Dataset Information

Prevalence and risk of progression of light-chain monoclonal gammopathy of undetermined significance: a retrospective population-based cohort study.

ABSTRACT:

Background

Monoclonal gammopathy of undetermined significance (MGUS) is defined by expression of heavy-chain immunoglobulin (IgH) and is the precursor lesion for 80% of cases of multiple myeloma. The remaining 20% are characterised by absence of IgH expression; we aimed to assess prevalence of a corresponding precursor entity, light-chain MGUS.

Methods

We used a population-based cohort, previously assembled to estimate MGUS prevalence, of 21,463 residents of Olmsted County, MN, USA, aged 50 years and older. We did a serum free light-chain assay on all samples with sufficient serum remaining, and immunofixation electrophoresis was done for all samples with an abnormal free light-chain ratio or abnormal protein electrophoresis results from the original study. Light-chain MGUS was defined as an abnormal free light-chain ratio with no IgH expression, plus increased concentration of the involved light chain. We calculated age-specific and sex-specific prevalence and rates of progression to lymphoproliferative disorders for light-chain and conventional MGUS and assessed incidence of renal disorders in patients with light-chain MGUS.

Findings

610 (3.3%) of 18,357 people tested had an abnormal free light-chain ratio, of whom 213 had IgH expression that was diagnostic of conventional MGUS. 146 of the remaining 397 individuals had an increase of at least one free light chain and met criteria for light-chain MGUS. Prevalence of light-chain MGUS was 0.8% (95% CI 0.7-0.9), contributing to an overall MGUS prevalence of 4.2% (3.9-4.5). Risk of progression to multiple myeloma in patients with light-chain MGUS was 0.3% (0.1-0.8) per 100 person-years. 30 (23%) of 129 patients with light-chain MGUS were diagnosed with renal disease.

Interpretation

We define a clinical entity representing the light-chain equivalent of conventional MGUS and posing a risk of progression to light-chain multiple myeloma and related disorders.

Funding

US National Cancer Institute.

SUBMITTER: Dispenzieri A

PROVIDER: S-EPMC2904571 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundPatients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma.MethodsIn this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria).FindingsWe included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM).InterpretationUse of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies.FundingSU2C Dream Team and Cancer Research UK.