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Abstract Number: 2658

Dipeptidyl Peptidase-4 Inhibitors In Type 2 Diabetes May Reduce The Risk Of Autoimmune Diseases

Seoyoung C. Kim1, Sebastian Schneeweiss2, Robert J. Glynn3, Michael Doherty3, Allison Goldfine4 and Daniel H. Solomon5,6, 1Div. of Pharmacoepidemiology and Pharmacoeconomics, Div. of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, MA, 2Division of Pharmacoepidemiology, Brigham and Women's Hospital, Boston, MA, 3Brigham and Women's Hospital, Boston, MA, 4Joslin Diabetes Center, Boston, MA, 5Division of Pharmacoepidemiology, Harvard Medical School, Brigham and Women's Hospital, Division of Rheumatology, Division of Pharmacoepidemiology, Boston, MA, 6Division of Rheumatology, Brigham and Women's Hospital, Boston, MA

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: Autoimmune diseases and diabetes

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Session Information

Title: Epidemiology and Health Services Research VI: Risk Factors in Rheumatic Disease Susceptibility

Session Type: Abstract Submissions (ACR)

Background/Purpose: Dipeptidyl peptidase-4 inhibitors (DPP4i), such as linagliptin, saxagliptin, and sitagliptin, are oral glucose-lowering drugs for type 2 diabetes mellitus (T2DM). DPP4 is a transmembrane glycoprotein widely expressed in various cells including fibroblasts, T lymphocytes, and macrophages, and has a co-stimulatory function in the immune response. Altered levels of DPP4 activity were noted in patients with autoimmune diseases (AD) such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), inflammatory bowel disease (IBD), psoriasis, and multiple sclerosis (MS). The objective of this study was to estimate the incidence rate (IR) of systemic AD such as RA, SLE, psoriasis, MS, and IBD in patients with T2DM initiating a DPP4i drug compared to those initiating non-DPP4i oral hypoglycemic agents.

 

Methods: We conducted a population-based cohort study using commercial insurance claims data (2005-2011). Among patients aged ≥40 years with T2DM, two mutually exclusive exposure groups were selected: 1) DPP4i combination therapy (DPP4i and at least 1 other oral non-DPP4i drugs) and 2) non-DPP4i combination therapy (2 or more oral non-DPP4i drugs). Patients with a diagnosis of systemic AD, HIV, and cancer, and use of insulin-containing drugs or immunosuppressive drugs at baseline were excluded. Incidence rates (IRs) were calculated for RA, other AD and composite AD. RA and other AD were defined with ≥2 diagnosis codes that were ≥7 days apart and ≥1 prescription for disease-specific immunosuppressive drugs or steroids. Propensity score (PS)-matched Cox regression models compared the risk of RA or AD in DPP4i initiators compared to non-DPP4i initiators, controlling for baseline demographic factors, comorbidities, medications, and health care utilization. Sensitivity analyses matched on PS compared DPP4i combination therapy initiators separately to sulfonylurea combination therapy initiators and to thiazolidinediones combination therapy initiators. 

Results: We included 58,275 patients starting DPP4i combination therapy 1:1 PS-matched to those starting non-DPP4i combination therapy. Risks of RA and other AD were significantly lower in the DPP4i group vs. non-DPP4i with the HR of 0.64 (95% CI 0.45-0.91) for RA, 0.53 (95% CI 0.39-0.73) for other AD, and 0.57 (95% CI 0.45-0.73) for composite AD (Table). In sensitivity analysis, the risk of other AD and composite AD was significantly reduced in initiators of DPP4i combination therapy compared to sulfonylurea combination therapy and thiazolidinediones combination therapy, but the risk of RA was not.

 

Conclusion: In this large cohort of T2DM patients, initiating DPP4i combination therapy was associated with a decreased risk of incident RA or other AD compared to those initiating non-DPP4i combination therapy. These results suggest possible pharmacologic pathways for reducing the incidence of AD.


 

Table. Risk of autoimmune diseases associated with type 2 DM treatments: PS-matched ‘as treated’ analysis

 

DPP4i

(n=58,275)

Non-DPP4i

(n=58,275)

 

Outcome

Cases

Person-years (PY)

IR *

(95% CI)

HR

Cases

Person-years (PY)

IR *

(95% CI)

HR

RA

47

39,379

1.19

(0.88-1.59)

0.64

(0.45-0.91)

87

48,665

1.79

(1.43-2.21)

Ref

Other autoimmune diseases

59

39,361

1.50

(1.14-1.93)

0.53

(0.39-0.73)

129

48,615

2.65

(2.22-3.15)

Ref

Composite: RA or other autoimmune diseases

105

39,325

2.67

(2.18-3.23)

0.57

(0.45-0.73)

214

48,539

4.41

(3.84-5.04)

Ref

*Per 1,000 PY

The logistic model for PS includes age, sex, comorbidities, smoking, obesity, non-DM medications, number of DM meds, number of primary and specialist visits, and other health care utilization.

 


Disclosure:

S. C. Kim,

Pfizer Inc,

2,

Pfizer and Asisa ,

9;

S. Schneeweiss,

Pfizer Inc, ,

2,

Novartis Pharmaceutical Corporation,

2,

Boehringer Ingelheim,

2,

WHISCON, LLC,

5,

BOOZ and Company,

5;

R. J. Glynn,

AstraZeneca,

2,

Novartis Pharmaceutical Corporation,

2;

M. Doherty,
None;

A. Goldfine,
None;

D. H. Solomon,

Lilly, Amgen, CORRONA,

2,

Lilly, Novartis, BMS, Pfizer,

6,

Lilly, BMS, Novartis,

9.

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