REVIEW OF THE QUALITY OF OBSERVATIONAL STUDIES OF THE ASSOCIATION BETWEEN ROSIGLITAZONE AND ACUTE MYOCARDIAL INFARCTION
Main Article Content
Keywords
Pharmacoepidemiology research, administrative data, confounding by indication, rosiglitazone, acute myocardial infarction
Abstract
Background
Following the publication of a meta-analysis reporting a risk of acute myocardial infarction (AMI) with rosiglitazone that led to severe restrictions being placed on its use, several observational studies of the association were reported. The lifting of restrictions in the United States in 2013 makes a review of these studies pertinent.
Objective
To evaluate the quality of population-based observational studies of the rosiglitazone - AMI association.
Methods
PubMed and Embase literature databases were searched for observational studies evaluating the association that were published between 2006 and 2010. Publications satisfying the inclusion criteria were reviewed using the Checklist for Retrospective Database Studies.
Results
Nineteen studies satisfied the inclusion criteria. Reasons for the research design and data source were absent or unclear in 18 (95%) and 16 (84%), respectively. Administrative data were used exclusively in 14 (74%). Baseline periods for prior diagnoses and medications varied widely. Reimbursement constraints on rosiglitazone use were reported in only seven studies (37%), although all were likely to have been impacted by them. What was being tested in half of the rosiglitazone treatment comparisons lacked specificity and clarity. All relied on risk ratios and, for 90% of the comparisons, the ratios were between 0.5 and two – a level at which residual confounding can lead to spurious significance.
Conclusion
Important deficiencies existed in the rosiglitazone studies suggesting that standards for methods and reporting of observational safety analyses need improvement. In particular, detailed clinical data should be included when the risk of confounding by indication is likely to be high.
References
1. Delea TE, Edelsberg JS, Hagiwara M, Oster G, Phillips LS . Use of thiazolidinediones and risk of heart failure in people with type 2 diabetes: a retrospective cohort study. Diabetes Care 2003;26: 2983 - 9.
2. Masoudi FA, Inzucchi SE, Wang Y, et al. Th iazolidinediones, metformin, and outcomes in older patients with diabetes and heart failure: an observational study. Circulation 2005;111: 583 - 90.
3. Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovasc ular causes. N Engl J Med 2007;356: 2457 - 71.
4. Bracken MB. Rosiglitazone and cardiovascular risk [Lett] . N Engl J Med 2007; 357:937 - 8.
5. Mannucci E, Monami M, Marchionni N. Rosiglitazone and cardiovascular risk [Lett] . N Engl J Med 2007;357: 938.
6. Diamond GA, Kaul S. Rosiglitazone and cardiovascular risk [Lett] . N Engl J Med 2007;357: 938 - 9.
7. Diamond GA, Bax L, Kaul S. Uncertain effects of rosiglitazone on the risk for myocardial infarction and cardiovascular death. Ann Intern Med 2007;147: 578 - 81.
8. Shuster JJ, Jones L S, Salmon DA. Fixed v random effects in meta - analysis in rare event studies: the rosiglitazone link with myocardial infarction and cardiac death. Stat Med 2007;26: 4375 - 85.
9. Kaul S, Diamond GA. Rosiglitazone and cardiovascular risk. Curr Atheroscler Rep 2008 ;10: 398 - 404.
10. Friedrich JO, Beyene J, Adhikari NKJ. Rosiglitazone: can meta - analysis accurately estimate excess cardiovascular risk given the available data? Re - analysis of randomized trials using various methodologic approaches. BMC Res Notes 2009;2: 5.
11. Sui ssa S, Henry D, Caetano P, et al. CNODES: the Canadian Network for Observational Drug Effect Studies. Open Med 2012;6: e134.
12. FDA’s Sentinel Initiative. Silver Spring, MD: US Fo od and Drug Administration, 2014 . http://www.fda.gov/Safety/FDAsSentinelInitiati ve/default.htm (accessed: May 1, 2014 ).
13. European Network of Centres for Pharmacovigilance and Pharmacoepidemiology. London: Europ ean Me dicines Agency, 2014 . http://www.encepp.eu/ (accessed : May 1, 2014 ).
14. Schneeweiss S. Developments in post - marketing comparative effectiveness research. Clin Pharmacol Ther 2007;82: 143 - 56.
15. Schneeweiss S. Confounding. In: Hartzema AG, Tilson HH, Chan KA, eds. Pharmacoepidemiology and Therapeutic Risk Management. Cincin nati, OH: Harvey Whitney, 2008: 273 - 99.
16. Joffe MM. Confounding by indication: the case of calcium channel blockers. Pharmacoepidemiol Drug Saf 2000; 9 : 37 - 41.
17. Da le AC, Midthjell K, Nilsen TI, Wiseth R, Vatten LJ. Glycaemic control in newly diagnosed diabetes patients and mortality from ischaemic heart disease: 20 - year follow - up of the HUNT Study in Norway. Eur Heart J 2009;30: 1372 - 7.
18. FDA requires removal of certain restrictions on the diabetes drug Avandia. Silver Spring, MD: US Food and Drug Administration, 2013. http://www.fda.gov/NewsEvents/Newsroom/Pre ssAnnouncements/ucm3765 16.htm (accessed: May 1, 2014 ).
19. Strom BL. Methodologic challenges to studying patient safety and comparative effectiveness. Med Care 2007;45 (suppl 2): S13 - 5.
20. Pocock SJ, Collier TJ, Dandreo KJ, et al. Issues in the reporting of epidemiological studies: a surve y of recent practice. BMJ 2004;329: 883.
21. Von Elm E, Altman DG, Egger M, et al. The Strengthening The Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiology 2007;18: 800 - 4.
22. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening The Reporting of Observational Studies in Epide miology (STROBE): explanation and elaboration. Epidemiology 2007;18: 805 - 35.
23. Motheral B, Brooks J, Clark MA, et al. A checklist for retrospective database studies – report of the ISPOR Task Force on Retrospective Databases. Value Health 2003;6: 90 - 7.
24. GRACE p rinciples: good research for comparative effectiveness. Cambridge, MA: GRACE Initiative, 2010. https://www.pharmacoepi.org/pub/1c29f69f - 2354 - d714 - 5100 - 1ef2b0e9abd9 (access ed : May 1, 2014 ).
25. Dreyer NA, Schneeweiss S, McNeil BJ, et al. GRACE principles: recognizing high - quality observational studies of comparative effectiveness. Am J Manag Care 2010;16: 467 - 71.
26. McAfee AT, Koro C, Landon J, Ziyadeh N, Walker AM . Coronary heart disease outcomes in patients receiving antidiabetic agents. Pharmacoepidemiol Drug Saf 2007;16: 711 - 25.
27. Gerrits CM, Bhattacharya M, Manthena S, Baran R, Perez A, Kupfer S. A comparison of pioglitazone and rosiglitazone for hospitalization f or acute myocardial infarction in type 2 diabetes. Pharmacoepidemiol Drug Saf 2007;16: 1065 - 71.
28. Lipscombe LL, Gomes T, Lévesque LE, Hux JE, Juurlink DN, Alter DA. Thiazolidinediones and cardiovascular outcomes in older patients with diabetes. JAMA 2007;298: 2634 - 43.
29. Margolis DJ, Hoffstad O, Strom BL. Association between serious ischemic cardiac outcomes and medications used to treat diabetes. Pharmacoepidemiol Drug Saf 2008;17: 753 - 9.
30. Walker AM, Koro CE, Landon J. Coronary heart disease outcomes in patients re ceiving antidiabetic agents in the PharMetrics database 2000 - 2007. Pharmacoepidemiol Drug Saf 2008;17: 760 - 8.
31. Koro CE, Fu Q, Stender M. An assessment of the effect of thiazolidinedione exposure on the risk of myocardial infarction in type 2 diabetic patient s. Pharmacoepidemiol Drug Saf 2008;17: 989 - 96.
32. Winkelmayer WC, Setoguchi S, Levin R, Solomon DH. Comparison of cardiovascular outcomes in elderly patients with diabetes who initiated rosiglitazone vs pioglitazone therapy. Arch Intern Med 2008;168: 2368 - 75.
33. S tockl KM, Le L, Zhang S, Harada ASM. Risk of acute myocardial infarction in patients treated with thiazolidinediones or other antidiabetic medications. Pharmacoepidemiol Drug Saf 2009;18: 166 - 74.
34. Vanasse A, Carpentier AC, Courteau J, Asghari S. Stroke and c ardiovascular morbidity and mortality associated with rosiglitazone use in elderly diabetic patients. Diab Vasc Dis Res 200 9;6: 87 - 93.
35. Dormuth CR, Maclure M, Carney G, Schneeweiss S, Bassett K, Wright JM. Rosiglitazone and myocardial infarction in patients previously prescribed metformin. PLoS One 2009; 4: e6080.
36. Habib ZA, Tzogias L, Havstad SL, et al. Relationship between thiazolidinedione use and cardiovascular outcomes and all - cause mortality among patients with diabetes: a time - updated propensity analysis . Pharmacoepidemiol Drug Saf 2009;18: 437 - 47.
37. Dore DD, Trivedi AN, Mor V, Lapane KL. Association between extent of thiazolidinedione exposure and risk of acute myocardial infarction. Pharmacotherapy 2009;29: 775 - 83.
38. Hsiao FY, Huang WF, Wen YW, Chen PF, Kuo K N, Tsai YW. Thiazolidinediones and cardiovascular events in patients with type 2 diabetes mellitus: a retrospective cohort study of over 473,000 patients using a National Health Insurance database in Taiwan. Drug Saf 2009;32: 675 - 90.
39. Juurlink DN, Gomes T, L ipscombe LL, Austin PC, Hux JE, Mamdani MM. Adverse cardiovascular events during treatment with pioglitazone and rosiglitazone: population based cohort study. BMJ 2009;339: b2942.
40. Ziyadeh N, McAfee AT, Koro C, Landon J, Chan KA. The thiazolidinediones rosig litazone and pioglitazone and the risk of coronary heart disease: a retrospective cohort study using a US health insurance database. Clin Ther 2009;31: 2665 - 77.
41. Tzoulaki I, Molokhia M, Curcin V, et al. Risk of cardiovascular disease and all cause mortality among patients with type 2 diabetes prescribed oral antidiabetes drugs: retrospective cohort study using UK general practice research database. BMJ 2009; 339:b4731.
42. Brownstein JS, Murphy SN, Goldfine AB, et al. Rapid identification of myocardial infarction risk associated with diabetic medications using electronic medical records. Diabetes Care 2010;33: 526 - 31.
43. Graham DJ, Ouellet - Hellstrom R, MaCurdy TE, et al. Risk of acute myocardial infarction, stroke, heart failure, and death in elderly Medicare patients treated with rosiglitazone or pioglitazone. JAMA 2010;304: 411 - 8.
44. Loebstein R, Dushinat M, Vesterman - Landes J, et al. Database evaluation of the effects of long - term rosiglitazone treatment on cardiovascular outcomes in patients with type 2 diabetes. J Cli n Pharmacol 2011;51: 173 - 80.
45. Walker AM, McAfee AT, Koro C. Studies of diabetes, thiazolidinediones, and coronary heart disease. Pharmacoepidemiol Drug Saf 2007;16: 1313 - 4.
46. International Society for Pharmacoepidemiology. Guidelines for good pharmacoepidemiology practices (GPP). Pharmacoepidemiol Drug Saf 2008;17: 200 - 8.
47. Rawson NSB, Downey W, Maxwell CJ, West R. 25 years of pharmacoepidemiologic innovation: the Saskatchewan Health administrative databases. J Popu l Ther Clin Pharmacol 2011;18: e245 - 9.
48. Strom BL. How the US drug safety system should be changed. JAMA 2006; 29 5: 2072 - 5.
49. Hall GC, Sauer B, Bourke A, Brown JS, Reynolds MW, LoCasale R. Guidelines for good database selection and use in pharmacoepidemiology research. Pharm acoepidemiol Drug Saf 2012;21: 1 - 10.
50. Paters on JM, Suleiman A, Hux JE, Bell C . How complete are drug history profiles that are based on public drug benefit claims? Can J Clin Pharmacol 2008;15: e108 - 16.
51. Alshammari AM, Hux JE. The impact of non - fee - for - service reimbursement on chronic disease surveillance using administrative data. Can J Public Health 2009;100: 472 - 4.
52. Rawson NSB, D’Arcy C. “Validity” and reliability: idealism and reality in the use of computerized health car e databases for pharmacoepidemiological research. Post Market Surveill 1991;5 : 31 - 55.
53. Jollis JG, Ancukiewicz M, DeLong ER, et al. Discordance of databases designed for claims payment versus clinical information systems: implications for outcomes research. A nn Intern Med 1993;119: 844 - 50.
54. Newton KM, Wagner EH, Ramsey SD, et al. The use of automated data to identify complications and comorbidities of diabetes: a validation study. J Clin Epidemiol 1999;52: 199 - 207.
55. Austin PC, Daly PA, Tu JV. A multicenter study o f the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care uni ts in Ontario. Am Heart J 2002;144: 290 - 6.
56. Lanes SF, de Luise C. Bias due to false - positive diagnoses in an automated health insurance claims database. Drug Saf 2006;29: 1069 - 75.
57. Rawson NSB, Shatin D. Assessing the validity of diagnostic data in large administrative health care utilization databases. In: Hartzema AG, Tilson HH, Chan KA, eds. Pharmacoepidemiology and Therapeutic Risk Management. Cincin nati, OH: Harvey Whitney, 2008: 495 - 517.
58. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005;58: 323 - 37.
59. Terris DD, Litaker DG, Koroukian SM. Health state information deri ved from secondary databases is affected by multiple sources of bias. J Clin Epidemiol 2007;60: 734 - 41.
60. Crystal S, Akincigil A, Bilder S, Walkup JT . Studying prescription drug use and outcomes with Medicaid claims data. Med Care 2007;45(suppl 2): S58 - 65.
61. Raw son NSB. Access to linked administrative healthcare utilization data for pharmacoepidemiology and pharmacoeconomics research in Canada: anti - viral drugs as an example. P harmacoepidemiol Drug Saf 2009;18: 1072 - 9.
62. V an Walraven C, Austin P. Administrative data base research has unique characteristics that can risk biased results. J Clin Epidemiol 2012;65:126 - 31.
63. Hennessy S, Bilker WB, Weber A, et al. Descriptive analyses of the integrity of a US Medicaid claims database. Pharmacoepidemiol Drug Saf 2003;12: 103 - 11.
64. Hennessy S, Carson JL, Ray WA, et al. Medicaid databases. In: Strom BL, ed. Pharmacoepidemiology. 4th ed. Ch ichester, England: Wiley, 2005: 281 - 94.
65. Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the Genera l Practice Research Database: a systematic review. Br J Pharmacol 2010;69: 4 - 14.
66. Van Walraven C, Bennett C, Forster AJ. Administrative database research infrequently used validated diagnostic or procedural codes. J Clin Epidemiol 2011;64: 1054 - 9.
67. Saunders KW , Davis RL, Stergachis A. Group Health Cooperative. In: Strom BL, ed. Pharmacoepidemiology. 4th ed. Ch ichester, England: Wiley, 2005: 223 - 39.
68. Psaty BM, Boineau R, Kuller LH, Leupker RV. The potential costs of upcoding for heart failure in the United States. Am J Cardiol 1999;84: 108 - 9.
69. Croghan TW, Esposito D, Daniel G, Wahl P, Stoto MA. Using medical records to supplement a claims - based comparative effectiveness analysis of antidepressants. Pharmacoepidemiol Drug Saf 2010;19: 814 - 8.
70. Best practices for conducti ng and reporting pharmacoepidemiologic safety studies using electronic healthcare data sets: draft guidance for industry and FDA staff. Rockville, MD: Food and Drug Administration, May 2013. http://www.fda.gov/downloads/Drugs/Guidance ComplianceRegulatoryInformation/Guidances/U CM243537.pdf (accessed : May 1, 2014 ).
71. Levine M, Gaebel K. Impact of formulary policy on thiazolidinedione (TZD) use in t he Ontario Drug Benefit (ODB) program [Abst] . Clin Pharmacol Ther 2005;77: P72.
72. Abushomar H, Gaebel K, Levine M. Evaluation of patient access to diabetic medications [Abst] . Can J Clin Pharmacol 2005;12: e76.
73. Dorais M, LeLorier J. Impact of the socioeconomic status on the probability of receiving formulary restricted thiazolidinediones (TZDs). Can J Clin Pharmacol 2008; 15: e15 - 21.
74. Hanley G. Prescription drug insurance and unmet need for health care: a cross - sectio nal analysis. O pen Med 2009;3: 178 - 83.
75. Ray WA. Evaluating medication effects outside of clinical trials: new - use r designs. Am J Epidemiol 2003;158: 915 - 20.
76. Starner CI, Schafer JA, Heaton AH, Gleason PP. Rosiglitazone and pioglitazone utilization from January 2007 through M ay 2008 associated with five risk - warning events. J Manag Care Pharm 2008;14: 523 - 31.
77. Shatin D, Rawson NSB, Stergachis A. UnitedHealth Group. In: Strom BL, ed. Pharmacoepidemiology. 4th ed. Chichester: Wiley, 2005: 271 - 80 .
78. Skinner BJ. Waiting for reimburseme nt of new medicines in Canada: it’s time for a rethink. Pharmacoeconomics 2008;26: 629 - 32.
79. LeLorier J, Bell A, Bougher DJ, Cox JL, Turpie AGG. Drug reimbursement policies in Canada: need for improved access to critical therapies. Ann Pharmacother 2008;42: 869 - 73.
80. Groenwold RHH, Hak E, Hoes AW. Quantitative assessment of unobserved confounding is mandatory in nonrandomized intervention studies. J Clin Epidemiol 2009;62: 22 - 8.
81. Johnson ML, Crown W, Martin BC, Dormuth CR, Siebert U. Good research practices for c omparative effectiveness research: analytic methods to improve causal inference from nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report – part III . Value Health 2009; 12:1062 - 73.
82. Jackson ML, Nelson JC, Jackson LA. Why do covariates defined by International Classification of Diseases codes fail to remove confounding in pharmacoepidemiologic studies among seniors? Pharmacoepidemiol Drug Saf 2011;20: 858 - 65.
83. Brookhart MA, Stürmer T, Glynn RJ, Rassen J, Schneeweiss S. Confounding control in healthcare database research: challenges and poten tial approaches. Med Care 2010;48(suppl): S114 - 20.
84. Schneeweiss S. Sensitivity analysis and external adjustment for unme asured confounders in epidemiologic database studies of therapeutics. Pharmacoepidemiol Drug Saf 2006;15:291 - 303.
85. Klungel OH, Martens EP, Psaty B, et al. Methods to assess intended effects of drug treatment in observational studies are reviewed. J Clin Epi demiol 2004;57: 1 223 - 31.
86. Cox E, Martin BC, Van Staa T, Garbe E, Siebert U, Johnson ML. Good research practices for comparative effectiveness research: approaches to mitigating bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report – part II. Value Health 2009;12:1053 - 61.
87. European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (EnCEPP). Guide on met hodological standards in pharmacoepidemiology (revision 2 ). London: Euro pean Medicines Agency, June 2013 . http://www.encepp.eu/standards_and_guid ances/documents/ENCePPGuideMethStandards PE_Rev2.pdf (accessed : May 1, 2014 ).
88. McMahon AD. Approaches to combat with confounding by indication in observational studies of intended drug effects. Pharmacoepidemiol Drug Sa f 2003;12: 551 - 8.
89. Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology 2000;11:550 - 60.
90. Bosco JLF, Silliman RA, Thwin SS, et al. A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies. J Clin Epidemiol 2010; 63: 64 - 74.
91. Thamer M, Hernán MA, Zhang Y, Cotter D, Petri M. Prednisone, lupus activity, and permanent organ damage. J Rheumatol 2009; 36: 560 - 4.
92. Schaubel D, Hanley J, Collet JP, et al. Two - stage sa mpling for etiologic studies: sample size and power. Am J Epidemiol 1997;146: 450 - 8.
93. Stürmer T, Glynn RJ, Rothman KJ, Avorn J. Adjustments for unmeasured confounders in pharmacoepidemiologic database studies using external information. Med Care 2007; 45(supp l 2) : S158 - 65.
94. Faries DE, Leon AC, Haro JM, Obenchain RL, eds. Analysis of Observational Health Care Data using SAS ® . Cary, NC: SAS Institute, 2010.
95. Berger ML, Mamdani M, Atkins D, Johnson ML. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report – part I. Value Health 2009;12: 1044 - 52.
96. Shapiro S. Explaining risk: a guide for health professionals. Maturitas 2009; 64: 143 - 4.
97. Shapiro S. Bias in the evaluation of low - magnitude associations: an empirical perspective. Am J Epidemiol 2000; 151: 939 - 45.
98. Shapiro S. Causation, bias and confounding: a hitchhiker’s guide to the epidemiological galaxy, part 2. Principles of causality in epidemiological research: confounding, effect modification and strength of association. J Fam Plann Reprod Health Care 2008;34:185 - 90.
99. Stewart KA, Natzke BM, Williams T, Granger E, Casscells SW, Croghan TW. Temporal trends in anti - diabetes drug use in tricare following safety warnings in 2007 about rosiglitazone. Pharmacoepidemiol Drug Saf 2009;18:1048 - 52.
100. Cohen A, Rabbani A, Shah A, Alexander GC. Changes in glitazone use among office - based physicians in the US, 2003 - 2009. Diabetes Care 2010;33: 823 - 5.
101. Rawson NSB, Ross Terres JA. Rosiglitazone use and associated adverse event rates in Canada between 2004 and 2010. BMC Res Notes 2013;6: 82.
102. Fanning EL, Weissma n PN, Menditto LA. Clinical practice effect of rosiglitazone discontinuation on glycemic control. Endocr Pract 2009;15: 270 - 2.
103. Aspinall SL, Zhao X, Good CB, Stone RA, Smith KJ, Cunningham FE. FDA warning and removal of rosiglitazone from VA national f ormula ry. Am J Manag Care 2013;19: 748 - 58.
104. Kung J, Henry RR. Thiazolidinedione safety. Expert Opin Drug Saf 2012; 11: 565 - 79.
105. Hiatt WR, Kaul S, Smith RJ. The cardiovascular safety of diabetes drugs – insights from the rosiglitazone experience. N Engl J Med 2013 ;369:1285 - 7.
2. Masoudi FA, Inzucchi SE, Wang Y, et al. Th iazolidinediones, metformin, and outcomes in older patients with diabetes and heart failure: an observational study. Circulation 2005;111: 583 - 90.
3. Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovasc ular causes. N Engl J Med 2007;356: 2457 - 71.
4. Bracken MB. Rosiglitazone and cardiovascular risk [Lett] . N Engl J Med 2007; 357:937 - 8.
5. Mannucci E, Monami M, Marchionni N. Rosiglitazone and cardiovascular risk [Lett] . N Engl J Med 2007;357: 938.
6. Diamond GA, Kaul S. Rosiglitazone and cardiovascular risk [Lett] . N Engl J Med 2007;357: 938 - 9.
7. Diamond GA, Bax L, Kaul S. Uncertain effects of rosiglitazone on the risk for myocardial infarction and cardiovascular death. Ann Intern Med 2007;147: 578 - 81.
8. Shuster JJ, Jones L S, Salmon DA. Fixed v random effects in meta - analysis in rare event studies: the rosiglitazone link with myocardial infarction and cardiac death. Stat Med 2007;26: 4375 - 85.
9. Kaul S, Diamond GA. Rosiglitazone and cardiovascular risk. Curr Atheroscler Rep 2008 ;10: 398 - 404.
10. Friedrich JO, Beyene J, Adhikari NKJ. Rosiglitazone: can meta - analysis accurately estimate excess cardiovascular risk given the available data? Re - analysis of randomized trials using various methodologic approaches. BMC Res Notes 2009;2: 5.
11. Sui ssa S, Henry D, Caetano P, et al. CNODES: the Canadian Network for Observational Drug Effect Studies. Open Med 2012;6: e134.
12. FDA’s Sentinel Initiative. Silver Spring, MD: US Fo od and Drug Administration, 2014 . http://www.fda.gov/Safety/FDAsSentinelInitiati ve/default.htm (accessed: May 1, 2014 ).
13. European Network of Centres for Pharmacovigilance and Pharmacoepidemiology. London: Europ ean Me dicines Agency, 2014 . http://www.encepp.eu/ (accessed : May 1, 2014 ).
14. Schneeweiss S. Developments in post - marketing comparative effectiveness research. Clin Pharmacol Ther 2007;82: 143 - 56.
15. Schneeweiss S. Confounding. In: Hartzema AG, Tilson HH, Chan KA, eds. Pharmacoepidemiology and Therapeutic Risk Management. Cincin nati, OH: Harvey Whitney, 2008: 273 - 99.
16. Joffe MM. Confounding by indication: the case of calcium channel blockers. Pharmacoepidemiol Drug Saf 2000; 9 : 37 - 41.
17. Da le AC, Midthjell K, Nilsen TI, Wiseth R, Vatten LJ. Glycaemic control in newly diagnosed diabetes patients and mortality from ischaemic heart disease: 20 - year follow - up of the HUNT Study in Norway. Eur Heart J 2009;30: 1372 - 7.
18. FDA requires removal of certain restrictions on the diabetes drug Avandia. Silver Spring, MD: US Food and Drug Administration, 2013. http://www.fda.gov/NewsEvents/Newsroom/Pre ssAnnouncements/ucm3765 16.htm (accessed: May 1, 2014 ).
19. Strom BL. Methodologic challenges to studying patient safety and comparative effectiveness. Med Care 2007;45 (suppl 2): S13 - 5.
20. Pocock SJ, Collier TJ, Dandreo KJ, et al. Issues in the reporting of epidemiological studies: a surve y of recent practice. BMJ 2004;329: 883.
21. Von Elm E, Altman DG, Egger M, et al. The Strengthening The Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiology 2007;18: 800 - 4.
22. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening The Reporting of Observational Studies in Epide miology (STROBE): explanation and elaboration. Epidemiology 2007;18: 805 - 35.
23. Motheral B, Brooks J, Clark MA, et al. A checklist for retrospective database studies – report of the ISPOR Task Force on Retrospective Databases. Value Health 2003;6: 90 - 7.
24. GRACE p rinciples: good research for comparative effectiveness. Cambridge, MA: GRACE Initiative, 2010. https://www.pharmacoepi.org/pub/1c29f69f - 2354 - d714 - 5100 - 1ef2b0e9abd9 (access ed : May 1, 2014 ).
25. Dreyer NA, Schneeweiss S, McNeil BJ, et al. GRACE principles: recognizing high - quality observational studies of comparative effectiveness. Am J Manag Care 2010;16: 467 - 71.
26. McAfee AT, Koro C, Landon J, Ziyadeh N, Walker AM . Coronary heart disease outcomes in patients receiving antidiabetic agents. Pharmacoepidemiol Drug Saf 2007;16: 711 - 25.
27. Gerrits CM, Bhattacharya M, Manthena S, Baran R, Perez A, Kupfer S. A comparison of pioglitazone and rosiglitazone for hospitalization f or acute myocardial infarction in type 2 diabetes. Pharmacoepidemiol Drug Saf 2007;16: 1065 - 71.
28. Lipscombe LL, Gomes T, Lévesque LE, Hux JE, Juurlink DN, Alter DA. Thiazolidinediones and cardiovascular outcomes in older patients with diabetes. JAMA 2007;298: 2634 - 43.
29. Margolis DJ, Hoffstad O, Strom BL. Association between serious ischemic cardiac outcomes and medications used to treat diabetes. Pharmacoepidemiol Drug Saf 2008;17: 753 - 9.
30. Walker AM, Koro CE, Landon J. Coronary heart disease outcomes in patients re ceiving antidiabetic agents in the PharMetrics database 2000 - 2007. Pharmacoepidemiol Drug Saf 2008;17: 760 - 8.
31. Koro CE, Fu Q, Stender M. An assessment of the effect of thiazolidinedione exposure on the risk of myocardial infarction in type 2 diabetic patient s. Pharmacoepidemiol Drug Saf 2008;17: 989 - 96.
32. Winkelmayer WC, Setoguchi S, Levin R, Solomon DH. Comparison of cardiovascular outcomes in elderly patients with diabetes who initiated rosiglitazone vs pioglitazone therapy. Arch Intern Med 2008;168: 2368 - 75.
33. S tockl KM, Le L, Zhang S, Harada ASM. Risk of acute myocardial infarction in patients treated with thiazolidinediones or other antidiabetic medications. Pharmacoepidemiol Drug Saf 2009;18: 166 - 74.
34. Vanasse A, Carpentier AC, Courteau J, Asghari S. Stroke and c ardiovascular morbidity and mortality associated with rosiglitazone use in elderly diabetic patients. Diab Vasc Dis Res 200 9;6: 87 - 93.
35. Dormuth CR, Maclure M, Carney G, Schneeweiss S, Bassett K, Wright JM. Rosiglitazone and myocardial infarction in patients previously prescribed metformin. PLoS One 2009; 4: e6080.
36. Habib ZA, Tzogias L, Havstad SL, et al. Relationship between thiazolidinedione use and cardiovascular outcomes and all - cause mortality among patients with diabetes: a time - updated propensity analysis . Pharmacoepidemiol Drug Saf 2009;18: 437 - 47.
37. Dore DD, Trivedi AN, Mor V, Lapane KL. Association between extent of thiazolidinedione exposure and risk of acute myocardial infarction. Pharmacotherapy 2009;29: 775 - 83.
38. Hsiao FY, Huang WF, Wen YW, Chen PF, Kuo K N, Tsai YW. Thiazolidinediones and cardiovascular events in patients with type 2 diabetes mellitus: a retrospective cohort study of over 473,000 patients using a National Health Insurance database in Taiwan. Drug Saf 2009;32: 675 - 90.
39. Juurlink DN, Gomes T, L ipscombe LL, Austin PC, Hux JE, Mamdani MM. Adverse cardiovascular events during treatment with pioglitazone and rosiglitazone: population based cohort study. BMJ 2009;339: b2942.
40. Ziyadeh N, McAfee AT, Koro C, Landon J, Chan KA. The thiazolidinediones rosig litazone and pioglitazone and the risk of coronary heart disease: a retrospective cohort study using a US health insurance database. Clin Ther 2009;31: 2665 - 77.
41. Tzoulaki I, Molokhia M, Curcin V, et al. Risk of cardiovascular disease and all cause mortality among patients with type 2 diabetes prescribed oral antidiabetes drugs: retrospective cohort study using UK general practice research database. BMJ 2009; 339:b4731.
42. Brownstein JS, Murphy SN, Goldfine AB, et al. Rapid identification of myocardial infarction risk associated with diabetic medications using electronic medical records. Diabetes Care 2010;33: 526 - 31.
43. Graham DJ, Ouellet - Hellstrom R, MaCurdy TE, et al. Risk of acute myocardial infarction, stroke, heart failure, and death in elderly Medicare patients treated with rosiglitazone or pioglitazone. JAMA 2010;304: 411 - 8.
44. Loebstein R, Dushinat M, Vesterman - Landes J, et al. Database evaluation of the effects of long - term rosiglitazone treatment on cardiovascular outcomes in patients with type 2 diabetes. J Cli n Pharmacol 2011;51: 173 - 80.
45. Walker AM, McAfee AT, Koro C. Studies of diabetes, thiazolidinediones, and coronary heart disease. Pharmacoepidemiol Drug Saf 2007;16: 1313 - 4.
46. International Society for Pharmacoepidemiology. Guidelines for good pharmacoepidemiology practices (GPP). Pharmacoepidemiol Drug Saf 2008;17: 200 - 8.
47. Rawson NSB, Downey W, Maxwell CJ, West R. 25 years of pharmacoepidemiologic innovation: the Saskatchewan Health administrative databases. J Popu l Ther Clin Pharmacol 2011;18: e245 - 9.
48. Strom BL. How the US drug safety system should be changed. JAMA 2006; 29 5: 2072 - 5.
49. Hall GC, Sauer B, Bourke A, Brown JS, Reynolds MW, LoCasale R. Guidelines for good database selection and use in pharmacoepidemiology research. Pharm acoepidemiol Drug Saf 2012;21: 1 - 10.
50. Paters on JM, Suleiman A, Hux JE, Bell C . How complete are drug history profiles that are based on public drug benefit claims? Can J Clin Pharmacol 2008;15: e108 - 16.
51. Alshammari AM, Hux JE. The impact of non - fee - for - service reimbursement on chronic disease surveillance using administrative data. Can J Public Health 2009;100: 472 - 4.
52. Rawson NSB, D’Arcy C. “Validity” and reliability: idealism and reality in the use of computerized health car e databases for pharmacoepidemiological research. Post Market Surveill 1991;5 : 31 - 55.
53. Jollis JG, Ancukiewicz M, DeLong ER, et al. Discordance of databases designed for claims payment versus clinical information systems: implications for outcomes research. A nn Intern Med 1993;119: 844 - 50.
54. Newton KM, Wagner EH, Ramsey SD, et al. The use of automated data to identify complications and comorbidities of diabetes: a validation study. J Clin Epidemiol 1999;52: 199 - 207.
55. Austin PC, Daly PA, Tu JV. A multicenter study o f the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care uni ts in Ontario. Am Heart J 2002;144: 290 - 6.
56. Lanes SF, de Luise C. Bias due to false - positive diagnoses in an automated health insurance claims database. Drug Saf 2006;29: 1069 - 75.
57. Rawson NSB, Shatin D. Assessing the validity of diagnostic data in large administrative health care utilization databases. In: Hartzema AG, Tilson HH, Chan KA, eds. Pharmacoepidemiology and Therapeutic Risk Management. Cincin nati, OH: Harvey Whitney, 2008: 495 - 517.
58. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005;58: 323 - 37.
59. Terris DD, Litaker DG, Koroukian SM. Health state information deri ved from secondary databases is affected by multiple sources of bias. J Clin Epidemiol 2007;60: 734 - 41.
60. Crystal S, Akincigil A, Bilder S, Walkup JT . Studying prescription drug use and outcomes with Medicaid claims data. Med Care 2007;45(suppl 2): S58 - 65.
61. Raw son NSB. Access to linked administrative healthcare utilization data for pharmacoepidemiology and pharmacoeconomics research in Canada: anti - viral drugs as an example. P harmacoepidemiol Drug Saf 2009;18: 1072 - 9.
62. V an Walraven C, Austin P. Administrative data base research has unique characteristics that can risk biased results. J Clin Epidemiol 2012;65:126 - 31.
63. Hennessy S, Bilker WB, Weber A, et al. Descriptive analyses of the integrity of a US Medicaid claims database. Pharmacoepidemiol Drug Saf 2003;12: 103 - 11.
64. Hennessy S, Carson JL, Ray WA, et al. Medicaid databases. In: Strom BL, ed. Pharmacoepidemiology. 4th ed. Ch ichester, England: Wiley, 2005: 281 - 94.
65. Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the Genera l Practice Research Database: a systematic review. Br J Pharmacol 2010;69: 4 - 14.
66. Van Walraven C, Bennett C, Forster AJ. Administrative database research infrequently used validated diagnostic or procedural codes. J Clin Epidemiol 2011;64: 1054 - 9.
67. Saunders KW , Davis RL, Stergachis A. Group Health Cooperative. In: Strom BL, ed. Pharmacoepidemiology. 4th ed. Ch ichester, England: Wiley, 2005: 223 - 39.
68. Psaty BM, Boineau R, Kuller LH, Leupker RV. The potential costs of upcoding for heart failure in the United States. Am J Cardiol 1999;84: 108 - 9.
69. Croghan TW, Esposito D, Daniel G, Wahl P, Stoto MA. Using medical records to supplement a claims - based comparative effectiveness analysis of antidepressants. Pharmacoepidemiol Drug Saf 2010;19: 814 - 8.
70. Best practices for conducti ng and reporting pharmacoepidemiologic safety studies using electronic healthcare data sets: draft guidance for industry and FDA staff. Rockville, MD: Food and Drug Administration, May 2013. http://www.fda.gov/downloads/Drugs/Guidance ComplianceRegulatoryInformation/Guidances/U CM243537.pdf (accessed : May 1, 2014 ).
71. Levine M, Gaebel K. Impact of formulary policy on thiazolidinedione (TZD) use in t he Ontario Drug Benefit (ODB) program [Abst] . Clin Pharmacol Ther 2005;77: P72.
72. Abushomar H, Gaebel K, Levine M. Evaluation of patient access to diabetic medications [Abst] . Can J Clin Pharmacol 2005;12: e76.
73. Dorais M, LeLorier J. Impact of the socioeconomic status on the probability of receiving formulary restricted thiazolidinediones (TZDs). Can J Clin Pharmacol 2008; 15: e15 - 21.
74. Hanley G. Prescription drug insurance and unmet need for health care: a cross - sectio nal analysis. O pen Med 2009;3: 178 - 83.
75. Ray WA. Evaluating medication effects outside of clinical trials: new - use r designs. Am J Epidemiol 2003;158: 915 - 20.
76. Starner CI, Schafer JA, Heaton AH, Gleason PP. Rosiglitazone and pioglitazone utilization from January 2007 through M ay 2008 associated with five risk - warning events. J Manag Care Pharm 2008;14: 523 - 31.
77. Shatin D, Rawson NSB, Stergachis A. UnitedHealth Group. In: Strom BL, ed. Pharmacoepidemiology. 4th ed. Chichester: Wiley, 2005: 271 - 80 .
78. Skinner BJ. Waiting for reimburseme nt of new medicines in Canada: it’s time for a rethink. Pharmacoeconomics 2008;26: 629 - 32.
79. LeLorier J, Bell A, Bougher DJ, Cox JL, Turpie AGG. Drug reimbursement policies in Canada: need for improved access to critical therapies. Ann Pharmacother 2008;42: 869 - 73.
80. Groenwold RHH, Hak E, Hoes AW. Quantitative assessment of unobserved confounding is mandatory in nonrandomized intervention studies. J Clin Epidemiol 2009;62: 22 - 8.
81. Johnson ML, Crown W, Martin BC, Dormuth CR, Siebert U. Good research practices for c omparative effectiveness research: analytic methods to improve causal inference from nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report – part III . Value Health 2009; 12:1062 - 73.
82. Jackson ML, Nelson JC, Jackson LA. Why do covariates defined by International Classification of Diseases codes fail to remove confounding in pharmacoepidemiologic studies among seniors? Pharmacoepidemiol Drug Saf 2011;20: 858 - 65.
83. Brookhart MA, Stürmer T, Glynn RJ, Rassen J, Schneeweiss S. Confounding control in healthcare database research: challenges and poten tial approaches. Med Care 2010;48(suppl): S114 - 20.
84. Schneeweiss S. Sensitivity analysis and external adjustment for unme asured confounders in epidemiologic database studies of therapeutics. Pharmacoepidemiol Drug Saf 2006;15:291 - 303.
85. Klungel OH, Martens EP, Psaty B, et al. Methods to assess intended effects of drug treatment in observational studies are reviewed. J Clin Epi demiol 2004;57: 1 223 - 31.
86. Cox E, Martin BC, Van Staa T, Garbe E, Siebert U, Johnson ML. Good research practices for comparative effectiveness research: approaches to mitigating bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report – part II. Value Health 2009;12:1053 - 61.
87. European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (EnCEPP). Guide on met hodological standards in pharmacoepidemiology (revision 2 ). London: Euro pean Medicines Agency, June 2013 . http://www.encepp.eu/standards_and_guid ances/documents/ENCePPGuideMethStandards PE_Rev2.pdf (accessed : May 1, 2014 ).
88. McMahon AD. Approaches to combat with confounding by indication in observational studies of intended drug effects. Pharmacoepidemiol Drug Sa f 2003;12: 551 - 8.
89. Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology 2000;11:550 - 60.
90. Bosco JLF, Silliman RA, Thwin SS, et al. A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies. J Clin Epidemiol 2010; 63: 64 - 74.
91. Thamer M, Hernán MA, Zhang Y, Cotter D, Petri M. Prednisone, lupus activity, and permanent organ damage. J Rheumatol 2009; 36: 560 - 4.
92. Schaubel D, Hanley J, Collet JP, et al. Two - stage sa mpling for etiologic studies: sample size and power. Am J Epidemiol 1997;146: 450 - 8.
93. Stürmer T, Glynn RJ, Rothman KJ, Avorn J. Adjustments for unmeasured confounders in pharmacoepidemiologic database studies using external information. Med Care 2007; 45(supp l 2) : S158 - 65.
94. Faries DE, Leon AC, Haro JM, Obenchain RL, eds. Analysis of Observational Health Care Data using SAS ® . Cary, NC: SAS Institute, 2010.
95. Berger ML, Mamdani M, Atkins D, Johnson ML. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report – part I. Value Health 2009;12: 1044 - 52.
96. Shapiro S. Explaining risk: a guide for health professionals. Maturitas 2009; 64: 143 - 4.
97. Shapiro S. Bias in the evaluation of low - magnitude associations: an empirical perspective. Am J Epidemiol 2000; 151: 939 - 45.
98. Shapiro S. Causation, bias and confounding: a hitchhiker’s guide to the epidemiological galaxy, part 2. Principles of causality in epidemiological research: confounding, effect modification and strength of association. J Fam Plann Reprod Health Care 2008;34:185 - 90.
99. Stewart KA, Natzke BM, Williams T, Granger E, Casscells SW, Croghan TW. Temporal trends in anti - diabetes drug use in tricare following safety warnings in 2007 about rosiglitazone. Pharmacoepidemiol Drug Saf 2009;18:1048 - 52.
100. Cohen A, Rabbani A, Shah A, Alexander GC. Changes in glitazone use among office - based physicians in the US, 2003 - 2009. Diabetes Care 2010;33: 823 - 5.
101. Rawson NSB, Ross Terres JA. Rosiglitazone use and associated adverse event rates in Canada between 2004 and 2010. BMC Res Notes 2013;6: 82.
102. Fanning EL, Weissma n PN, Menditto LA. Clinical practice effect of rosiglitazone discontinuation on glycemic control. Endocr Pract 2009;15: 270 - 2.
103. Aspinall SL, Zhao X, Good CB, Stone RA, Smith KJ, Cunningham FE. FDA warning and removal of rosiglitazone from VA national f ormula ry. Am J Manag Care 2013;19: 748 - 58.
104. Kung J, Henry RR. Thiazolidinedione safety. Expert Opin Drug Saf 2012; 11: 565 - 79.
105. Hiatt WR, Kaul S, Smith RJ. The cardiovascular safety of diabetes drugs – insights from the rosiglitazone experience. N Engl J Med 2013 ;369:1285 - 7.
Article Sidebar
Published
Nov 17, 2018
Article Details
How to Cite
Rawson, N. S. B. (2018). REVIEW OF THE QUALITY OF OBSERVATIONAL STUDIES OF THE ASSOCIATION BETWEEN ROSIGLITAZONE AND ACUTE MYOCARDIAL INFARCTION. Journal of Population Therapeutics and Clinical Pharmacology, 21(2). https://mail.jptcp.com/index.php/jptcp/article/view/317
Issue
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles published in JPTCP are licensed under Copyright Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Rawson, N. S. B. (2018). REVIEW OF THE QUALITY OF OBSERVATIONAL STUDIES OF THE ASSOCIATION BETWEEN ROSIGLITAZONE AND ACUTE MYOCARDIAL INFARCTION. Journal of Population Therapeutics and Clinical Pharmacology, 21(2). https://mail.jptcp.com/index.php/jptcp/article/view/317