A1c Improvement After Initiating Real-Time Continuous Glucose Monitoring Among People with Type 2 Diabetes Not on Insulin Therapy
Author(s)
Blake C. Liu, MSc, Katia Hannah, BS, MPH, PhD, Poorva Nemlekar, MS, Greg J. Norman, PhD;
Dexcom, Inc, San Diego, CA, USA
Dexcom, Inc, San Diego, CA, USA
Presentation Documents
OBJECTIVES: A1c is a key metric in diabetes management for people with type 2 diabetes (PwT2D). While previous studies in type 1 diabetes have demonstrated A1c improvements with real-time continuous glucose monitoring (rtCGM) systems over intermittently scanned CGM (isCGM), less is known about the difference in glycemic benefits between rtCGM and isCGM in PwT2D, especially among those not on insulin therapy (NIT).
METHODS: A retrospective study was conducted using de-identified US administrative health claims data from Merative™ MarketScan® Research Database (09/2017 to 09/2022). The cohort included CGM-naïve PwT2D NIT who initiated rtCGM or isCGM (index = first CGM claim). Two cohorts were propensity score matched on demographic and healthcare resource utilization at baseline. A1c improvement was measured 12 months pre- (baseline) and post-index (follow-up) by: (1) average change in A1c after CGM initiation and the difference-in-difference (DiD) between cohorts, (2) proportion of PwT2D with an A1c <7% in the follow-up period, and (3) proportion of PwT2D with baseline A1c ≥7% achieving an A1c <7% after CGM initiation.
RESULTS: Among 909 CGM users (rtCGM, n=490; isCGM, n=419), rtCGM users had a greater A1c reduction over time compared to isCGM users (-1.01% vs -0.68%, DiD = -0.32%, p<0.0001). More rtCGM users achieved an A1c level <7% during follow-up compared to isCGM users (52.45% vs. 43.68%, p<0.0001). Additionally, among those with baseline A1c ≥7%, more rtCGM users achieved an A1c <7% at follow-up compared to isCGM users (28.78% vs 21.00%, p<0.0001).
CONCLUSIONS: Findings from this study suggest that rtCGM may be a clinically valuable tool for glycemic management in PwT2D NIT. The greater A1c reduction and higher proportion of patients achieving target A1c levels with rtCGM compared to isCGM highlight its potential to improve long-term diabetes outcomes and support the consideration of rtCGM as a preferred monitoring strategy in clinical practice for PwT2D not on insulin.
METHODS: A retrospective study was conducted using de-identified US administrative health claims data from Merative™ MarketScan® Research Database (09/2017 to 09/2022). The cohort included CGM-naïve PwT2D NIT who initiated rtCGM or isCGM (index = first CGM claim). Two cohorts were propensity score matched on demographic and healthcare resource utilization at baseline. A1c improvement was measured 12 months pre- (baseline) and post-index (follow-up) by: (1) average change in A1c after CGM initiation and the difference-in-difference (DiD) between cohorts, (2) proportion of PwT2D with an A1c <7% in the follow-up period, and (3) proportion of PwT2D with baseline A1c ≥7% achieving an A1c <7% after CGM initiation.
RESULTS: Among 909 CGM users (rtCGM, n=490; isCGM, n=419), rtCGM users had a greater A1c reduction over time compared to isCGM users (-1.01% vs -0.68%, DiD = -0.32%, p<0.0001). More rtCGM users achieved an A1c level <7% during follow-up compared to isCGM users (52.45% vs. 43.68%, p<0.0001). Additionally, among those with baseline A1c ≥7%, more rtCGM users achieved an A1c <7% at follow-up compared to isCGM users (28.78% vs 21.00%, p<0.0001).
CONCLUSIONS: Findings from this study suggest that rtCGM may be a clinically valuable tool for glycemic management in PwT2D NIT. The greater A1c reduction and higher proportion of patients achieving target A1c levels with rtCGM compared to isCGM highlight its potential to improve long-term diabetes outcomes and support the consideration of rtCGM as a preferred monitoring strategy in clinical practice for PwT2D not on insulin.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
RWD108
Topic
Real World Data & Information Systems
Topic Subcategory
Health & Insurance Records Systems
Disease
SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity)