Ola Landgren1, Jonathan N Hofmann2, Charlene M McShane3, Loredana Santo2, Malin Hultcrantz1,4, Neha Korde1, Sham Mailankody1, Dickran Kazandjian5, Kazunori Murata6, Katie Thoren6, Lakshmi Ramanathan6, Ahmet Dogan7, Even Rustad1, Sydney X Lu1, Theresia Akhlaghi1, Sigurdur Y Kristinsson4,8, Magnus Björkholm4, Sean Devlin9, Mark P Purdue2, Ruth M Pfeiffer2, Ingemar Turesson10. 1. Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York. 2. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland. 3. Cancer Epidemiology and Health Services Research Group, Centre for Public Health, Queen's University, Belfast, Northern Ireland, United Kingdom. 4. Division of Hematology, Department of Medicine, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden. 5. Multiple Myeloma Section, National Cancer Institute, Bethesda, Maryland. 6. Department of Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York. 7. Department of Hematopathology, Memorial Sloan Kettering Cancer Center, New York, New York. 8. Faculty of Medicine, University of Iceland, Reykjavik, Iceland. 9. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York. 10. Myeloma Section, Department of Medicine, University Hospital of Malmo, Malmo, Sweden.
Abstract
IMPORTANCE: Multiple myeloma is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS). Risk models that estimate the risk of progression from MGUS to multiple myeloma use data from a single time point, usually the initial workup. OBJECTIVE: To longitudinally investigate the alterations of serum immune markers with stable vs progressive MGUS. DESIGN, SETTING, AND PARTICIPANTS: This prospective cross-sectional cohort study included 77 469 adult participants aged 55 to 74 years in the screening arm of the National Cancer Institute Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial who had a diagnosis of progressing MGUS (n = 187) or stable MGUS (n = 498), including light-chain subtype, from November 1993, through December 2011. For each participant, all available serially stored prediagnostic serum samples (N = 3266) were obtained. Data analysis was performed from April 2018, to December 2018. MAIN OUTCOMES AND MEASURES: Serum protein and monoclonal immunoglobulin levels, serum free light chains, and serum light chains within each immunoglobulin class were measured. RESULTS: Of 685 individuals included in the study, 461 (67.3%) were men; the mean (SD) age was 69.1 (5.6) years. In cross-sectional modeling, risk factors associated with progressive MGUS were IgA isotype (adjusted odds ratio [OR], 1.80; 95% CI, 1.03-3.13; P = .04), 15 g/L or more monoclonal spike (adjusted OR, 23.5; 95% CI, 8.9-61.9; P < .001), skewed (<0.1 or >10) serum free light chains ratio (adjusted OR, 46.4; 95% CI, 18.4-117.0; P < .001), and severe immunoparesis (≥2 suppressed uninvolved immunoglobulins) (adjusted OR, 19.1; 95% Cl, 7.5-48.3; P < .001). Risk factors associated with progressive light-chain MGUS were skewed serum free light chains ratio (adjusted OR, 44.0; 95% CI, 14.2-136.3; P < .001) and severe immunoparesis (adjusted OR, 48.6; 95% CI, 9.5-248.2; P < .001). In longitudinal analysis of participants with serial samples prior to progression, 23 of 43 participants (53%) had high-risk MGUS before progression; 16 of these 23 (70%) experienced conversion from low-risk or intermediate-risk MGUS within 5 years. Similar results were found for light-chain MGUS. CONCLUSIONS AND RELEVANCE: The findings of evolving risk patterns support annual blood testing and risk assessment for patients with MGUS or light-chain MGUS.
IMPORTANCE: Multiple myeloma is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS). Risk models that estimate the risk of progression from MGUS to multiple myeloma use data from a single time point, usually the initial workup. OBJECTIVE: To longitudinally investigate the alterations of serum immune markers with stable vs progressive MGUS. DESIGN, SETTING, AND PARTICIPANTS: This prospective cross-sectional cohort study included 77 469 adult participants aged 55 to 74 years in the screening arm of the National Cancer Institute Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial who had a diagnosis of progressing MGUS (n = 187) or stable MGUS (n = 498), including light-chain subtype, from November 1993, through December 2011. For each participant, all available serially stored prediagnostic serum samples (N = 3266) were obtained. Data analysis was performed from April 2018, to December 2018. MAIN OUTCOMES AND MEASURES: Serum protein and monoclonal immunoglobulin levels, serum free light chains, and serum light chains within each immunoglobulin class were measured. RESULTS: Of 685 individuals included in the study, 461 (67.3%) were men; the mean (SD) age was 69.1 (5.6) years. In cross-sectional modeling, risk factors associated with progressive MGUS were IgA isotype (adjusted odds ratio [OR], 1.80; 95% CI, 1.03-3.13; P = .04), 15 g/L or more monoclonal spike (adjusted OR, 23.5; 95% CI, 8.9-61.9; P < .001), skewed (<0.1 or >10) serum free light chains ratio (adjusted OR, 46.4; 95% CI, 18.4-117.0; P < .001), and severe immunoparesis (≥2 suppressed uninvolved immunoglobulins) (adjusted OR, 19.1; 95% Cl, 7.5-48.3; P < .001). Risk factors associated with progressive light-chain MGUS were skewed serum free light chains ratio (adjusted OR, 44.0; 95% CI, 14.2-136.3; P < .001) and severe immunoparesis (adjusted OR, 48.6; 95% CI, 9.5-248.2; P < .001). In longitudinal analysis of participants with serial samples prior to progression, 23 of 43 participants (53%) had high-risk MGUS before progression; 16 of these 23 (70%) experienced conversion from low-risk or intermediate-risk MGUS within 5 years. Similar results were found for light-chain MGUS. CONCLUSIONS AND RELEVANCE: The findings of evolving risk patterns support annual blood testing and risk assessment for patients with MGUS or light-chain MGUS.
Authors: Kylee Maclachlan; Benjamin Diamond; Francesco Maura; Jens Hillengass; Ingemar Turesson; C Ola Landgren; Dickran Kazandjian Journal: Best Pract Res Clin Haematol Date: 2020-01-11 Impact factor: 3.020
Authors: Maximilian Merz; Thomas Hielscher; David Schult; Elias K Mai; Marc S Raab; Jens Hillengass; Anja Seckinger; Dirk Hose; Martin Granzow; Anna Jauch; Hartmut Goldschmidt Journal: Leukemia Date: 2019-11-11 Impact factor: 11.528
Authors: Jonathan N Hofmann; Ola Landgren; Rebecca Landy; Troy J Kemp; Loredana Santo; Charlene M McShane; Joseph J Shearer; Qing Lan; Nathaniel Rothman; Ligia A Pinto; Ruth M Pfeiffer; Allan Hildesheim; Hormuzd A Katki; Mark P Purdue Journal: JNCI Cancer Spectr Date: 2019-12-16