The association between sglt-2 inhibitor use and progression from monoclonal gammopathy of undetermined significance to multiple myeloma in US veterans

Abstract Introduction Sodium-glucose cotransporter 2 inhibitors (SGLT-2i) are antidiabetic agents with known cardio- and renoprotective effects. SGLT-2i have demonstrated anti-cancer activity; however, their activity in multiple myeloma (MM) remains unclear. We evaluated the association between SGLT-2i use and progression from MGUS to MM in patients with diabetes mellitus (DM) using population-level data. Methods We identified patients diagnosed with MGUS from 1/1/2014 to 12/31/2024 in the nationwide US Veterans Health Administration (VHA) with preceding DM. Diagnoses of MGUS and MM were confirmed by a natural language processing-based algorithm (NLP; Wang et al. JCO CCI 2023). DM was identified via ICD-9/10 codes and DM prescriptions in the VHA, VHA-purchased care, and the linked Medicare Part D claims. We excluded patients who were diagnosed with MGUS before DM or progressed to MM within 6 months. MGUS patients using SGLT-2i within ±1 year of MGUS were matched on follow-up time (±6 months) in a 1:2 ratio to non-users during the same period. Follow-up was the time from MGUS to MM progression, death, or censoring on 6/3/2025, whichever came first. The exposure was time-varying SGLT-2i use during follow-up, assessed in 30-day intervals based on prescription fill dates. The outcome was time from MGUS to MM progression, confirmed by ≥1 record of MM treatment within ±6 months of NLP-confirmed MM. The association between time-varying SGLT-2i use and MM progression was estimated by multivariable, inverse probability of treatment weighting (IPTW)-adjusted, time-to-competing event analysis using a Fine-Gray model with death as a competing risk. Covariates included age, sex, race (Non-Hispanic Black [NHB], Non-Hispanic White [NHW], Other, and Unknown), MGUS subtype (IgG, IgA, or light-chain), M-protein category (e.g., ≥1.5 g/dL), BMI category (underweight, normal weight, overweight, obese), creatinine level (>1.5 mg/dL), anemia status based on ICD-9/10 codes, Charlson Comorbidity Index (CCI), HbA1c level (>7%), months from DM to MGUS (±6 months), MGUS diagnosis year (2014-2019 vs 2020-2024), and DM medication use (i.e., metformin, insulin, glucagon-like peptide-1 receptor agonist [GLP-1RA], sulfonylureas [SU], thiazolidinediones [TZDs], and dipeptidyl peptidase-4 inhibitor [DPP-4i]), all at MGUS diagnosis. IPTW was used to balance covariates between the SGLT-2i use groups. Propensity scores were generated using logistic regression, with a binary outcome indicating SGLT-2i use within ±6 months of MGUS diagnosis. The model included the covariates above to estimate the probability of using SGLT-2i at baseline. Common support was applied to exclude patients with extreme scores. Results Our matched cohort included 2,069 SGLT-2i ever-users and 4,138 non-users. Among ever-users and non-users, the median age was 74.0 (IQR: 68.1-77.8) vs. 74.2 (IQR: 68.6-79.5; p<0.0001) years; 96.7% vs. 96.6% were male (p=0.96); 31.0% vs. 31.7% were NHB, 57.3% vs. 57.3% NHW, 4.1% vs. 3.8% Hispanic, and 2.3% vs. 1.7% other (p=0.61). Baseline characteristics were significantly different in BMI category (higher obesity and lower proportions of underweight, normal weight, and overweight in the SGLT-2i group), anti-DM medication use (greater use of metformin, insulin, GLP-1RA, SU, TZD, and DPP-4i in the SGLT-2i group), creatinine <1.5 mg/dL (higher in the SGLT-2i use group), HbA1c >7% (higher in the SGLT-2i use group), MGUS diagnosis in 2020-2024 (higher in the SGLT-2i use group), CCI (lower in the SGLT-2i use group), time from DM to MGUS diagnosis (higher in the SGLT-2i use group). At a median follow-up of 23.9 (IQR: 14.8-38.9) months for SGLT-2i users vs. 24.6 (IQR: 14.6-39.2; p=0.93), progression occurred in 2.8% vs. 3.9% of patients, respectively (p<0.0001). In the multivariable IPTW-adjusted analysis, SGLT-2i use was associated with reduced MM progression risk (aHR 0.65, 95% CI 0.43–0.99). Other covariates associated with progression included M-protein ≥1.5 g/dL (aHR 7.72, 95% CI 5.32-11.21), age (aHR 0.96, 95% CI 0.95-0.98), HbA1c >7% (aHR 0.68, 95% CI 0.50-0.93), months from DM to MGUS diagnosis (aHR 0.997, 95% CI 0.995-0.999), and MGUS diagnosis year 2020-2024 (aHR 0.55, 95% CI 0.40-0.75). Conclusion In patients with DM and MGUS, SGLT-2i use was associated with a 35% reduced risk of progression to MM. Prospective studies are needed to evaluate whether SGLT-2i may play a role in MM prevention. B.S. and L.L., co–first; T.T. and S.H., co–senior authors.

Authors

Institutions

Publication Details

Journal
Blood
Published
2025-11-03
DOI
https://doi.org/10.1182/blood-2025-4027
Primary Topic
Multiple Myeloma Research and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The association between sglt-2 inhibitor use and progression from monoclonal gammopathy of undetermined significance to multiple myeloma in US veterans

Su‐Hsin Chang, Lawrence Liu, Kristen M. Sanfilippo, Murali Janakiram et al.
Blood
Multiple Myeloma Research and Treatments
article

The association between sglt-2 inhibitor use and progression from monoclonal gammopathy of undetermined significance to multiple myeloma in US veterans

Su‐Hsin Chang, Lawrence Liu, Kristen M. Sanfilippo, Murali Janakiram, Martin William Schoen, Mei Wang, Byron Sigel, Theodore Thomas, Qingyuan Tan
article en

Abstract

Abstract Introduction Sodium-glucose cotransporter 2 inhibitors (SGLT-2i) are antidiabetic agents with known cardio- and renoprotective effects. SGLT-2i have demonstrated anti-cancer activity; however, their activity in multiple myeloma (MM) remains unclear. We evaluated the association between SGLT-2i use and progression from MGUS to MM in patients with diabetes mellitus (DM) using population-level data. Methods We identified patients diagnosed with MGUS from 1/1/2014 to 12/31/2024 in the nationwide US Veterans Health Administration (VHA) with preceding DM. Diagnoses of MGUS and MM were confirmed by a natural language processing-based algorithm (NLP; Wang et al. JCO CCI 2023). DM was identified via ICD-9/10 codes and DM prescriptions in the VHA, VHA-purchased care, and the linked Medicare Part D claims. We excluded patients who were diagnosed with MGUS before DM or progressed to MM within 6 months. MGUS patients using SGLT-2i within ±1 year of MGUS were matched on follow-up time (±6 months) in a 1:2 ratio to non-users during the same period. Follow-up was the time from MGUS to MM progression, death, or censoring on 6/3/2025, whichever came first. The exposure was time-varying SGLT-2i use during follow-up, assessed in 30-day intervals based on prescription fill dates. The outcome was time from MGUS to MM progression, confirmed by ≥1 record of MM treatment within ±6 months of NLP-confirmed MM. The association between time-varying SGLT-2i use and MM progression was estimated by multivariable, inverse probability of treatment weighting (IPTW)-adjusted, time-to-competing event analysis using a Fine-Gray model with death as a competing risk. Covariates included age, sex, race (Non-Hispanic Black [NHB], Non-Hispanic White [NHW], Other, and Unknown), MGUS subtype (IgG, IgA, or light-chain), M-protein category (e.g., ≥1.5 g/dL), BMI category (underweight, normal weight, overweight, obese), creatinine level (>1.5 mg/dL), anemia status based on ICD-9/10 codes, Charlson Comorbidity Index (CCI), HbA1c level (>7%), months from DM to MGUS (±6 months), MGUS diagnosis year (2014-2019 vs 2020-2024), and DM medication use (i.e., metformin, insulin, glucagon-like peptide-1 receptor agonist [GLP-1RA], sulfonylureas [SU], thiazolidinediones [TZDs], and dipeptidyl peptidase-4 inhibitor [DPP-4i]), all at MGUS diagnosis. IPTW was used to balance covariates between the SGLT-2i use groups. Propensity scores were generated using logistic regression, with a binary outcome indicating SGLT-2i use within ±6 months of MGUS diagnosis. The model included the covariates above to estimate the probability of using SGLT-2i at baseline. Common support was applied to exclude patients with extreme scores. Results Our matched cohort included 2,069 SGLT-2i ever-users and 4,138 non-users. Among ever-users and non-users, the median age was 74.0 (IQR: 68.1-77.8) vs. 74.2 (IQR: 68.6-79.5; p<0.0001) years; 96.7% vs. 96.6% were male (p=0.96); 31.0% vs. 31.7% were NHB, 57.3% vs. 57.3% NHW, 4.1% vs. 3.8% Hispanic, and 2.3% vs. 1.7% other (p=0.61). Baseline characteristics were significantly different in BMI category (higher obesity and lower proportions of underweight, normal weight, and overweight in the SGLT-2i group), anti-DM medication use (greater use of metformin, insulin, GLP-1RA, SU, TZD, and DPP-4i in the SGLT-2i group), creatinine <1.5 mg/dL (higher in the SGLT-2i use group), HbA1c >7% (higher in the SGLT-2i use group), MGUS diagnosis in 2020-2024 (higher in the SGLT-2i use group), CCI (lower in the SGLT-2i use group), time from DM to MGUS diagnosis (higher in the SGLT-2i use group). At a median follow-up of 23.9 (IQR: 14.8-38.9) months for SGLT-2i users vs. 24.6 (IQR: 14.6-39.2; p=0.93), progression occurred in 2.8% vs. 3.9% of patients, respectively (p<0.0001). In the multivariable IPTW-adjusted analysis, SGLT-2i use was associated with reduced MM progression risk (aHR 0.65, 95% CI 0.43–0.99). Other covariates associated with progression included M-protein ≥1.5 g/dL (aHR 7.72, 95% CI 5.32-11.21), age (aHR 0.96, 95% CI 0.95-0.98), HbA1c >7% (aHR 0.68, 95% CI 0.50-0.93), months from DM to MGUS diagnosis (aHR 0.997, 95% CI 0.995-0.999), and MGUS diagnosis year 2020-2024 (aHR 0.55, 95% CI 0.40-0.75). Conclusion In patients with DM and MGUS, SGLT-2i use was associated with a 35% reduced risk of progression to MM. Prospective studies are needed to evaluate whether SGLT-2i may play a role in MM prevention. B.S. and L.L., co–first; T.T. and S.H., co–senior authors.

BloodVol. 146(Supplement 1)
Cedars-Sinai Medical Center (US), Veterans Health Administration (US), St. Louis VA Medical Center (US), City of Hope (US), Department of Veterans Affairs (AU), Saint Louis University (US)
Openalex Percentile: Top 47%
Multiple Myeloma Research and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.