IMPACT OF DRUG EXPOSURE DEFINITIONS ON OBSERVED ASSOCIATIONS IN PHARMACOEPIDEMIOLOGY RESEARCH
Main Article Content
Keywords
Diabetes, Drug Exposure, Metformin, Bias, Pharmacoepidemiology
Abstract
BACKGROUND - A variety of methods used to define exposure in pharmacoepidemiologic studies. Although each method has known biases, the relative effect of these biases on an observed association has not been fully examined.
OBJECTIVE - To explore the influence of different exposure definitions on estimates, using the association between metformin and all-cause mortality as a proto-typical model.
METHODS - New users of oral anti-hyperglycemic drugs were identified using administrative health databases from Alberta, Canada between 1998 and 2010. Drug exposure was described using definitions that are commonly used in observational studies. All analyses included the same covariates of age, gender, and a comorbidity score, and subjects not exposed to metformin served as the reference group. The measure of association was assessed using a Cox Proportional Hazards model for cohort studies and conditional logistic regression for case-control studies.
RESULTS – We identified 64,293 new oral anti-hyperglycemic drugs users; mean age 68.9 years, 33,131 (52%) males, and 24,745 (39%) deaths during a mean follow-up of 6 years. In adjusted models, the association between metformin and mortality ranged from 0.23 (95% CI 0.22-0.25) to 0.92 (95% CI 0.88-0.95) reduction. Most metformin exposure definitions, however, provided estimates in the 0.6-0.8 reduction range, aligning with the results of previous observational studies.
CONCLUSIONS – The variety of exposure definitions tested in this analysis produced a wide range of associations between metformin and mortality risk. Therefore, pharmacoepidemiological studies should include sensitivity analyses using at least two exposure definitions with complementary risks of bias to improve the validity of study results.
References
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31. MacDonald M, Eurich D, Majumdar S, et al. Treatment of type 2 diabetes and outcomes in patients with heart failure: a nested case-control study from the U.K. General Practice Research Database. Diabet Care 2010;33(6):1213–8.
32. Azoulay L, Filion K, Platt R, et al. Association between incretin-based drugs and the risk of acute pancreatitis. JAMA Intern Med 2016;176(10):1464–73.
33. Eurich D, Weir D, Simpson S, Senthilselvan S, McAl ister F. Risk of new-onset heart failure in patients using sitagliptin: a population-based cohort study. Diabet Med 2016;33(5):621–30.
34. Lipscombe L, Gomes T, Lévesque L, Hux J, Juurlink D, Alter D. Thiazolidinediones and cardiovascular outcomes in older patients with diabetes. JAMA 2007;298(22):2634–43.
35. Shih C, Wu Y, Chao P, et al. Association between use of oral anti-diabetic drugs and the risk of sepsis: a nested case-control study. Scientific Reports 2015;5.
36. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43(11):1130–9.
37. Van Walraven C, Austin P, Jennings A, Quan H, Forster A. A modification of the elixhauser comorbidity into a point system for hospital death using administrative data. Med Care 2009;47(6):626–33.
38. Suissa S. Immortal time bias in pharmacoepidemiology. Am J Epidemiol 2008;167(4):492–99.
39. Daniel S, Koren G, Lunenfeld E, Levy A. Immortal time bias in drug safety cohort studies: spontaneous abortion following nonsteroidal antiinflammatory drug exposure Am J Obstet Gynecol 2015;212(3):307.e1–6.
40. Matok I, Azoulay L, Yin H, Suissa S. Immortal time bias in observational studies of drug effects in pregnancy. Birth Defects Res A Clin Mol Teratol 2014;100(9):658–62.
41. Lévesque L, Hanley J, Kezouh A, Suissa S. Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ 2010;340.
42. Suissa S, Azoulay L. Metformin and the risk of cancer time-related biases in observational studies. Diabet Care 2012;36(6):e88.
43. Hill A. The environment and disease: Association or causation? Proc R Soc Med 1965;58:295–300.
44. Royston P, Altman D, Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med 2006;25(1):127–41.
45. Cramer J. A systematic review of adherence with medications for diabetes. Diabet Care. 2004;27(5):1218–24.
46. Krass I, Schieback P, Dhippayom T. Adherence to diabetes medication: a systematic review. Diabet Med 2015;32(6):725–37.
47. Austin P, Anderson G, Cigsar C, Gruneir A. Comparing the cohort design and the nested case–control design in the presence of both time-invariant and time-dependent treatment and competing risks: bias and precision. Pharmacoepidemiol Drug Saf 2012;21(7):714–24.
2. Walker JJ, Johnson JA, Wild SH. Diabetes treatments and cancer risk: the importance of considering aspects of drug exposure. Lancet Diabetes Endocrinol 2013;1(2):132–9.
3. Bannister CA, Holden SE, Jenkins-Jones S, et al. Can people with type 2 diabetes live longer than those without? a comparison of mortality in people initiated with metformin or sulphonylurea monotherapy and matched non-diabetic controls. Diabetes Obes Metab 2014;16(11):1165–73.
4. Gandini S, Puntoni M, Heckman-Stoddard B, et al. Metformin and cancer risk and mortality: A systematic review and meta-analysis taking into account biases and confounders. Cancer Prev Res (Phila) 2014;7(9):867–85.
5. Boussageon R, Supper I, Bejan-Angoulvant T, et al. Reappraisal of metformin efficacy in the treatment of type 2 diabetes: a meta-analysis of randomized controlled trials. PLoS Med 2012;9(4).
6. Tournier M, Bégaud B, Cougnard A, et al. Influence of the drug exposure definition on the assessment of the antipsychotic metabolic impact in patients initially treated with mood-stabilizers. Br J Clin Pharmacol 2012;74(1):189–96.
7. Eurich D, McAlister F, Blackburn D, et al. Benefits and harms of antidiabetic agents in patients with diabetes and heart failure: systematic review. BMJ 2007;335(7618):497.
8. Johnson J, Majumdar S, Simpson S, Toth E. Decreased mortality associated with the use of metformin compared with sulfonylurea monotherapy in type 2 diabetes. Diabetes Care 2002;25(12):2244–8.
9. Group UPDSU. Effect of intensive blood glucose control with metformin on complications in overweight patients with type 2 diabetes Lancet. 1998;352(9131):854–65.
10. Eurich D, Majumdar S, McAlister F, Tsuyuki R, Johnson J. Improved clinical outcomes associated with metformin in patients with diabetes and heart failure. Diabetes Care 2005;28(10):2345–51.
11. Chaiteerakij R, Petersen G, Bamlet W, et al. Metformin use and survival of patients with pancreatic cancer: a cautionary lesson. J Clin Oncol 2016;34(16):1898–904.
12. Tseng C. Metformin and endometrial cancer risk in Chinese women with type 2 diabetes mellitus in Taiwan. Gynecol Oncol 2015;138(1):147–53.
13. Faillie J, Azoulay L, Patenaude V, Hillaire-Buys D, Suissa S. Incretin based drugs and risk of accute pancreatitis in patients with type 2 diabetes: cohort study. BMJ 2014;348(g2780).
14. Lee M, Hsu C, Wahlqvist M, Tsai H, Chang Y, Huang Y. Type 2 diabetes increases and metformin reduces total, colorectal, liver and pancreatic cancer incidences in Taiwanese: a representative population prospective cohort study of 800,000 individuals. BMC Cancer 2011;11(20).
15. Ferrara A, Lewis J, Quesenberry C, et al. Cohort study of pioglitazone and cancer incidence in patients with diabetes. Diabetes Care 2011;34(4):923–9.
16. Mamtani R, Pfanzelter N, Haynes K, et al. Incidence of bladder cancer in patients with type 2 diabetes treated with metformin or sulfonylureas Diabetes Care2014;37(7):1910–7.
17. Ruiter R, Visser L, Van Herk-Sukel M, et al. Lower risk of cancer in patients on metformin in comparison with those on sulfonylurea derivatives. Diabetes Care2012;35(1):119–24.
18. Margel D, Urbach D, Lipscombe L, et al. Metformin use and all-cause and prostate cancer-specific mortality among men with diabetes J Clin Oncol 2013;31(25):3069–75.
19. Nayana M, Macdonaldb E, Juurlink D, et al. Medication use and survival in diabetic patients with kidney cancer: A population-based cohort study. Pharmacol Res 2016;113(Pt A):468–74.
20. Calip G, Yu O, Hoskins K, Boudreau D. Associations between diabetes medication use and risk of second breast cancer events and mortality. Cancer causes control 2015;26(8):1065–77.
21. Eurich D, Simpson S, Senthilselvan A, Asche C, Sandhu-Minhas J, McAlister F. Comparative safety and effectiveness of sitagliptin in patients with type 2 diabetes: retrospective population based cohort study.BMJ 2013;346(f2267).
22. Garg R, Chen W, Pendergrass M. Acute pancreatitis in type 2 diabetes treated with exenatide or sitagliptin.Diabetes Care 2010;33(11):2349–54.
23. Vittinghoff E, Glidden D, Shiboski S, McCulloch C. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. New York, NY: Springer;n2012.
24. Abdelmoneim A, Eurich D, Senthilselvan A, Qiu W, Simpson S. Dose-response relationship between sulfonylureas and major adverse cardiovascular events in elderly patients with type 2 diabetes. Pharmacoepidemiol Drug Saf 2016;25(10):1186–95.
25. Suissa S, Dell’aniello S, Vahey S, Renoux C. Time-window bias in case-control studies: statins and lung cancer. Epidemiology 2011;22:22:228–31.
26. Simpson S, Lin M, Eurich D. Medication adherence affects risk of new diabetes complications: a cohort study. Ann Pharmacother 2016;5(9):741–6.
27. Bowker S, Yasui Y, Veugelers P, Johnson J. Glucose-lowering agents and cancer mortality rates in type 2 diabetes: assessing effects of time-varying exposure. Diabetologia 2010;53(8):1631–37.
28. Azoulay L, Yin H, Filion K, et al. The use of pioglitazone and the risk of bladder cancer in people with type 2 diabetes: nested case-control study. BMJ. 2012;344(e3645).
29. Johnson J, Simpson S, Toth E, Majumdar S. Reduced cardiovascular morbidity and mortality associated with metformin use in subjects with type 2 diabetes. Diabet Med 2005;22(4):497–502.
30. Bensimon L, Yin H, Suissa S, Pollak M, Azoulay L. The use of metformin in patients with prostate cancer and the risk of death. Cancer Epidemiol Biomarkers Prev 2014;23(10):2111–8.
31. MacDonald M, Eurich D, Majumdar S, et al. Treatment of type 2 diabetes and outcomes in patients with heart failure: a nested case-control study from the U.K. General Practice Research Database. Diabet Care 2010;33(6):1213–8.
32. Azoulay L, Filion K, Platt R, et al. Association between incretin-based drugs and the risk of acute pancreatitis. JAMA Intern Med 2016;176(10):1464–73.
33. Eurich D, Weir D, Simpson S, Senthilselvan S, McAl ister F. Risk of new-onset heart failure in patients using sitagliptin: a population-based cohort study. Diabet Med 2016;33(5):621–30.
34. Lipscombe L, Gomes T, Lévesque L, Hux J, Juurlink D, Alter D. Thiazolidinediones and cardiovascular outcomes in older patients with diabetes. JAMA 2007;298(22):2634–43.
35. Shih C, Wu Y, Chao P, et al. Association between use of oral anti-diabetic drugs and the risk of sepsis: a nested case-control study. Scientific Reports 2015;5.
36. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43(11):1130–9.
37. Van Walraven C, Austin P, Jennings A, Quan H, Forster A. A modification of the elixhauser comorbidity into a point system for hospital death using administrative data. Med Care 2009;47(6):626–33.
38. Suissa S. Immortal time bias in pharmacoepidemiology. Am J Epidemiol 2008;167(4):492–99.
39. Daniel S, Koren G, Lunenfeld E, Levy A. Immortal time bias in drug safety cohort studies: spontaneous abortion following nonsteroidal antiinflammatory drug exposure Am J Obstet Gynecol 2015;212(3):307.e1–6.
40. Matok I, Azoulay L, Yin H, Suissa S. Immortal time bias in observational studies of drug effects in pregnancy. Birth Defects Res A Clin Mol Teratol 2014;100(9):658–62.
41. Lévesque L, Hanley J, Kezouh A, Suissa S. Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ 2010;340.
42. Suissa S, Azoulay L. Metformin and the risk of cancer time-related biases in observational studies. Diabet Care 2012;36(6):e88.
43. Hill A. The environment and disease: Association or causation? Proc R Soc Med 1965;58:295–300.
44. Royston P, Altman D, Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med 2006;25(1):127–41.
45. Cramer J. A systematic review of adherence with medications for diabetes. Diabet Care. 2004;27(5):1218–24.
46. Krass I, Schieback P, Dhippayom T. Adherence to diabetes medication: a systematic review. Diabet Med 2015;32(6):725–37.
47. Austin P, Anderson G, Cigsar C, Gruneir A. Comparing the cohort design and the nested case–control design in the presence of both time-invariant and time-dependent treatment and competing risks: bias and precision. Pharmacoepidemiol Drug Saf 2012;21(7):714–24.
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Mar 20, 2018
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Eskin, M., Simpson, S., & Eurich, D. (2018). IMPACT OF DRUG EXPOSURE DEFINITIONS ON OBSERVED ASSOCIATIONS IN PHARMACOEPIDEMIOLOGY RESEARCH. Journal of Population Therapeutics and Clinical Pharmacology, 25(1), e39-e52. https://doi.org/10.22374/1710-6222.25.1.4
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