope National Comprehensive Cancer Center, Duarte, CA, St. Louis Veterans Affairs Medical Center, St. Louis, MO, Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, Saint Louis VA Medical Center John Cochran Division, St. Louis, MO, Research Service, St. Louis Veterans Affairs Medical Center, St. Louis, MO, Washington University in St. Louis, St. Louis, MO, Siteman Cancer Ctr, Saint Louis, MO, Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO Abstract Disclosures Research Funding U.S. National Institutes of Health U.S. National Institutes of Health Background: Obesity is a known risk factor for the development of multiple myeloma (MM) and for progression of its asymptomatic premalignant state, monoclonal gammopathy of undetermined significance (MGUS) to MM. Prior studies have demonstrated that monoclonal protein (M-spike) at MGUS diagnosis as well as high M-spike velocity within a year following MGUS diagnosis predict progression of MGUS to MM, making M-spike a useful, readily available, and less invasive (compared to bone marrow biopsy) marker to assess progression risk. However, no studies have evaluated to what extent exposure to high body mass index (BMI) over time influences M-spike trajectory. Methods: Patients diagnosed with MGUS from 1999-2021 in the Veterans Health Administration were identified. We used a natural language processing-based algorithm to confirm MGUS diagnosis and progression to smoldering MM or MM. MGUS patients without IgM or IgD subtype or Diabetes Mellitus and were black or white were included in the analysis. Other exclusion criteria were progression within 5 years of MGUS diagnosis, patients without M-spike level within a year before or after MGUS diagnosis, and patients without BMI data 3 years or more after MGUS diagnosis. The exposure was the trajectory of excess BMI (defined as BMI > 25 kg/m 2 ), defined by an area under the curve (AUC) of excess BMI during the 5 years following MGUS diagnosis. The outcome was continuous M-spike trajectory post-MGUS diagnosis since a prior study demonstrated that this was a reliable marker for progression risk A multivariable mixed model was used to estimate the association of excess BMI trajectory AUC with M-spike trajectory to control for correlation between M-spike values overtime. The covariates included BMI at MGUS diagnosis, M-spike level ( > = 1.5g/dL) at MGUS diagnosis, age at MGUS diagnosis, sex, race, MGUS heavy chain subtype, and light-chain MGUS. Results: After applying the inclusion and exclusion criteria, the analytic cohort consisted of 6757 MGUS patients. Our multivariable analysis demonstrated a positive association between excess BMI trajectory and increasing M-spike trajectory (β = 0.005, p = 0.007). Conclusions: In patients diagnosed with MGUS, increasing BMI over time following MGUS diagnosis was associated with increasing M-spike level. This further supports the relationship between obesity and weight gain in the pathway of MGUS to MM progression.