EFFECTS OF CANAGLIFLOZIN ON BETA-CELL FUNCTION AND INSULIN RESISTANCE IN TYPE 2 DIABETES MELLITUS: DATA FROM THE CANVAS TRIAL

 

Certificate Output Instructions

For best output, select "Paper Size" as "A4" and "Margin" as "0" or "None".

To save or print to PDF, please select Print Destination > Save as PDF, enable Background Graphics under "More Settings", then click "Save".

 


 

Certificate Background

   

Presented the abstract " "
(Abstract co-author(s):  )

 

 

E-Poster Presentation

During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center. 

Preparing your E-Poster

Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.

​E-Poster Submission Deadline

Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.​

E-Poster Format Requirements
  • PDF file
  • Layout: Portrait (vertical orientation)
  • One page only (Dim A4: 210 x 297mm or PPT)
  • E-Poster can be prepared in PowerPoint (one (1) PowerPoint slide) but must be saved and submitted as PDF file.
  • File Size: Maximum file size is 2 Megabytes (2 MB)
  • No hyperlinks, animated images, animations, and slide transitions
  • Language: English
  • Include your abstract number
  • E-posters can include QR codes, tables and photos
 
EFFECTS OF CANAGLIFLOZIN ON BETA-CELL FUNCTION AND INSULIN RESISTANCE IN TYPE 2 DIABETES MELLITUS: DATA FROM THE CANVAS TRIAL

Please follow the instructions below to input your abstract title.

Abstract titles should be brief and reflect the content of the abstract.

  • The title will not be accepted if it exceeds 25 words.
  • Type in CAPITAL LETTERS.
  • Lowercase may be used for abbreviations only, for example, mRNA.
HC Arthur
Tang
HC Arthur Tang atang@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Renal and Metabolic Sydney Australia *
Emily K Yeung eyeung@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Renal and Metabolic Sydney Australia -
Amanda Siriwardana asiriwardana@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Renal and Metabolic Sydney Australia -
Luke Buizen lbuizen@georgeinstitute.org The George Institute for Global Health, University of New South Wales, Sydney, Australia Biostatistics and Data Science Division Sydney Australia -
Sydney C.W Tang scwtang@hku.hk School of Clinical Medicine, University of Hong Kong, Hong Kong Medicine Hong Kong Hong Kong, China -
Min Jun mjun@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Renal and Metabolic Sydney Australia -
Sradha Kotwal skotwal@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Renal and Metabolic Sydney Australia -
Clare Arnott carnott@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Cardiovascular Sydney Australia -
David ZI Cherney david.cherney@uhn.ca Toronto General Hospital, University of Toronto, Toronto, Ontario, Canada Medicine Toronto Canada -
Bruce Neal bneal@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia George Institute Australia Sydney Australia -
Vlado Perkovic vlado.perkovic@unsw.edu.au The George Institute for Global Health, University of New South Wales, Sydney, Australia George Institute Australia Sydney Australia -
Hiddo JL Heerspink h.j.lambers.heerspink@umcg.nl The George Institute for Global Health, University of New South Wales, Sydney, Australia George Institute Australia Groningen Netherlands -
Brendon L Neuen bneuen@georgeinstitute.org.au The George Institute for Global Health, University of New South Wales, Sydney, Australia Renal and Metabolic Sydney Australia -
 
 

Sodium–glucose cotransporter 2 (SGLT2) inhibitors improve glycaemic control in those with established type 2 diabetes and reduce the incidence of new onset diabetes in those without it. The homeostatic model assessment of insulin resistance (HOMA-IR) is a validated measure of insulin resistance, while the proinsulin-to-C-peptide (PIC) ratio serves as a surrogate marker of β-cell function. We evaluated the effects of the SGLT2 inhibitor canagliflozin on insulin resistance and β-cell function, as assessed by HOMA-IR and PIC ratio, in patients with type 2 diabetes and high risk of atherosclerotic cardiovascular disease.

We performed a post-hoc analysis of the CANVAS trial, which assessed the effects of canagliflozin on cardiovascular and kidney outcomes in patients with type 2 diabetes at high risk of atherosclerotic cardiovascular disease. We used mixed-effects models for repeated measures to estimate the effects of canagliflozin on changes in log-transformed HOMA-IR and PIC ratio, expressed as geometric mean ratios, over 2 years. We further evaluated whether baseline HOMA-IR and PIC ratio modified the effects of canagliflozin on clinical outcomes, including (i) hospitalization for heart failure or cardiovascular death and (ii) chronic kidney disease progression (≥40% decline in eGFR, kidney failure, or kidney-related death), using Cox regression with treatment-by-subgroup interaction terms.

Overall, 2987 (91.0%) and 1747 (53.2%) participants had available data to calculate HOMA-IR and PIC at baseline. Participants with higher baseline HOMA-IR were more likely to be younger, have higher HbA1c, higher BMI and history of heart failure. Participants with higher baseline PIC ratio were more likely to be younger, male, receiving insulin and have a higher HbA1c. Compared to placebo, canagliflozin also reduced HOMA-IR over two years by 22% (95% CI -18% to -27%; P<0.001; Figure 1). Canagliflozin versus placebo also reduced PIC ratio 12% (95% CI -9% to -14%; P<0.001; Figure 1).

Figure 1: Geometric mean changes over 2 years for PIC and HOMA-IR

Geometric mean change over 2 year for PIC and HOMA-IR

HOMA-IR: Homeostatic Model Assessment of Insulin Resistance

Figure 2a Relative effect of canagliflozin versus placebo on clinical outcomes by PIC tertile

Relative effect of canagliflozin on clinical outcome by PIC tertile

Figure 2b Relative effect of canagliflozin versus placebo on clinical outcomes by HOMA-IR tertile

Relative effect of canagliflozin on clinical outcome by HOMA-IR tertile

In patients with type 2 diabetes, canagliflozin improves markers of β-cell function and insulin resistance, as measured by PIC ratio and HOMA-IR. These findings offer mechanistic insights into the metabolic benefits of SGLT2 inhibition and may help explain observed effects on glycaemic outcomes.  

Kewords