Preview

Russian Journal of Cardiology

Advanced search

Evidence-based approaches to comparing the effectiveness of modern cardiology interventions: trends, bias and prospects

https://doi.org/10.15829/1560-4071-2020-4037

Abstract

The article discusses the limitations of the evidence from observational studies. Modern approaches to reducing bias in observational studies are discussed in detail, in particular, propensity score matching, which has become popular in recent years. The main differences between randomized and observational studies are discussed. Arguments against the observational studies and improved methods of analysis to compare the treatments’ effectiveness in clinical practice are presented. The role of observational studies as a source of evidence is discussed. The article points out the validity of performing large-scale prospective observational studies to assess the effects of postmarketing drug use in clinical practice, as well as to obtain data on drug use in patients that differ from those in randomized clinical trials.

About the Authors

S. R. Gilyarevsky
Russian Medical Academy of Continuous Professional Education
Russian Federation
Moscow


Yu. N. Belenkov
I.M. Sechenov First Moscow State Medical University
Russian Federation
Moscow


References

1. Kahneman D. Thinking, fast and slow. M:AST. 2014. 656 p. (In Russ.) Канеман Д. Думай медленно, решай быстро. пер. с англ.; Москва: АСТ, 2014. 656 c. ISBN: 978-5-17-080053-7.

2. Fanaroff AC, Califf RM, Lopes RD. New Approaches to Conducting Randomized Controlled Trials. J Am Coll Cardiol. 2020;75:556-9. doi:10.1016/j.jacc.2019.11.043.

3. Murray KW, Duggan A. Understanding Confounding in Research Pediatr Rev. 2010;31(3):124-6. doi:10.1542/pir.31-3-124.

4. Meuli L, Dick F. Understanding Confounding in Observational Studies. Eur J Vasc Endovasc Surg. 2018;55(5):737. doi:10.1016/j.ejvs.2018.02.028.

5. Fanaroff AC, Califf RM, Windecker S, et al. Levels of Evidence Supporting American College of Cardiology/American Heart Association and European Society of Cardiology Guidelines, 2008-2018. JAMA. 2019;321:1069-80. doi:10.1001/jama.2019.1122.

6. Schüpke S, Neumann FJ, Menichelli M, et al; ISAR-REACT 5 Trial Investigators. Ticagrelor or Prasugrel in Patients with Acute Coronary Syndromes. N Engl J Med. 2019;381:1524-34. doi:10.1056/NEJMoa1908973.

7. Nanna MG, Navar AM, Wang TY, et al. Practice-level variation in statin use and lowdensity lipoprotein cholesterol control in the United States: results from the Patient and Provider Assessment of Lipid Management (PALM) registry. Am Heart J. 2019;214:113-24. doi:10.1016/j.ahj.2019.05.009.

8. Harrington D, D’Agostino RBSr, Gatsonis C, et al. New Guidelines for Statistical Reporting in the Journal. N Engl J Med. 2019;381:285-6. doi:10.1056/NEJMe1906559.

9. Mehra MR, Desai SS, Kuy S, et al. Cardiovascular disease, drug therapy, and mortality in Covid-19. N Engl J Med. published online May 1. doi:10.1056/NEJMoa2007621.

10. Mehra MR, Desai SS, Ruschitzka F, Patel AN. Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis. Lancet. 2020; published online May 22. doi:10.1016/S0140-6736(20)31180-6.

11. Mehra MR, Desai SS, Kuy S, et al. Retraction: Cardiovascular Disease, Drug Therapy, and Mortality in Covid-19. N Engl J Med. doi:10.1056/NEJMoa2007621 [ahead of print, 2020 Jun 4] [retraction of: N Engl J Med. 2020 May 1]. N Engl J Med . 2020;382(26):2582. doi:10.1056/NEJMc2021225.

12. Mehra MR, Ruschitzka F, Patel AN. Retraction-Hydroxychloroquine or Chloroquine With or Without a Macrolide for Treatment of COVID-19: A Multinational Registry Analysis. Retraction of Publication Lancet. 2020 Jun 5;S0140-6736(20)31324-6. doi:10.1016/S0140-6736(20)31324-6. Ahead of print.

13. Hellenbart EL, Faulkenberg KD, Finks SW. Evaluation of bleeding in patients receiving direct oral anticoagulants. Vasc Health Risk Manag. 2017;13:325-42. doi:10.2147/VHRM.S121661.

14. Guimarães PO, Krishnamoorthy A, Kaltenbach LA, et al. Accuracy of Medical Claims for Identifying Cardiovascular and Bleeding Events After Myocardial Infarction: A Secondary Analysis of the TRANSLATE-ACS Study. JAMA Cardiol. 2017;2(7):750-7. doi:10.1001/jamacardio.2017.1460.

15. Fralick M, Colacci M, Schneeweiss S, et al. Effectiveness and Safety of Apixaban Compared With Rivaroxaban for Patients With Atrial Fibrillation in Routine Practice: A Cohort Study. Ann Intern Med. 2020;172(7):463-73. doi:10.7326/M19-2522.

16. Kuss O, Blettner M, Börgermann J. Propensity Score: an Alternative Method of Analyzing Treatment Effects. Dtsch Arztebl Int. 2016;113(35-36):597-603. doi:10.3238/arztebl.2016.0597.

17. Black N. Why we need observational studies to evaluate the effectiveness of health care. BMJ. 1996;312:1215-8. doi:10.1136/bmj.312.7040.1215.

18. McKee M, Britton A, Black N, et al. Methods in health services research. Interpreting the evidence: choosing between randomised and non-randomised studies. BMJ. 1999;319:312-5. doi:10.1136/bmj.319.7205.312.

19. Rothwell PM. External validity of randomised controlled trials: „to whom do the results of this trial apply?“. Lancet. 2005;365:82-93. doi:10.1016/S0140-6736(04)17670-8.

20. Camm AJ, Amarenco P, Haas S, et al; XANTUS Investigators. XANTUS: a real-world, prospective, observational study of patients treated with rivaroxaban for stroke prevention in atrial fibrillation. Eur Heart J. 2016;37(14):1145-53. doi:10.1093/eurheartj/ehv466.

21. Gueyffier F, Cucherat M. The limitations of observation studies for decision making regarding drugs efficacy and safety. Therapie. 2019;74:181-5. doi:10.1016/j.therap.2018.11.001.

22. Packer M. Are Meta-Analyses a Form of Medical Fake News? Thoughts About How They Should Contribute to Medical Science and Practice. Circulation. 2017;136:2097-9. doi:10.1161/CIRCULATIONAHA.117.030209.

23. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41-55. doi:10.1093/biomet/70.1.41.

24. Brookhart MA, Schneeweiss S, Rothman KJ, et al. Variable selection for propensity score models. Am J Epidemiol. 2006;163:1149-56. doi:10.1093/aje/kwj149.

25. Austin PC. The relative ability of different propensity score methods to balance measured covariates between treated and untreated subjects in observational studies. Med Decis Making. 2009;29:661-77. doi:10.1177/0272989X09341755.

26. Stuart EA, Marcus SM, Horvitz-Lennon MV, et al. Using non-experimental data to estimate treatment effects. Psychiatr Ann. 2009;39:719-28. doi:10.3928/00485713-20090625-07

27. Austin PC. Propensity-score matching in the cardiovascular surgery literature from 2004 to 2006: a systematic review and suggestions for improvement. J Thorac Cardiovasc Surg. 2007;134:1128-35. doi:10.1016/j.jtcvs.2007.07.021.

28. Morgan SL, Harding DJ. Matching estimators of causal effects: prospects and pitfalls in theory and practice. Sociological Methods Res. 2006;35:3-60.

29. Weitzen S, Lapane KL, Toledano AY, et al. Weaknesses of goodness of fit tests for evaluating propensity score models: the case of the omitted confounder. Pharmacoepidemiol Drug Saf. 2005;14:227-38. doi:10.1002/pds.986.

30. Mueller S, Groth A, Spitzer SG, et al. Real-world Effectiveness and Safety of Oral Anticoagulation Strategies in Atrial Fibrillation: A Cohort Study Based on a German Claims Dataset. Pragmat Obs Res. 2018;9:1-10. doi:10.2147/POR.S156521.

31. Turgeon RD, Koshman SL, Youngson E, et al. Association of Ticagrelor vs Clopidogrel With Major Adverse Coronary Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention. JAMA Intern Med. 2020;180:420-8. doi:10.1001/jamainternmed.2019.6447.

32. Jonasson C, Ghanima W, Söderdahl F, Halvorsen S. Comparison of Dabigatran, Rivaroxaban, and Apixaban for Effectiveness and Safety in Atrial Fibrillation: A Nationwide Cohort Study. Eur Heart J Cardiovasc Pharmacother. 2020;6:75-85. doi:10.1093/ehjcvp/pvz086.

33. Healey JS. Stroke Prevention in Atrial Fibrillation: What Is Real World, and What Do RealWorld Data Reveal? J Am Coll Cardiol. 2018;72(2):154-5. doi:10.1016/j.jacc.2018.04.057.

34. Bowman L, Baras A, Bombien R, et al. Understanding the use of observational and randomized data in cardiovascular medicine. Eur Heart J. 2020;41(27):2571-8. doi:10.1093/eurheartj/ehaa020.


Review

For citations:


Gilyarevsky S.R., Belenkov Yu.N. Evidence-based approaches to comparing the effectiveness of modern cardiology interventions: trends, bias and prospects. Russian Journal of Cardiology. 2020;25(8):4037. (In Russ.) https://doi.org/10.15829/1560-4071-2020-4037

Views: 693


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1560-4071 (Print)
ISSN 2618-7620 (Online)