806-P: Correlation of Derived Time in Range (dTIR) and Time in Range (TIR) in People with Type 2 Diabetes (T2D) Treated with IDegLira (IDL) , Degludec, or Liraglutide: A Post Hoc Analysis of the DUAL I Trial

Abstract

Background and Aims: TIR (blood glucose 70-180 mg/dL) , measured by continuous glucose monitoring (CGM) , provides a more comprehensive picture of glycemic control than A1c alone. Derived TIR (dTIR) , a calculated estimate of TIR, is useful when CGM data are unavailable. This post hoc analysis of DUAL I investigated the correlation between dTIR and TIR in patients with CGM data. Materials and Methods: In DUAL I, people with T2D uncontrolled on oral antidiabetic drugs (n=1663) were randomized 2:1:1 to IDL, degludec or liraglutide, for up to 52 weeks. CGM data were collected using IPro1 and IPro2 (Medtronic) . dTIR was calculated from 9-point self-measured blood glucose (SMBG) profiles (minimum 6 points) . The Pearson correlation coefficient was used to assess correlation between dTIR and TIR at baseline, and at weeks 26 and 52. Also assessed were the correlation between change in dTIR and change in TIR, from baseline to end of trial (EOT) , and the proportion of patients achieving a ≥5% increase in TIR or dTIR at weeks 26 and 52. Results: 260 patients had CGM data. Using dTIR calculated from patients with ≥6-point SMBG profiles, a strong correlation was seen between dTIR and TIR at baseline (n=2observations; correlation 0.8838) , with a moderate correlation also seen at week 26 (n=165; correlation 0.5512) and week 52 (n=152; correlation 0.5184) . Change in dTIR and change in TIR, from baseline to EOT, were also correlated (n=137; correlation 0.7686) . Similar results were seen using dTIR calculated using ≥7- or ≥8-point SMBG profiles. A numerically greater proportion of patients achieved a ≥5% increase in dTIR vs. TIR at weeks 26 and 52 (78% vs. 54% and 62% vs. 50%, respectively) , perhaps due to missed nocturnal hypoglycemia, and limited data points, measured by SMBG. Conclusion: These data support the use of dTIR as a surrogate endpoint when CGM data are unavailable, to provide additional information on glycemic control. Disclosure A.Philis-tsimikas: Advisory Panel; Bayer AG, Novo Nordisk, Research Support; Lilly Diabetes, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Viking Therapeutics. J.M.Dcruz: Employee; Novo Nordisk Global Business Services. R.Sivarathinasami: None. C.De block: Advisory Panel; Abbott Diagnostics, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic, Novo Nordisk, Research Support; Indigo Diabetes, Speaker's Bureau; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk. Funding Novo Nordisk A/S