[Skip to Content]
[Skip to Content Landing]
Figure 1.
Construction of the Base and Study Cohorts
Construction of the Base and Study Cohorts

HAART indicates highly active antiretroviral therapy; HIV, human immunodeficiency virus.

Figure 2.
Association Between the Use of Incretin-Based Drugs and the Risk of Acute Pancreatitis Among Patients With Type 2 Diabetes
Association Between the Use of Incretin-Based Drugs and the Risk of Acute Pancreatitis Among Patients With Type 2 Diabetes

The reference category was current use of 2 or more oral antidiabetic drugs. The size of the boxes is proportional to the weight of a given participating site in the random-effects meta-analysis. The I2 (percentage of the total variance due to between-study heterogeneity) was 13.6% (P = .33 for heterogeneity). CPRD indicates Clinical Practice Research Datalink; HR, hazard ratio.

Figure 3.
Sensitivity Analyses for the Association Between the Use of Incretin-Based Drugs and the Incidence of Acute Pancreatitis
Sensitivity Analyses for the Association Between the Use of Incretin-Based Drugs and the Incidence of Acute Pancreatitis

HR indicates hazard ratio; NA, not applicable.

aDefined as current use of incretin-based drugs in combination with at least 1 other antidiabetic drug.

bThe models were adjusted for a composite variable of microvascular complications variable, categorical variables were converted to their continuous counterparts where possible, and insulin, oral antidiabetic drug monotherapy, and not currently exposed were collapsed to a single “other exposure” category.

cThe models included only exposure (current use of incretin-based drugs, current use of oral antidiabetic combinations, and other exposure) and the Deyo version of the Charlson comorbidity index.

Table 1.  
Characteristics of Acute Pancreatitis Cases and Matched Controls Among Patients With Type 2 Diabetesa
Characteristics of Acute Pancreatitis Cases and Matched Controls Among Patients With Type 2 Diabetesa
Table 2.  
Association Between Use of Incretin-Based Drugs and the Incidence of Acute Pancreatitisa
Association Between Use of Incretin-Based Drugs and the Incidence of Acute Pancreatitisa
1.
Holst  JJ.  The physiology of glucagon-like peptide 1.  Physiol Rev. 2007;87(4):1409-1439.PubMedGoogle ScholarCrossref
2.
Elashoff  M, Matveyenko  AV, Gier  B, Elashoff  R, Butler  PC.  Pancreatitis, pancreatic, and thyroid cancer with glucagon-like peptide-1–based therapies.  Gastroenterology. 2011;141(1):150-156.PubMedGoogle ScholarCrossref
3.
Raschi  E, Piccinni  C, Poluzzi  E, Marchesini  G, De Ponti  F.  The association of pancreatitis with antidiabetic drug use: gaining insight through the FDA pharmacovigilance database.  Acta Diabetol. 2013;50(4):569-577.PubMedGoogle ScholarCrossref
4.
Faillie  JL, Babai  S, Crépin  S,  et al; French Pharmacovigilance Centers Network.  Pancreatitis associated with the use of GLP-1 analogs and DPP-4 inhibitors: a case/non-case study from the French Pharmacovigilance Database.  Acta Diabetol. 2014;51(3):491-497.PubMedGoogle Scholar
5.
Shihab  HM, Akande  T, Armstrong  K, Singh  S, Loke  YK.  Risk of pancreatic adverse events associated with the use of glucagon-like peptide-1 receptor agonist and dipeptidyl peptidase-4 inhibitor drugs: a systematic review and meta-analysis of randomized trials.  World J Meta-Anal. 2015;3:254-283.Google ScholarCrossref
6.
Dore  DD, Seeger  JD, Arnold Chan  K.  Use of a claims-based active drug safety surveillance system to assess the risk of acute pancreatitis with exenatide or sitagliptin compared to metformin or glyburide.  Curr Med Res Opin. 2009;25(4):1019-1027.PubMedGoogle ScholarCrossref
7.
Garg  R, Chen  W, Pendergrass  M.  Acute pancreatitis in type 2 diabetes treated with exenatide or sitagliptin: a retrospective observational pharmacy claims analysis.  Diabetes Care. 2010;33(11):2349-2354.PubMedGoogle ScholarCrossref
8.
Dore  DD, Bloomgren  GL, Wenten  M,  et al.  A cohort study of acute pancreatitis in relation to exenatide use.  Diabetes Obes Metab. 2011;13(6):559-566.PubMedGoogle ScholarCrossref
9.
Romley  JA, Goldman  DP, Solomon  M, McFadden  D, Peters  AL.  Exenatide therapy and the risk of pancreatitis and pancreatic cancer in a privately insured population.  Diabetes Technol Ther. 2012;14(10):904-911.PubMedGoogle ScholarCrossref
10.
Wenten  M, Gaebler  JA, Hussein  M,  et al.  Relative risk of acute pancreatitis in initiators of exenatide twice daily compared with other anti-diabetic medication: a follow-up study.  Diabet Med. 2012;29(11):1412-1418.PubMedGoogle ScholarCrossref
11.
Eurich  DT, Simpson  S, Senthilselvan  A, Asche  CV, Sandhu-Minhas  JK, McAlister  FA.  Comparative safety and effectiveness of sitagliptin in patients with type 2 diabetes: retrospective population based cohort study.  BMJ. 2013;346:f2267.PubMedGoogle ScholarCrossref
12.
Singh  S, Chang  HY, Richards  TM, Weiner  JP, Clark  JM, Segal  JB.  Glucagonlike peptide 1–based therapies and risk of hospitalization for acute pancreatitis in type 2 diabetes mellitus: a population-based matched case-control study.  JAMA Intern Med. 2013;173(7):534-539.PubMedGoogle ScholarCrossref
13.
Dore  DD, Hussein  M, Hoffman  C, Pelletier  EM, Smith  DB, Seeger  JD.  A pooled analysis of exenatide use and risk of acute pancreatitis.  Curr Med Res Opin. 2013;29(12):1577-1586.PubMedGoogle ScholarCrossref
14.
Funch  D, Gydesen  H, Tornøe  K, Major-Pedersen  A, Chan  KA.  A prospective, claims-based assessment of the risk of pancreatitis and pancreatic cancer with liraglutide compared to other antidiabetic drugs.  Diabetes Obes Metab. 2014;16(3):273-275.PubMedGoogle ScholarCrossref
15.
Giorda  CB, Picariello  R, Nada  E,  et al.  Incretin therapies and risk of hospital admission for acute pancreatitis in an unselected population of European patients with type 2 diabetes: a case-control study.  Lancet Diabetes Endocrinol. 2014;2(2):111-115.PubMedGoogle ScholarCrossref
16.
Faillie  JL, Azoulay  L, Patenaude  V, Hillaire-Buys  D, Suissa  S.  Incretin based drugs and risk of acute pancreatitis in patients with type 2 diabetes: cohort study.  BMJ. 2014;348:g2780.PubMedGoogle ScholarCrossref
17.
Chou  HC, Chen  WW, Hsiao  FY.  Acute pancreatitis in patients with type 2 diabetes mellitus treated with dipeptidyl peptidase-4 inhibitors: a population-based nested case-control study.  Drug Saf. 2014;37(7):521-528.PubMedGoogle ScholarCrossref
18.
Liao  KF, Lin  CL, Lai  SW, Chen  WC.  Sitagliptin use and risk of acute pancreatitis in type 2 diabetes mellitus: a population-based case-control study in Taiwan.  Eur J Intern Med. 2016;27:76-79.PubMedGoogle ScholarCrossref
19.
Tseng  CH.  Sitagliptin increases acute pancreatitis risk within 2 years of its initiation: a retrospective cohort analysis of the National Health Insurance database in Taiwan.  Ann Med. 2015;47(7):561-569.PubMedGoogle ScholarCrossref
20.
Clemens  KK, McArthur  E, Fleet  JL, Hramiak  I, Garg  AX.  The risk of pancreatitis with sitagliptin therapy in older adults: a population-based cohort study.  CMAJ Open. 2015;3(2):E172-E181.PubMedGoogle ScholarCrossref
21.
Chang  HY, Hsieh  CF, Singh  S, Tang  W, Chiang  YT, Huang  WF.  Anti-diabetic therapies and the risk of acute pancreatitis: a nationwide retrospective cohort study from Taiwan.  Pharmacoepidemiol Drug Saf. 2015;24(6):567-575.PubMedGoogle ScholarCrossref
22.
Soranna  D, Bosetti  C, Casula  M,  et al.  Incretin-based drugs and risk of acute pancreatitis: a nested-case control study within a healthcare database.  Diabetes Res Clin Pract. 2015;108(2):243-249.PubMedGoogle ScholarCrossref
23.
Thomsen  RW, Pedersen  L, Møller  N, Kahlert  J, Beck-Nielsen  H, Sørensen  HT.  Incretin-based therapy and risk of acute pancreatitis: a nationwide population-based case-control study.  Diabetes Care. 2015;38(6):1089-1098.PubMedGoogle ScholarCrossref
24.
Azoulay  L.  Incretin-based drugs and adverse pancreatic events: almost a decade later and uncertainty remains.  Diabetes Care. 2015;38(6):951-953.PubMedGoogle ScholarCrossref
25.
Egan  AG, Blind  E, Dunder  K,  et al.  Pancreatic safety of incretin-based drugs—FDA and EMA assessment.  N Engl J Med. 2014;370(9):794-797.PubMedGoogle ScholarCrossref
26.
Suissa  S, Henry  D, Caetano  P,  et al; Canadian Network for Observational Drug Effect Studies (CNODES).  CNODES: the Canadian Network for Observational Drug Effect Studies.  Open Med. 2012;6(4):e134-e140.PubMedGoogle Scholar
27.
Azoulay  L, Filion  KB, Platt  RW,  et al; Canadian Network for Observational Drug Effect Studies Investigators.  Incretin based drugs and the risk of pancreatic cancer: international multicentre cohort study.  BMJ. 2016;352:i581.PubMedGoogle ScholarCrossref
28.
Filion  KB, Azoulay  L, Platt  RW,  et al; CNODES Investigators.  A multicenter observational study of incretin-based drugs and heart failure.  N Engl J Med. 2016;374(12):1145-1154.PubMedGoogle ScholarCrossref
29.
Herrett  E, Gallagher  AM, Bhaskaran  K,  et al.  Data Resource Profile: Clinical Practice Research Datalink (CPRD).  Int J Epidemiol. 2015;44(3):827-836.PubMedGoogle ScholarCrossref
30.
Dassopoulos  T, Ehrenpreis  ED.  Acute pancreatitis in human immunodeficiency virus-infected patients: a review.  Am J Med. 1999;107(1):78-84.PubMedGoogle ScholarCrossref
31.
Suissa  S. Novel approaches to pharmacoepidemiology study design and statistical analysis. In: Strom  B, ed.  Pharmacoepidemiology. 4th ed. Chichester, England: John Wiley & Sons; 2005:811-829.
32.
Essebag  V, Platt  RW, Abrahamowicz  M, Pilote  L.  Comparison of nested case-control and survival analysis methodologies for analysis of time-dependent exposure.  BMC Med Res Methodol. 2005;5(1):5.PubMedGoogle ScholarCrossref
33.
Suissa  S.  The quasi-cohort approach in pharmacoepidemiology: upgrading the nested case-control.  Epidemiology. 2015;26(2):242-246.PubMedGoogle ScholarCrossref
34.
Moores  K, Gilchrist  B, Carnahan  R, Abrams  T.  A systematic review of validated methods for identifying pancreatitis using administrative data.  Pharmacoepidemiol Drug Saf. 2012;21(suppl 1):194-202.PubMedGoogle ScholarCrossref
35.
Inzucchi  SE, Bergenstal  RM, Buse  JB,  et al; American Diabetes Association (ADA); European Association for the Study of Diabetes (EASD).  Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).  Diabetes Care. 2012;35(6):1364-1379.PubMedGoogle ScholarCrossref
36.
Schneeweiss  S, Seeger  JD, Maclure  M, Wang  PS, Avorn  J, Glynn  RJ.  Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data.  Am J Epidemiol. 2001;154(9):854-864.PubMedGoogle ScholarCrossref
37.
US Food and Drug Administration. Information for Healthcare Professionals. Exenatide (marketed as Byetta)— 8/2008 Update. http://www.fda.gov/Drugs/DrugSafety/PostmarketDrugSafetyInformationforPatientsandProviders/ucm124713.htm. Published August 18, 2008. Accessed May 23, 2014.
38.
Deyo  RA, Cherkin  DC, Ciol  MA.  Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases.  J Clin Epidemiol. 1992;45(6):613-619.PubMedGoogle ScholarCrossref
39.
DerSimonian  R, Laird  N.  Meta-analysis in clinical trials.  Control Clin Trials. 1986;7(3):177-188.PubMedGoogle ScholarCrossref
40.
Suissa  S, Azoulay  L.  Metformin and the risk of cancer: time-related biases in observational studies.  Diabetes Care. 2012;35(12):2665-2673.PubMedGoogle ScholarCrossref
41.
Scirica  BM, Bhatt  DL, Braunwald  E,  et al; SAVOR-TIMI 53 Steering Committee and Investigators.  Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus.  N Engl J Med. 2013;369(14):1317-1326.PubMedGoogle ScholarCrossref
42.
White  WB, Cannon  CP, Heller  SR,  et al; EXAMINE Investigators.  Alogliptin after acute coronary syndrome in patients with type 2 diabetes.  N Engl J Med. 2013;369(14):1327-1335.PubMedGoogle ScholarCrossref
43.
Green  JB, Bethel  MA, Armstrong  PW,  et al; TECOS Study Group.  Effect of sitagliptin on cardiovascular outcomes in type 2 diabetes.  N Engl J Med. 2015;373(3):232-242.PubMedGoogle ScholarCrossref
44.
Pfeffer  MA, Claggett  B, Diaz  R,  et al; ELIXA Investigators.  Lixisenatide in patients with type 2 diabetes and acute coronary syndrome.  N Engl J Med. 2015;373(23):2247-2257.PubMedGoogle ScholarCrossref
45.
Ray  WA.  Evaluating medication effects outside of clinical trials: new-user designs.  Am J Epidemiol. 2003;158(9):915-920.PubMedGoogle ScholarCrossref
46.
Benoit  SR, Fleming  R, Philis-Tsimikas  A, Ji  M.  Predictors of glycemic control among patients with type 2 diabetes: a longitudinal study.  BMC Public Health. 2005;5:36.PubMedGoogle ScholarCrossref
Original Investigation
October 2016

Association Between Incretin-Based Drugs and the Risk of Acute Pancreatitis

Author Affiliations
  • 1Center for Clinical Epidemiology, Lady Davis Research Institute, Jewish General Hospital, Montreal, Quebec, Canada
  • 2Department of Oncology, McGill University, Montreal, Quebec, Canada
  • 3Department of Medicine, McGill University, Montreal, Quebec, Canada
  • 4Departments of Pediatrics and of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
  • 5The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
  • 6Manitoba Centre for Health Policy, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
  • 7Department of Family Medicine, McMaster University, Hamilton, Ontario, Canada
  • 8Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
  • 9Department of Medicine, Western University, London, Ontario, Canada
  • 10Department of Internal Medicine, University of Montreal Health Centre, Montreal, Quebec, Canada
  • 11Health Quality Council, Saskatoon, Saskatchewan, Canada
  • 12Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
  • 13Institute of Health Policy, Management and Evaluation, University of Toronto, Ontario, Toronto
  • 14Department of Family Medicine, University of Calgary, Calgary, Alberta, Canada
JAMA Intern Med. 2016;176(10):1464-1473. doi:10.1001/jamainternmed.2016.1522
Abstract

Importance  The association between incretin-based drugs, such as dipeptidyl peptidase 4 (DPP-4) inhibitors and glucagon-like peptide 1 (GLP-1) agonists, and acute pancreatitis is controversial.

Objective  To determine whether the use of incretin-based drugs, compared with the use of 2 or more other oral antidiabetic drugs, is associated with an increased risk of acute pancreatitis.

Design, Setting, and Participants  A large, international, multicenter, population-based cohort study was conducted using combined health records from 7 participating sites in Canada, the United States, and the United Kingdom. An overall cohort of 1 532 513 patients with type 2 diabetes initiating the use of antidiabetic drugs between January 1, 2007, and June 30, 2013, was included, with follow-up until June 30, 2014.

Exposures  Current use of incretin-based drugs compared with current use of at least 2 oral antidiabetic drugs.

Main Outcomes and Measures  Nested case-control analyses were conducted including hospitalized patients with acute pancreatitis matched with up to 20 controls on sex, age, cohort entry date, duration of treated diabetes, and follow-up duration. Hazard ratios (HRs) and 95% CIs for hospitalized acute pancreatitis were estimated and compared current use of incretin-based drugs with current use of 2 or more oral antidiabetic drugs. Secondary analyses were performed to assess whether the risk varied by class of drug (DPP-4 inhibitors and GLP-1 agonists) or by duration of use. Site-specific HRs were pooled using random-effects models.

Results  Of 1 532 513 patients included in the analysis, 781 567 (51.0%) were male; mean age was 56.6 years. During 3 464 659 person-years of follow-up, 5165 patients were hospitalized for acute pancreatitis (incidence rate, 1.49 per 1000 person-years). Compared with current use of 2 or more oral antidiabetic drugs, current use of incretin-based drugs was not associated with an increased risk of acute pancreatitis (pooled adjusted HR, 1.03; 95% CI, 0.87-1.22). Similarly, the risk did not vary by drug class (DPP-4 inhibitors: pooled adjusted HR, 1.09; 95% CI, 0.86-1.22; GLP-1 agonists: pooled adjusted HR, 1.04; 95% CI, 0.81-1.35) and there was no evidence of a duration-response association.

Conclusions and Relevance  In this large population-based study, use of incretin-based drugs was not associated with an increased risk of acute pancreatitis compared with other oral antidiabetic drugs.

Introduction

Dipeptidylpeptidase 4 (DPP-4) inhibitors and glucagon-like peptide 1 (GLP-1) agonists are incretin-based drugs that are widely used in the treatment of type 2 diabetes. Despite lowering the risk of hypoglycemia and having favorable effects on body weight compared with other antidiabetic drugs,1 there have been concerns that the use of incretin-based drugs may increase the risk of pancreatic-related events. Indeed, analyses24 of adverse events databases have associated the use of incretin-based drugs with an increased risk of acute pancreatitis, although such analyses have well-known limitations. In addition, in a meta-analysis5 of randomized clinical trials (RCTs), incretin-based drugs were associated with an increased risk of pancreatic enzyme level elevation, but the association with acute pancreatitis was inconclusive because of sparse data. This association was also assessed in several observational studies, but these have generated conflicting findings.623 Such discrepancies may be the result of important methodologic limitations, such as confounding by indication, and none were adequately powered to detect a modest increased risk of this rare outcome.24

Thus, given the continued concerns regarding the safety of incretin-based drugs,25 the Canadian Network for Observational Drug Effect Studies (CNODES)26 assessed their association with 3 clinically important adverse events, including pancreatic cancer27 and heart failure,28 and acute pancreatitis. We describe a large, multicenter study using health records from 3 countries to determine whether the use of incretin-based drugs is associated with an increased risk of acute pancreatitis in patients with type 2 diabetes.

Box Section Ref ID

Key Points

  • Question Is the use of the incretin-based drugs (glucagon-like peptide 1 agonist and dipeptidyl peptidase 4 inhibitors) associated with an increased risk of acute pancreatitis?

  • Findings In this international population-based study of 1.5 million patients with type 2 diabetes, compared with other antidiabetic drugs, the use of incretin-based agents was not associated with an overall increased risk of acute pancreatitis. Similarly, there was no association by duration of use and by type of incretin-based drug.

  • Meaning The findings of this real-world study provide some reassurance that the use of incretin-based drugs is not associated with an increased risk of acute pancreatitis.

Methods
Data Sources

This cohort study used the administrative and electronic medical record databases from 7 participating sites across 3 countries. The data sources included 5 Canadian provinces (Alberta, Manitoba, Ontario, Quebec, and Saskatchewan), the United States (MarketScan), and the United Kingdom (Clinical Practice Research Datalink [CPRD]).29 The Canadian databases include patient-level information on prescription drug claims, hospitalization data, and physician billings; the Ontario data were restricted to patients 65 years or older; the US MarketScan database includes medical information from individuals and their dependents insured by private health insurance plans; and the UK CPRD database contains complete primary care medical records for more than 13 million individuals enrolled in more than 680 general practices and has been shown to be representative of the UK population.

This was a large, international, multicenter, population-based cohort study (clinicaltrials.gov identifier: NCT02476760). All participating sites followed a common analytical protocol that was approved by the institutional review boards at all participating sites (Conjoint Health Research Ethics Board, University of Saskatchewan Research Ethics Office, University of Manitoba Health Research Ethics Board, University of British Columbia Office of Research Ethics, Sunnybrook Health Sciences Centre, Jewish General Hospital Research Ethics Office, and the Independent Scientific Advisory Committee of the CPRD [protocol number 14_119R]). All data were deidentified for research purposes; thus, patient informed consent was not necessary.

Study Population

At each participating site, a base cohort was assembled consisting of all patients who initiated treatment with a first-ever prescription for a noninsulin antidiabetic drug. These agents included metformin, sulfonylureas, thiazolidinediones, DPP-4 inhibitors, GLP-1 agonists, α-glucosidase inhibitors, and meglitinides, from the earliest date of data availability in each participating site up to June 30, 2013, or the most recent date of data availability at each participating site. Patients with the following characteristics were then sequentially excluded at the time of the first prescription for a noninsulin antidiabetic drug: age younger than 18 years (or the minimum age for which prescription data are available plus 365 days), less than 365 days of medical history in the database before the first prescription for a noninsulin antidiabetic drug, a previous insulin prescription (as this may indicate more advanced disease), and women with a history of polycystic ovarian syndrome or a diagnosis of gestational diabetes in the 365 days before the first prescription for a noninsulin antidiabetic drug since these conditions are other possible indications for use of metformin.

Within the base cohort, a cohort consisting of all patients who initiated use of a new antidiabetic drug class any time after incretin-based drugs entered the market in each participating site until June 30, 2013 (or the most recent date of data availability at each participating site) was identified. These cohort members included individuals who initiated treatment with an antidiabetic drug (ie, first-ever prescription of a noninsulin antidiabetic drug) as well as those who added or switched to an antidiabetic drug class not previously identified in their medication history. The date of this new prescription defined cohort entry. Patients were then sequentially excluded if they met the following criteria at any time before cohort entry: previous diagnosis of pancreatic cancer, history of pancreatectomy or pancreatic injury, presence of congenital defects of the pancreas, diagnosis of cystic fibrosis or lupus erythematosus, bariatric surgery, or diagnosis of human immunodeficiency virus or treatment with highly active antiretroviral therapy (a known risk factor for acute pancreatitis30). Finally, patients hospitalized for acute pancreatitis (defined below) in the 30 days before cohort entry were excluded.

All patients meeting the study inclusion criteria were monitored from cohort entry until a hospitalization for acute pancreatitis (defined below) or censored on a new diagnosis of human immunodeficiency virus or prescription for highly active antiretroviral therapy, death from any cause, end of coverage in the database, or end of the study period (June 30, 2014, or the most recent date of data availability at each participating site), whichever occurred first.

Case-Control Selection

Nested case-control analyses were conducted within the cohort in each participating site. This approach was chosen because of the size of the cohorts and the time-varying nature of exposure.31 Risk-set sampling was used for the matching of controls to cases, which produces odds ratios that are unbiased estimators of hazard ratios (HRs).3133

Cases consisted of all patients with a hospital admission for acute pancreatitis during follow-up (International Classification of Diseases, Ninth Revision, code 577.0, and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, codes K85.0, K85.1, K85.2, K85.3, K85.8, and K85.9 in either the primary [or most responsible] or secondary position). For each case, the index date was defined by the date of the hospital admission. The recording of hospitalized acute pancreatitis events was shown to have good positive and negative predictive values.34

Up to 20 controls were randomly selected for each case, matched on age (±365 days), date of cohort entry (±180 days), sex, duration of pharmacologically treated diabetes before cohort entry (defined as the time between base-cohort entry and cohort entry, ±90 days), and duration of follow-up. Matched controls were assigned the index date of their respective cases.

Exposure Assessment

Cases and matched controls were classified into 1 of 5 mutually exclusive exposure groups at index date, with patients sequentially categorized by (1) current use of incretin-based drugs (DPP-4 inhibitors [linagliptin, sitagliptin phosphate, vildagliptin, and saxagliptin] or GLP-1 agonists [exenatide and liraglutide], alone or in combination with other antidiabetic drugs); (2) current use of insulin (alone or in combination with other nonincretin-based antidiabetic drugs); (3) current use of 2 or more oral antidiabetic drugs; (4) current use of 1 oral antidiabetic drug; and (5) noncurrent use of any antidiabetic drug. Current use was defined by prescription duration, plus a 30-day grace period overlapping the index date. Since incretin-based drugs are considered second- to third-line antidiabetic agents,35 the reference group consisted of current use of at least 2 oral antidiabetic drugs, which is a common second- to third-line treatment strategy.35

Potential Confounders

In addition to age, calendar year of cohort entry, sex, duration of treated diabetes, and duration of follow-up on which the models were conditioned, the following potential baseline confounders were considered: alcohol-related disorders (based on diagnoses for alcohol-related disorders, such as alcoholism, alcoholic cirrhosis of the liver, alcoholic hepatitis, and hepatic failure), history of gallstones, history of cancer (other than nonmelanoma skin cancer), and history of acute or chronic pancreatitis, all measured at any time before cohort entry. The models were also adjusted for prescription drugs previously associated with acute pancreatitis, including use of angiotensin-converting enzyme inhibitors, loop or thiazide diuretics, oral contraceptives and hormone replacement therapy, statins, fibrates, and valproic acid; all were measured in the year before cohort entry. Microvascular complications of diabetes (neuropathy, renal disease, retinopathy, and peripheral arteriopathy) were also adjusted for, as well as the number of different antidiabetic drug classes received in the patient’s history before cohort entry, with both factors as proxies of diabetes severity. In addition, the models were adjusted for 2 general measures of comorbidity: total number of hospitalizations and total number of unique nondiabetic drugs prescribed, with both measured in the year before cohort entry.36 In the CPRD, the models were additionally adjusted for body mass index (<25, 25-29, and ≥30 [calculated as weight in kilograms divided by height in meters squared]; last measure prior to cohort entry), hemoglobin A1c level (≤7.0%, 7.1%-8.0%, and >8.0% [to convert to proportion of total hemoglobin, multiply by 0.01]; last measure before cohort entry), and smoking status (ever or never). These variables were modeled by including a category for missing values, given that information was missing in relatively few patients.

Statistical Analysis

The crude incidence rate of acute pancreatitis was calculated with 95% CIs based on the Poisson distribution. Conditional logistic regression was used to estimate HRs and corresponding 95% CIs of hospitalized acute pancreatitis, comparing current use of incretin-based drugs with current use of 2 or more oral antidiabetic drugs. All models were adjusted for the potential confounders listed above. Statistical analysis was conducted using SAS, version 9.4 (SAS Institute).

Secondary Analyses

We conducted 3 secondary analyses. First, we assessed whether there was a duration-response association between the use of incretin-based drugs and the risk of acute pancreatitis. Thus, patients deemed to be current users of incretin-based drugs in the primary analysis were further categorized according to duration of continuous use (<1.0, 1.0-1.9, and ≥2 years). Continuous drug use was defined as receiving consecutive overlapping prescriptions for incretin-based drugs, allowing for 30-day grace periods in the event of no overlap. Second, individuals with current use of incretin-based drugs were further categorized according to current use of DPP-4 inhibitors and GLP-1 agonists. Finally, we determined whether a history of acute or chronic pancreatitis is an effect modifier of the association between incretin-based drugs and acute pancreatitis. Effect modification was assessed by including an interaction term between the exposure and history of pancreatitis variables.

Sensitivity Analyses

Eight prespecified sensitivity analyses were conducted to assess the robustness of the results. First, given the unknown validity of the acute pancreatitis diagnosis in the different CNODES participating sites, the primary analysis was repeated with restriction to cases with the diagnosis in primary position (ie, most responsible). Second, because there are no clear comparators for incretin-based drugs, the primary analysis was repeated using alternative comparators, consisting of current use of the metformin-sulfonylurea combination therapy and current use of insulin (with or without oral antidiabetic drugs). Third, the primary analysis was repeated by varying the grace period between prescriptions to 0 and 90 days. Fourth, the primary analysis was repeated by additionally adjusting for the antidiabetic drugs used in the year before cohort entry. Fifth, the primary analysis was repeated after excluding patients with a history of insulin use prior to the index date. Sixth, the primary analysis was repeated with the study period restricted to the period before the first alert regarding the potential association between incretin-based drugs and acute pancreatitis (October 2007). The latter analysis was restricted to the participating sites where incretin-based drugs entered their market prior to October 2007.37 Seventh, to account for changes in health status that occurred during follow-up, the primary analysis was repeated with adjustment of covariates at the index date rather than baseline. Eighth, the primary analysis was repeated with a reduced set of covariates to ensure model convergence at all participating sites, with variables included in their continuous form where possible in one reduced model and using the Deyo version of the Charlson comorbidity index in a second reduced model.38 Finally, in a post hoc sensitivity analysis, current use of incretin-based drugs was restricted to patients using these agents in combination with at least 1 other antidiabetic drug.

Meta-analysis

DerSimonian and Laird39 random-effects models were used with inverse variance weighting to pool site-specific estimates. The estimates were also pooled using fixed-effects modeling in sensitivity analyses. Between-site heterogeneity was estimated using the I2 statistic.

Results

A total of 1 532 513 patients met the study inclusion criteria (Figure 1). The mean age at cohort entry was 56.6 years, and 781 567 were male (51.0%) ; additional baseline characteristics of the cohort can be found in eTable 1 and site-specific baseline characteristics are presented in eTables 2-8 in the Supplement. Overall, the cohort was followed for a mean of 2.3 years, generating 3 464 659 person-years of follow-up; site-specific durations of follow-up are reported in eTable 9 in the Supplement. During this time, 5165 patients were hospitalized for acute pancreatitis, generating a crude incidence rate of 1.49 (95% CI, 1.45-1.53) per 1000 person-years. The site-specific incidence rates ranged between 1.09 and 2.00 per 1000 person-years (eTable 10 in the Supplement).

Table 1 presents the baseline characteristics of the 5165 cases and 96 654 matched controls. As expected, cases were more likely to have a history of alcohol-related disorders, gallstones, cancer (other than nonmelanoma skin cancer), and acute or chronic pancreatitis. Compared with controls, cases were also more likely to have used prescription drugs previously associated with acute pancreatitis, including fibrates, angiotensin-converting enzyme inhibitors, loop or thiazide diuretics, and valproic acid.

Overall, compared with current users of 2 or more oral antidiabetic drugs, current users of incretin-based drugs were less likely to be male, but had longer durations of treated diabetes, were more likely to be obese, and were more likely to have a history of gallstones and cancer. Both exposure groups had similar histories of acute or chronic pancreatitis (eTable 11 in the Supplement).

Table 2 presents the results of the primary and secondary analyses. Compared with current use of 2 or more oral antidiabetic drugs, current use of incretin-based drugs was not associated with an increased risk of hospitalization for acute pancreatitis (pooled adjusted HR, 1.03; 95% CI, 0.87-1.22) (Figure 2). Similarly, there was no association in the secondary analysis that categorized the use of incretin-based drugs by class (DPP-4 inhibitors: pooled adjusted HR, 1.09; 95% CI, 0.86-1.22; GLP-1 agonists: pooled adjusted HR, 1.04; 95% CI, 0.81-1.35) or by duration of use (Table 2 and eFigures 1-5 in the Supplement). Finally, there was no evidence of effect modification by history of acute or chronic pancreatitis (no history: pooled adjusted HR, 1.05; 95% CI, 0.86-1.27; history: pooled adjusted HR, 0.70; 95% CI, 0.42-1.17; P = .20 for interaction); (eFigures 6 and 7 in the Supplement).

The results of the sensitivity analyses are summarized in Figure 3; site-specific estimates are presented in eFigures 8-19 in the Supplement. Overall, these analyses yielded findings that were consistent with those of the primary analysis. The HR in the fixed-effects model (pooled adjusted HR, 1.00; 95% CI, 0.87-1.13) was similar to the one generated with the random-effects model for the primary analysis (pooled adjusted HR, 1.03; 95% CI, 0.87-1.22).

Discussion

To our knowledge, this is the largest population-based study to have investigated the association between the use of incretin-based drugs and the risk of acute pancreatitis. With a combined cohort of more than 1.5 million patients with type 2 diabetes, our findings suggest that use of incretin-based drugs is not associated with an overall increased risk of acute pancreatitis compared with use of 2 or more oral antidiabetic drugs. We observed similar results in secondary analyses that assessed the risk with DPP-4 inhibitors and GLP-1 agonists separately and by duration of use. Finally, our findings remained consistent in several sensitivity analyses that considered different potential sources of bias.

To date, several observational studies623 have investigated the association between incretin-based drugs and acute pancreatitis. Overall, most of these studies611,1418,20,21,23 have reported null associations, with the exception of 4 investigations12,13,19,22 in which positive associations were reported. The heterogeneity between these studies is likely the result of several methodologic shortcomings, including the use of inappropriate comparator groups, confounding by indication, time-lag bias,40 prevalent user bias, small sample sizes, and short durations of follow-up.

In addition to the aforementioned observational studies, 4 large RCTs of DPP-4 inhibitors and GLP-1 agonists have been published.4144 In the RCTs of DPP-4 inhibitors, there were imbalances in the number of acute pancreatitis events between the experimental and placebo groups. Specifically, in the SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus–Thrombolysis in Myocardial Infarction 53) trial,41 there were 24 events in the saxagliptin group and 21 in the placebo group; in the EXAMINE (Examination of Cardiovascular Outcomes with Alogliptin vs Standard of Care) trial,42 there were 12 events in the alogliptin benzoate group and 4 in the placebo group; and in the TECOS (Trial Evaluating Cardiovascular Outcomes with Sitagliptin) trial,43 23 events occurred in the sitagliptin group compared with 12 in the placebo group. However, the imbalance was in the other direction in the ELIXA (Evaluation of Lixisenatide in Acute Coronary Syndrome) trial,44 with 5 events documented in the lixisenatide group and 8 events in the placebo group. These RCTs recruited patients with long-standing disease as well as a history of cardiovascular complications, which contrasts with the population using incretin-based drugs in a real-world setting. In our study, patients receiving incretin-based drugs had a relatively short duration of treated diabetes, and relatively few had microvascular complications of diabetes. However, it is unclear whether the apparent differences between our findings and the imbalance observed in these RCTs4144 is a reflection of the populations being evaluated. As such, future studies including patients with longer durations of diabetes will need to be conducted to reassess this association.

The present study has several strengths. First, with a combined cohort of more than 1.5 million patients, our study was well powered to detect modest but clinically important associations. Second, the use of population-based cohorts from 7 participating sites across 3 countries strengthens the generalizability of our findings. Finally, prevalent user bias45 was avoided by requiring patients entering the base and study cohorts to be new users of antidiabetic drugs.

The study also has some limitations. Because of its observational design, residual confounding should be considered. However, we believe that residual confounding was mitigated through 3 different approaches. The first of these involved matching cases and controls on important variables, such as duration of treated diabetes, a proxy for disease severity.46 In the second approach, we adjusted the models for a wide variety of potential confounders, including proxies of diabetes severity (eg, microvascular complications of type 2 diabetes and number of antidiabetic drugs) and variables previously associated with acute pancreatitis. In the third approach, we compared incretin-based drugs with the use of oral antidiabetic drug combinations, the latter representing a second- to third-line treatment approach used at a similar stage of the disease as incretin-based drugs.35 It was not possible to ascertain treatment adherence, possibly resulting in some exposure misclassification. Finally, although none of the sites generated statistically significant results, we observed some heterogeneity in the direction of their point estimates. Specifically, the HRs were above the null in the databases of the CPRD and Canadian sites (with the exception of the Ontario site), whereas the HR was under the null in the US MarketScan database. This heterogeneity may be the result of formulary restrictions in certain jurisdictions, differences in population, and the availability of certain potential confounders (eg, the CPRD was the only site where it was possible to additionally adjust for smoking, body mass index, and hemoglobin A1c). The heterogeneity observed between the different data sets highlights the importance of replication in many databases, which is a key strength of the present study.

Conclusions

The findings of this large, population-based study indicate that the use of incretin-based drugs is not associated with an overall increased risk of acute pancreatitis compared with the use of oral antidiabetic drug combinations. Although it remains possible that these drugs may be associated with acute pancreatitis, the upper limit of our 95% CI suggests that this risk is likely to be small. Thus, the findings of this study should provide some reassurance to patients treated with incretin-based drugs.

Back to top
Article Information

Corresponding Author: Laurent Azoulay PhD, Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, 3755 Côte Sainte-Catherine, H-461, Montreal, QC H3T 1E2, Canada (laurent.azoulay@mcgill.ca).

Accepted for Publication: May 27, 2016.

Published Online: August 1, 2016. doi:10.1001/jamainternmed.2016.1522

The Canadian Network for Observational Drug Effect Studies (CNODES) Investigators include Samy Suissa, PhD; Colin R. Dormuth, ScD; Brenda R. Hemmelgarn, MD, PhD, FRCPC; Gary F. Teare, DVM, PhD; Patricia Caetano, PhD; Dan Chateau, PhD; David A. Henry, MBChB, MRCP, FRCP (Edin); J. Michael Paterson, MSc; Jacques LeLorier, MD, MSc, FRCPC, FISPE; Adrian R. Levy, PhD; Pierre Ernst, MD, MSc, FRCPC; Robert W. Platt, PhD; Ingrid S. Sketris, PharmD, MPA(HSA).

Affiliations of The Canadian Network for Observational Drug Effect Studies (CNODES) Investigators: Center for Clinical Epidemiology, Lady Davis Research Institute, Jewish General Hospital, Montreal, Quebec, Canada (Ernst); Department of Medicine, McGill University, Montreal, Quebec, Canada (Ernst); Departments of Pediatrics and of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada (Platt); The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada (Platt); Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada (Dormuth); Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada (Paterson); Institute of Health Policy, Management and Evaluation, University of Toronto, Ontario, Toronto (Paterson).

Author Contributions: Drs Azoulay and Ernst had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Azoulay, Filion, Platt, Dormuth, Clemens, Durand, Paterson, Targownik, Turin, Ernst, Hemmelgarn, Caetano, Chateau, LeLorier, Levy, Sketris.

Acquisition, analysis, or interpretation of data: Azoulay, Filion, Platt, Dahl, Dormuth, Clemens, Durand, Hu, Juurlink, Paterson, Targownik, Turin, Ernst, Suissa, Hemmelgarn, Teare, Caetano, Chateau, Henry, LeLorier, Levy.

Drafting of the manuscript: Azoulay, Hu, Targownik, Ernst.

Critical revision of the manuscript for important intellectual content: Azoulay, Filion, Platt, Dahl, Dormuth, Clemens, Durand, Juurlink, Paterson, Targownik, Turin, Ernst, Suissa, Hemmelgarn, Teare, Caetano, Chateau, Henry, LeLorier, Levy, Sketris.

Statistical analysis: Azoulay, Filion, Platt, Dahl, Durand, Hu, Targownik, Turin, Hemmelgarn, Chateau.

Obtained funding: Platt, Paterson, Ernst, Suissa, Teare, Caetano, Chateau, Henry, LeLorier, Levy, Sketris.

Administrative, technical, or material support: Dormuth, Clemens, Juurlink, Turin, Ernst, Hemmelgarn, Chateau, LeLorier.

Study supervision: Filion, Platt, Paterson, Turin, Ernst, Caetano, Henry.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure for Potential Conflicts of Interest. Dr Platt received consulting fees for work unrelated to this project from Pfizer, Amgen, Abbvie, and Novartis. Dr Targownik receives financial compensation as a member of the Speaker’s Panel for Janssen Canada, Takeda Canada, Pfizer Canada, and Shire Canada; has received grant support from Pfizer Canada and Abbvie Canada; and receives financial compensation as a member of the advisory boards for Takeda Canada, Abbvie Canada, and Janssen Canada. There were no other disclosures.

Funding/Support: This study was made possible through data-sharing agreements between Canadian Network for Observational Drug Effect Studies (CNODES) member research centers and the respective provincial governments of Alberta, Manitoba (Health Information Privacy Committee: 2014/2015-08; Health Research Ethics Authority: H2014:236), Ontario, and Quebec. The CNODES, a collaborating center of the Drug Safety and Effectiveness Network, is funded by Canadian Institutes of Health Research grant DSE-111845. Dr Azoulay is the recipient of a Chercheur-Boursier Career Award from the Fonds de Recherche du Quebec-Santé (FRQS [Quebec Foundation for Health Research]). Dr Filion holds a Canadian Institutes of Health Research New Investigator Award. Dr Platt holds the Albert Boehringer I. Chair and is supported by a Chercheur-National Career Award of the FRQS. Dr Durand is supported by a clinical investigator award of the FRQS. Dr Juurlink is supported by the Eaton Scholar Program, Department of Medicine, University of Toronto.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: No endorsement by the provinces is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions and statements expressed herein are those of the authors, and not necessarily those of CIHI.

Additional Contributions: We are grateful for the programming support of the following individuals who received financial compensation through the CNODES grant: Zhihai Ma, MSc, and Jianguo Zhang, MSc (University of Calgary); Gregory A. Carney, BSc (University of British Columbia; US MarketScan); Hui Yin, MSc (Lady Davis Institute, Jewish General Hospital; UK CPRD); Caixia Fangyun Wu, MSc, MA, and Simon Hollands, MSc (Institute for Clinical Evaluative Sciences); and Menglan Pang, MSc (Lady Davis Institute, Jewish General Hospital). We also thank Corine Mizrahi, BCom, Melissa Dahan, BA, and Laura Sang, MPH, at the Coordinating Center (Lady Davis Institute, Jewish General Hospital) for their administrative assistance. In addition, we acknowledge Héloïse Cardinal, MD, PhD, for her contribution to the development of the study design. We acknowledge the important contributions of the CNODES collaborators and assistants at each site.

References
1.
Holst  JJ.  The physiology of glucagon-like peptide 1.  Physiol Rev. 2007;87(4):1409-1439.PubMedGoogle ScholarCrossref
2.
Elashoff  M, Matveyenko  AV, Gier  B, Elashoff  R, Butler  PC.  Pancreatitis, pancreatic, and thyroid cancer with glucagon-like peptide-1–based therapies.  Gastroenterology. 2011;141(1):150-156.PubMedGoogle ScholarCrossref
3.
Raschi  E, Piccinni  C, Poluzzi  E, Marchesini  G, De Ponti  F.  The association of pancreatitis with antidiabetic drug use: gaining insight through the FDA pharmacovigilance database.  Acta Diabetol. 2013;50(4):569-577.PubMedGoogle ScholarCrossref
4.
Faillie  JL, Babai  S, Crépin  S,  et al; French Pharmacovigilance Centers Network.  Pancreatitis associated with the use of GLP-1 analogs and DPP-4 inhibitors: a case/non-case study from the French Pharmacovigilance Database.  Acta Diabetol. 2014;51(3):491-497.PubMedGoogle Scholar
5.
Shihab  HM, Akande  T, Armstrong  K, Singh  S, Loke  YK.  Risk of pancreatic adverse events associated with the use of glucagon-like peptide-1 receptor agonist and dipeptidyl peptidase-4 inhibitor drugs: a systematic review and meta-analysis of randomized trials.  World J Meta-Anal. 2015;3:254-283.Google ScholarCrossref
6.
Dore  DD, Seeger  JD, Arnold Chan  K.  Use of a claims-based active drug safety surveillance system to assess the risk of acute pancreatitis with exenatide or sitagliptin compared to metformin or glyburide.  Curr Med Res Opin. 2009;25(4):1019-1027.PubMedGoogle ScholarCrossref
7.
Garg  R, Chen  W, Pendergrass  M.  Acute pancreatitis in type 2 diabetes treated with exenatide or sitagliptin: a retrospective observational pharmacy claims analysis.  Diabetes Care. 2010;33(11):2349-2354.PubMedGoogle ScholarCrossref
8.
Dore  DD, Bloomgren  GL, Wenten  M,  et al.  A cohort study of acute pancreatitis in relation to exenatide use.  Diabetes Obes Metab. 2011;13(6):559-566.PubMedGoogle ScholarCrossref
9.
Romley  JA, Goldman  DP, Solomon  M, McFadden  D, Peters  AL.  Exenatide therapy and the risk of pancreatitis and pancreatic cancer in a privately insured population.  Diabetes Technol Ther. 2012;14(10):904-911.PubMedGoogle ScholarCrossref
10.
Wenten  M, Gaebler  JA, Hussein  M,  et al.  Relative risk of acute pancreatitis in initiators of exenatide twice daily compared with other anti-diabetic medication: a follow-up study.  Diabet Med. 2012;29(11):1412-1418.PubMedGoogle ScholarCrossref
11.
Eurich  DT, Simpson  S, Senthilselvan  A, Asche  CV, Sandhu-Minhas  JK, McAlister  FA.  Comparative safety and effectiveness of sitagliptin in patients with type 2 diabetes: retrospective population based cohort study.  BMJ. 2013;346:f2267.PubMedGoogle ScholarCrossref
12.
Singh  S, Chang  HY, Richards  TM, Weiner  JP, Clark  JM, Segal  JB.  Glucagonlike peptide 1–based therapies and risk of hospitalization for acute pancreatitis in type 2 diabetes mellitus: a population-based matched case-control study.  JAMA Intern Med. 2013;173(7):534-539.PubMedGoogle ScholarCrossref
13.
Dore  DD, Hussein  M, Hoffman  C, Pelletier  EM, Smith  DB, Seeger  JD.  A pooled analysis of exenatide use and risk of acute pancreatitis.  Curr Med Res Opin. 2013;29(12):1577-1586.PubMedGoogle ScholarCrossref
14.
Funch  D, Gydesen  H, Tornøe  K, Major-Pedersen  A, Chan  KA.  A prospective, claims-based assessment of the risk of pancreatitis and pancreatic cancer with liraglutide compared to other antidiabetic drugs.  Diabetes Obes Metab. 2014;16(3):273-275.PubMedGoogle ScholarCrossref
15.
Giorda  CB, Picariello  R, Nada  E,  et al.  Incretin therapies and risk of hospital admission for acute pancreatitis in an unselected population of European patients with type 2 diabetes: a case-control study.  Lancet Diabetes Endocrinol. 2014;2(2):111-115.PubMedGoogle ScholarCrossref
16.
Faillie  JL, Azoulay  L, Patenaude  V, Hillaire-Buys  D, Suissa  S.  Incretin based drugs and risk of acute pancreatitis in patients with type 2 diabetes: cohort study.  BMJ. 2014;348:g2780.PubMedGoogle ScholarCrossref
17.
Chou  HC, Chen  WW, Hsiao  FY.  Acute pancreatitis in patients with type 2 diabetes mellitus treated with dipeptidyl peptidase-4 inhibitors: a population-based nested case-control study.  Drug Saf. 2014;37(7):521-528.PubMedGoogle ScholarCrossref
18.
Liao  KF, Lin  CL, Lai  SW, Chen  WC.  Sitagliptin use and risk of acute pancreatitis in type 2 diabetes mellitus: a population-based case-control study in Taiwan.  Eur J Intern Med. 2016;27:76-79.PubMedGoogle ScholarCrossref
19.
Tseng  CH.  Sitagliptin increases acute pancreatitis risk within 2 years of its initiation: a retrospective cohort analysis of the National Health Insurance database in Taiwan.  Ann Med. 2015;47(7):561-569.PubMedGoogle ScholarCrossref
20.
Clemens  KK, McArthur  E, Fleet  JL, Hramiak  I, Garg  AX.  The risk of pancreatitis with sitagliptin therapy in older adults: a population-based cohort study.  CMAJ Open. 2015;3(2):E172-E181.PubMedGoogle ScholarCrossref
21.
Chang  HY, Hsieh  CF, Singh  S, Tang  W, Chiang  YT, Huang  WF.  Anti-diabetic therapies and the risk of acute pancreatitis: a nationwide retrospective cohort study from Taiwan.  Pharmacoepidemiol Drug Saf. 2015;24(6):567-575.PubMedGoogle ScholarCrossref
22.
Soranna  D, Bosetti  C, Casula  M,  et al.  Incretin-based drugs and risk of acute pancreatitis: a nested-case control study within a healthcare database.  Diabetes Res Clin Pract. 2015;108(2):243-249.PubMedGoogle ScholarCrossref
23.
Thomsen  RW, Pedersen  L, Møller  N, Kahlert  J, Beck-Nielsen  H, Sørensen  HT.  Incretin-based therapy and risk of acute pancreatitis: a nationwide population-based case-control study.  Diabetes Care. 2015;38(6):1089-1098.PubMedGoogle ScholarCrossref
24.
Azoulay  L.  Incretin-based drugs and adverse pancreatic events: almost a decade later and uncertainty remains.  Diabetes Care. 2015;38(6):951-953.PubMedGoogle ScholarCrossref
25.
Egan  AG, Blind  E, Dunder  K,  et al.  Pancreatic safety of incretin-based drugs—FDA and EMA assessment.  N Engl J Med. 2014;370(9):794-797.PubMedGoogle ScholarCrossref
26.
Suissa  S, Henry  D, Caetano  P,  et al; Canadian Network for Observational Drug Effect Studies (CNODES).  CNODES: the Canadian Network for Observational Drug Effect Studies.  Open Med. 2012;6(4):e134-e140.PubMedGoogle Scholar
27.
Azoulay  L, Filion  KB, Platt  RW,  et al; Canadian Network for Observational Drug Effect Studies Investigators.  Incretin based drugs and the risk of pancreatic cancer: international multicentre cohort study.  BMJ. 2016;352:i581.PubMedGoogle ScholarCrossref
28.
Filion  KB, Azoulay  L, Platt  RW,  et al; CNODES Investigators.  A multicenter observational study of incretin-based drugs and heart failure.  N Engl J Med. 2016;374(12):1145-1154.PubMedGoogle ScholarCrossref
29.
Herrett  E, Gallagher  AM, Bhaskaran  K,  et al.  Data Resource Profile: Clinical Practice Research Datalink (CPRD).  Int J Epidemiol. 2015;44(3):827-836.PubMedGoogle ScholarCrossref
30.
Dassopoulos  T, Ehrenpreis  ED.  Acute pancreatitis in human immunodeficiency virus-infected patients: a review.  Am J Med. 1999;107(1):78-84.PubMedGoogle ScholarCrossref
31.
Suissa  S. Novel approaches to pharmacoepidemiology study design and statistical analysis. In: Strom  B, ed.  Pharmacoepidemiology. 4th ed. Chichester, England: John Wiley & Sons; 2005:811-829.
32.
Essebag  V, Platt  RW, Abrahamowicz  M, Pilote  L.  Comparison of nested case-control and survival analysis methodologies for analysis of time-dependent exposure.  BMC Med Res Methodol. 2005;5(1):5.PubMedGoogle ScholarCrossref
33.
Suissa  S.  The quasi-cohort approach in pharmacoepidemiology: upgrading the nested case-control.  Epidemiology. 2015;26(2):242-246.PubMedGoogle ScholarCrossref
34.
Moores  K, Gilchrist  B, Carnahan  R, Abrams  T.  A systematic review of validated methods for identifying pancreatitis using administrative data.  Pharmacoepidemiol Drug Saf. 2012;21(suppl 1):194-202.PubMedGoogle ScholarCrossref
35.
Inzucchi  SE, Bergenstal  RM, Buse  JB,  et al; American Diabetes Association (ADA); European Association for the Study of Diabetes (EASD).  Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).  Diabetes Care. 2012;35(6):1364-1379.PubMedGoogle ScholarCrossref
36.
Schneeweiss  S, Seeger  JD, Maclure  M, Wang  PS, Avorn  J, Glynn  RJ.  Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data.  Am J Epidemiol. 2001;154(9):854-864.PubMedGoogle ScholarCrossref
37.
US Food and Drug Administration. Information for Healthcare Professionals. Exenatide (marketed as Byetta)— 8/2008 Update. http://www.fda.gov/Drugs/DrugSafety/PostmarketDrugSafetyInformationforPatientsandProviders/ucm124713.htm. Published August 18, 2008. Accessed May 23, 2014.
38.
Deyo  RA, Cherkin  DC, Ciol  MA.  Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases.  J Clin Epidemiol. 1992;45(6):613-619.PubMedGoogle ScholarCrossref
39.
DerSimonian  R, Laird  N.  Meta-analysis in clinical trials.  Control Clin Trials. 1986;7(3):177-188.PubMedGoogle ScholarCrossref
40.
Suissa  S, Azoulay  L.  Metformin and the risk of cancer: time-related biases in observational studies.  Diabetes Care. 2012;35(12):2665-2673.PubMedGoogle ScholarCrossref
41.
Scirica  BM, Bhatt  DL, Braunwald  E,  et al; SAVOR-TIMI 53 Steering Committee and Investigators.  Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus.  N Engl J Med. 2013;369(14):1317-1326.PubMedGoogle ScholarCrossref
42.
White  WB, Cannon  CP, Heller  SR,  et al; EXAMINE Investigators.  Alogliptin after acute coronary syndrome in patients with type 2 diabetes.  N Engl J Med. 2013;369(14):1327-1335.PubMedGoogle ScholarCrossref
43.
Green  JB, Bethel  MA, Armstrong  PW,  et al; TECOS Study Group.  Effect of sitagliptin on cardiovascular outcomes in type 2 diabetes.  N Engl J Med. 2015;373(3):232-242.PubMedGoogle ScholarCrossref
44.
Pfeffer  MA, Claggett  B, Diaz  R,  et al; ELIXA Investigators.  Lixisenatide in patients with type 2 diabetes and acute coronary syndrome.  N Engl J Med. 2015;373(23):2247-2257.PubMedGoogle ScholarCrossref
45.
Ray  WA.  Evaluating medication effects outside of clinical trials: new-user designs.  Am J Epidemiol. 2003;158(9):915-920.PubMedGoogle ScholarCrossref
46.
Benoit  SR, Fleming  R, Philis-Tsimikas  A, Ji  M.  Predictors of glycemic control among patients with type 2 diabetes: a longitudinal study.  BMC Public Health. 2005;5:36.PubMedGoogle ScholarCrossref
×