USE OF CONTINUOUS EXPOSURE VARIABLES WHEN EXAMINING DOSE-DEPENDENT PHARMACOLOGICAL EFFECTS – APPLICATION TO THE ASSOCIATION BETWEEN EXPOSURE TO HIGHER STATIN DOSES AND THE INCIDENCE OF DIABETES

Main Article Content

Jason R Guertin
Elham Rahme
Jacques LeLorier

Keywords

exposure measures, exposure assessment, drug utilization study

Abstract

Background


Many observational studies have found an association between the exposure to statins and the increased risk of diabetes, mostly through the use of intent-to-treat (ITT) like exposure measure (EM). ITT like EM may not adequately reflect the mechanism of action by which statins could cause diabetes.


Objective


To determine if continuous EMs can more accurately reflect the mechanism of action by which statins and incidence of diabetes would be associated than ITT like EM.


Methods


We obtained a cohort of 404,129 diabetes-free incident statin users from the Quebec public drug insurance plan. Patients dispensed with a drug used in the treatment of diabetes or diagnosed with diabetes within 2-years follow-up were defined as cases. Controls were randomly matched to each case on the index date. Three EMs were tested, EM 1: exposure to a high versus low dose statin at baseline (ITT like); EM 2: cumulative standardized statin dose (cSSD) at the index date; and EM 3: cSSD in the 180 days prior to the index date. The optimal EM was selected based upon each model’s Akaike’s information criterion (AIC). Conditional logistic regressions were used to calculate conditional OR and model AIC.


Results


All three EMs identified an increased risk of diabetes among patients exposed to higher statin doses. Model AIC identified EM 3 as the best EM for this association.


Conclusion


Our results indicate that higher statin doses increase the risk of diabetes but favour a cumulative reversible diabetogenic effect of statins.

Abstract 52 | PDF Downloads 29

References

1. Rothman KJ. Induction and latent periods. Am J Epidemiol 1981;114(2):253–9.
2. White E, Hunt JR, Casso D. Exposure measurement in cohort studies: the challenges of prospective data collection. Epidemiol Rev 1998;20(1):43–56.
3. Stampfer MJ. ITT for observational data: worst of both worlds? Epidemiology 2008;19(6):783–4; discussion 9–93.
4. Preiss D, Seshasai SR, Welsh P, et al. Risk of incident diabetes with intensive-dose compared with moderate-dose statin therapy: a meta-analysis. JAMA 2011;305(24):2556–64.
5. Dormuth CR, Filion KB, Paterson JM, et al. Higher potency statins and the risk of new diabetes: multicentre, observational study of administrative databases. BMJ 2014;348(May29 6):g3244–g.
6. Carter AA, Gomes T, Camacho X, et al. Risk of incident diabetes among patients treated with statins: population based study. BMJ 2013;346(May23 4):f2610.
7. Zaharan NL, Williams D, Bennett K. Statins and risk of treated incident diabetes in a primary care population. Br J Clin Pharmacol 2013;75(4):1118–24.
8. Wang KL, Liu CJ, Chao TF, et al. Statins, risk of diabetes, and implications on outcomes in the general population. J Am Coll Cardiol 2012;60(14):1231–8.
9. Ko DT, Wijeysundera HC, Jackevicius CA, et al. Diabetes and cardiovascular events in older myocardial infarction patients prescribed intensive-dose and moderate-dose statins. Circ Cardiovasc Qual Outcomes 2013;6:315–22.
10. Waters DD, Ho JE, DeMicco DA, et al. Predictors of new-onset diabetes in patients treated with atorvastatin: results from 3 large randomized clinical trials. J Am Coll Cardiol 2011;57(14):1535–45.
11. Sattar N, McConnachie A, Shaper AG, et al. Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Outcome data from two prospective studies. Lancet 2008;371(9628):1927–35.
12. Mancia G, Bombelli M, Facchetti R, et al. Long-term risk of diabetes, hypertension and left ventricular hypertrophy associated with the metabolic syndrome in a general population. J Hypertens 2008;26(8):1602–11.
13. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovas - cular disease and type 2 diabetes mellitus. Circulation 2005;112(20):3066–72.
14. Rothman KJ, Greenland S. Causation and causal inference in epidemiology. Am J Public Health 2005;95 Suppl 1:S144–50.
15. Jackevicius CA, Mamdani M, Tu JV. Adherence with statin therapy in elderly patients with and without acute coronary syndromes. JAMA 2002;288(4):462–7.
16. Dormuth CR, Patrick AR, Shrank WH, et al. Statin adherence and risk of accidents: a cautionary tale. Circulation 2009;119(15):2051–7.
17. Benner JS, Glynn RJ, Mogun H, Neumann PJ, Weinstein MC, Avorn J. Long-term persistence in use of statin therapy in elderly patients. JAMA 2002;288(4):455–61.
18. Avorn J, Monette J, Lacour A, et al. Persistence of use of lipid-lowering medications: a cross-national study. JAMA 1998;279(18):1458–62.
19. Navarese EP, Szczesniak A, Kolodziejczak M, et al. Statins and risk of new-onset diabetes mellitus: is there a rationale for individualized statin therapy? Am J Cardiovasc Drugs 2013;14(2):79–87.
20. Ray K. Statin diabetogenicity: guidance for clinicians. Cardiovasc Diabetol 2013;12(Suppl 1):S3.
21. Sattar N, Taskinen, M-J. Statins are diabetogenic - Myth or reality? Artheroscler Suppl 2012;13:1–10.
22. Simpson WG. Statins and risk of incident diabetes. Lancet 2010;375(9732):2140; author reply 1–2.
23. Government of Quebec. Population of Québec 2013. Available at: http://www.stat.gouv.qc.ca/donstat/societe/ demographie/struc_poplt/qc_1971-20xx.htm.
24. Blais C, Lambert L, Hamel D, et al. Évaluation des soins et surveillance des maladies cardiovasculaires: Pouvons-nous faire confiance aux données médico- administratives hospitalières ? Montreal: Institut national d’excellence en santé et en services sociaux (INESSS), 2012.
25. Lambert L, Blais C, Hamel D, et al. Evaluation of care and surveillance of cardiovascular disease: can we trust medico-administrative hospital data? Can J Cardiol 2012;28(2):162–8.
26. Tamblyn R, Lavoie G, Petrella L, Monette J. The use of prescription claims databases in pharmacoepidemiological research: the accuracy and comprehensiveness of the prescription claims database in Quebec. J Clin Epidemiol 1995;48(8):999–1009.
27. Tamblyn R, Reid T, Mayo N, McLeod P, Churchill-Smith M. Using medical services claims to assess injuries in the elderly: sensitivity of diagnostic and procedure codes for injury ascertainment. J Clin Epidemiol 2000;53(2):183–94.
28. World Health Organization. WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD Index. Available at: http://www.whocc.no/atc_ddd_index/.
29. 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 Method 2005;5(1):5.
30. Kheterpal S, Tremper KK, Englesbe MJ, et al. Predictors of postoperative acute renal failure after noncardiac surgery in patients with previously normal renal function. Anesthesiology 2007;107(6):892–902.
31. Molnar AO, Coca SG, Devereaux PJ, et al. Statin use associates with a lower incidence of acute kidney injury after major elective surgery. J Am Soc Nephrol: JASN 2011;22(5):939–46.
32. Ouattara A, Benhaoua H, Le Manach Y, et al. Perioperative statin therapy is associated with a significant and dose-dependent reduction of adverse cardiovascular outcomes after coronary artery bypass graft surgery. J Cardiothorac Vasc Anesth 2009;23(5):633–8.
33. Akaike H. A new look at the statistical model identification. IEEE Transact Automat Control 1974;AC–19(6):716–23.
34. Abrahamowicz M, Beauchamp ME, Sylvestre MP. Comparison of alternative models for linking drug exposure with adverse effects. Statist Med 2012;31(11–12):1014–30.
35. Leffondre K, Abrahamowicz M, Siemiatycki J, Rachet B. Modeling smoking history: a comparison of different approaches. Am J Epidemiol 2002;156(9):813–23.
36. Quantin C, Abrahamowicz M, Moreau T, et al. Variation over time of the effects of prognostic factors in a population-based study of colon cancer: comparison of statistical models. Am J Epidemiol 1999;150(11):1188–200.
37. Sampson UK, Linton MF, Fazio S. Are statins diabetogenic? Curr Opin Cardiol 2011;26(4):342–7.
38. Nakata M, Nagasaka S, Kusaka I, et al. Effects of statins on the adipocyte maturation and expression of glucose transporter 4 (SLC2A4): implications in glycaemic control. Diabetologia 2006;49(8):1881–92.
39. Yada T, Nakata M, Shiraishi T, Kabei M. nhibition by simvastatin, but not pravastatin, of glucose-induced cytosolic Ca2+ signalling and insulin secretion due to blockade of L-type Ca2+ channels in rat islet β -cells. Br J Pharmacol 1999;126(5):1205–13.
40. Harris MI, Klein R, Welborn TA, Knuiman MW. Onset of NIDDM occurs at least 4-7 yr before clinical diagnosis. Diabet Care 1992;15(7):815–9.
41. Canadian Diabetes Association Clinical Practice Guidelines Expert Comittee, Goldenberg R, Punthakee Z. Definition, classification and diagnosis of diabetes, prediabetes and metabolic syndrome. Can J Diabetes 2013;37 Suppl 1:S8–11.