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Randomized Controlled Trials

  • Mike ArmourEmail author
  • Carolyn Ee
  • Genevieve Z. Steiner
Reference work entry

Abstract

This chapter covers the current gold standard for evaluating the effectiveness of therapeutic interventions, the randomized controlled trial (RCT). Key features of the RCT, regardless of sub-type, are randomization, allocation concealment, and blinding. These key features help reduce bias and the influence of confounding variables, making the randomized controlled trial eminently suitable to determine cause and effect relationships. Protocol design and registration prior to trial onset are important factors in determining the quality of the trial, and various trial design sub-types, including parallel, factorial, crossover, and cluster, are outlined and the strengths and weakness of each examined. Various checklists such as SPIRIT and CONSORT can be used to ensure proper reporting of both trial protocols and trial findings, to ensure clear, concise reporting. Finally, the shortcomings of RCTs and newer trial designs, such as comparative effectiveness research and pragmatic studies, designed to overcome some of these issues are examined, and ways to make clinical trial results more clinically applicable are discussed.

Keywords

Randomized controlled trials Blinding Factorial Pragmatic Factorial Cluster Crossover Pragmatic Comparative effectiveness 

References

  1. Altman DG, Bland JM. How to randomise. BMJ. 1999a;319(7211):703–4.CrossRefGoogle Scholar
  2. Altman DG, Bland JM. Statistics notes. Treatment allocation in controlled trials: why randomise? BMJ. 1999b;318(7192):1209.CrossRefGoogle Scholar
  3. Arnold DM, Burns KEA, Adhikari NKJ, Kho ME, Meade MO, Cook DJ. The design and interpretation of pilot trials in clinical research in critical care. Crit Care Med. 2009;37(1 Suppl):S69–74.CrossRefGoogle Scholar
  4. Barr K, Smith CA, de Lacey SL. Participation in a randomised controlled trial of acupuncture as an adjunct to in vitro fertilisation: the views of study patients and acupuncturists. Eur J Integr Med. 2016;8(1):48–54.  https://doi.org/10.1016/j.eujim.2015.10.006.CrossRefGoogle Scholar
  5. Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gotzsche PC, Krleza-Jeric K,... Moher D. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3): 200–7.  https://doi.org/10.7326/0003-4819-158-3-201302050-00583.CrossRefGoogle Scholar
  6. Committee for Proprietary Medicinal Products. Points to consider on switching between superiority and non-inferiority. Br J Clin Pharmacol. 2001;52(3):223–8.CrossRefGoogle Scholar
  7. Community Intervention Trial for Smoking Cessation (COMMIT): I. cohort results from a four-year community intervention. Am J Public Health. 1995;85(2): 183–92.Google Scholar
  8. Cornfield J. Randomization by group: a formal analysis. Am J Epidemiol. 1978;108(2):100–2.CrossRefGoogle Scholar
  9. De Angelis C, Drazen JM, Frizelle FA, Haug C, Hoey J, Horton R,... International Committee of Medical Journal, E. Clinical trial registration: a statement from the International Committee of Medical Journal Editors. N Engl J Med. 2004;351(12): 1250–1.  https://doi.org/10.1056/NEJMe048225.CrossRefGoogle Scholar
  10. Doherty S. History of evidence-based medicine. Oranges, chloride of lime and leeches: barriers to teaching old dogs new tricks. Emerg Med Australas. 2005;17(4):314–21.Google Scholar
  11. Doig GS, Simpson F. Randomization and allocation concealment: a practical guide for researchers. J Crit Care. 2005;20(2):187–91.; discussion 191–83.  https://doi.org/10.1016/j.jcrc.2005.04.005.CrossRefGoogle Scholar
  12. Doll R. Controlled trials: the 1948 watershed. BMJ. 1998;317(7167): 1217–20.CrossRefGoogle Scholar
  13. Donner A, Klar N. Pitfalls of and controversies in cluster randomization trials. Am J Public Health. 2004;94(3):416–22.CrossRefGoogle Scholar
  14. Fanelli D. Do pressures to publish increase scientists’ bias? An empirical support from US states data. PLoS One. 2010;5(4):e10271.  https://doi.org/10.1371/journal.pone.0010271.CrossRefGoogle Scholar
  15. Feeley N, Cossette S, Cote J, Heon M, Stremler R, Martorella G, Purden M. The importance of piloting an RCT intervention. Can J Nurs Res. 2009;41(2):85–99.Google Scholar
  16. Ganju J, Rom D. Non-inferiority versus superiority drug claims: the (not so) subtle distinction. Trials. 2017;18(1):278.  https://doi.org/10.1186/s13063-017-2024-2.CrossRefGoogle Scholar
  17. Gartlehner G, Hansen R, Nissman D, Lodhr K, Carey T. Criteria for distinguishing effectiveness from efficacy in systematic reviews. 2006. Retrieved from.Google Scholar
  18. Gluud LL. Bias in clinical intervention research. Am J Epidemiol. 2006;163(6):493–501.  https://doi.org/10.1093/aje/kwj069.CrossRefGoogle Scholar
  19. Higgins JP, Altman DG, Gotzsche PC, Juni P, Moher D, Oxman AD,... Sterne JA. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343: d5928.  https://doi.org/10.1136/bmj.d5928.CrossRefGoogle Scholar
  20. Hill AB. The clinical trial. N Engl J Med. 1952;247(4):113–9.  https://doi.org/10.1056/nejm195207242470401.CrossRefGoogle Scholar
  21. Hollis S, Campbell F. What is meant by intention to treat analysis? Survey of published randomised controlled trials. BMJ. 1999;319(7211):670–4.CrossRefGoogle Scholar
  22. ICH. ICH harmonised tripartite guideline. Guideline for Good Clinical Practice E6(R1) 1996.Google Scholar
  23. Jairath N, Hogerney M, Parsons C. The role of the pilot study: a case illustration from cardiac nursing research. Appl Nurs Res. 2000;13(2):92–6.CrossRefGoogle Scholar
  24. Juni P, Altman DG, Egger M. Systematic reviews in health care: assessing the quality of controlled clinical trials. BMJ. 2001;323(7303):42–6.CrossRefGoogle Scholar
  25. Kalish LA, Begg CB. Treatment allocation methods in clinical trials: a review. Stat Med. 1985;4(2):129–44.CrossRefGoogle Scholar
  26. Katz MH. Study design and statistical analysis: a practical guide for clinicians. Cambridge: Cambridge University Press; 2006.CrossRefGoogle Scholar
  27. Landorf KB. Clinical trials: the good, the bad and the ugly. In: Liamputtong P, editor. Research methods in health: foundations for evidence-based practice. 3rd ed. Melbourne: Oxford University Press; 2017. p. 275–90.Google Scholar
  28. Lesaffre E. Superiority, equivalence, and non-inferiority trials. Bull NYU Hosp Jt Dis. 2008;66(2):150–4.Google Scholar
  29. Manchikanti L. Evidence-based medicine, systematic reviews, and guidelines in interventional pain management, part I: introduction and general considerations. Pain Physician. 2008;11(2):161–86.Google Scholar
  30. Mayer D. Essential evidence-based medicine. Cambridge: Cambridge University Press; 2004.Google Scholar
  31. Moher D, Schulz KF, Altman DG. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. Ann Intern Med. 2001;134(8):657–62.CrossRefGoogle Scholar
  32. Moher D, Hopewell S, Schulz K.F, Montori V, Gotzsche PC, Devereaux PJ,.... Consort. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. Int J Surg (Lond). 2012;10(1): 28–55.CrossRefGoogle Scholar
  33. Piaggio G, Elbourne DR, Altman DG, Pocock SJ, Evans SJ, Group C. Reporting of noninferiority and equivalence randomized trials: an extension of the CONSORT statement. JAMA. 2006;295(10):1152–60.  https://doi.org/10.1001/jama.295.10.1152.CrossRefGoogle Scholar
  34. Sackett DL. Bias in analytic research. J Chronic Dis. 1979;32(1–2):51–63.CrossRefGoogle Scholar
  35. Schulz KF, Chalmers I, Hayes RJ, Altman DG. Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA. 1995;273(5):408–12.CrossRefGoogle Scholar
  36. Scott A, Rucklidge JJ, Mulder RT. Is mandatory prospective trial registration working to prevent publication of unregistered trials and selective outcome reporting? An observational study of five psychiatry journals that mandate prospective clinical trial registration. PLoS One. 2015;10(8):e0133718.  https://doi.org/10.1371/journal.pone.0133718.CrossRefGoogle Scholar
  37. Suresh KP. An overview of randomization techniques: an unbiased assessment of outcome in clinical research. J Hum Reprod Sci. 2011;4(1):8–11.  https://doi.org/10.4103/0974-1208.82352.CrossRefGoogle Scholar
  38. The CONSORT Statement. The CONSORT statement. 2017. Retrieved from http://www.consort-statement.org/
  39. The James Lind Library. Avoiding biased comparisons. 2007a. Retrieved from http://www.jameslindlibrary.org/essays/bias/avoiding-biased-comparisons.html
  40. The James Lind Library. Differences in the way treatment outcomes are assessed. 2007b. Retrieved from www.jameslind.org
  41. The James Lind Library. Taking account of the play of chance. 2007c. 17 Dec 2009. Retrieved from www.jameslind.org
  42. Thorpe KE, Zwarenstein M, Oxman AD, Treweek S, Furberg CD, Altman DG,... Chalkidou K. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. J Clin Epidemiol. 2009;62(5): 464–75.  https://doi.org/10.1016/j.jclinepi.2008.12.011.CrossRefGoogle Scholar
  43. Viboud C, Boelle PY, Kelly J, Auquier A, Schlingmann J, Roujeau JC, Flahault A. Comparison of the statistical efficiency of case-crossover and case-control designs: application to severe cutaneous adverse reactions. J Clin Epidemiol. 2001;54(12):1218–27.CrossRefGoogle Scholar
  44. Witt CM, Aickin M, Baca T, Cherkin D, Haan MN, Hammerschlag R.,... Berman BM. Effectiveness Guidance Document (EGD) for acupuncture research – a consensus document for conducting trials. BMC Complement Altern Med. 2012;12:148.  https://doi.org/10.1186/1472-6882-12-148.

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Mike Armour
    • 1
    Email author
  • Carolyn Ee
    • 1
  • Genevieve Z. Steiner
    • 2
  1. 1.NICM, Western Sydney University (Campbelltown Campus)PenrithAustralia
  2. 2.NICM and Translational Health Research Institute (THRI)Western Sydney UniversityPenrithAustralia

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