Hostname: page-component-8448b6f56d-dnltx Total loading time: 0 Render date: 2024-04-24T02:51:40.728Z Has data issue: false hasContentIssue false
  • English
  • Français

The Evidence-based Medicine Paradigm: Where are We 20 Years Later? Part 2

Published online by Cambridge University Press:  23 September 2014

Shashi S. Seshia  and
G. Bryan Young
Shashi S. Seshia*
Affiliation:
Department of Pediatrics, Division of Pediatric Neurology, University of Saskatchewan, Royal University Hospital, Saskatoon, Saskatchewan
G. Bryan Young
Affiliation:
Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada
*
Department of Pediatrics, Division of Pediatric Neurology, University of Saskatchewan, Royal University Hospital, 108 Hospital Drive, Saskatoon, Saskatchewan, S7N 0W8, Canada. Email: sseshia@yahoo.ca
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In Part 2, we discuss the challenges of keeping up with the ‘literature,’ evidence-based medicine (EBM) in emerging economies and the Neurosciences, and two recent approaches to classifying evidence. We conclude by summarizing information from Parts 1 and 2 which suggest the need to critically re-appraise core elements of the EBM paradigm: (1) the hierarchical ranking of evidence, (2) randomized controlled trials or systematic reviews as the gold standard for all clinical questions or situations, (3) the statistical tests that have become integral to the ‘measurements’ for analyzing evidence, and (4) re-incorporating a role for evidence from basic sciences and pathophysiology. An understanding of how cognitive processes influence clinical decisions is also necessary to improve evidence-based practice. Emerging economies may have to modify the design and conduct of clinical research to their settings. Like all paradigms, EBM must keep improving with input from the grassroots to remain beneficial.

Résumé:

Résumé:

Dans cette deuxième partie, nous discutons des défis que présentent le suivi de la littérature, la médecine fondée sur des données probantes (MFDP) dans les économies émergentes et les neurosciences ainsi que deux approches novatrices de classification des données. Nous concluons par un sommaire de l'information contenue dans les parties 1 et 2 qui suggère que nous devons réévaluer de façon critique des éléments fondamentaux du paradigme de la MFDP: 1) le classement hiérarchique des données; 2) les études randomisées contrôlées ou les revues systématiques comme étalon or en ce qui concerne toutes les questions ou situations cliniques; 3) les tests statistiques qui sont devenus une partie fondamentale des « mesures » utilisées pour analyser les données et 4) le rôle des données des sciences de base et de la physiopathologie qui devrait être rétabli. La compréhension de la façon dont les processus cognitifs influencent les décisions cliniques est également nécessaire pour améliorer la pratique médicale fondée sur des preuves. Les économies émergentes pourraient devoir modifier la conception et la réalisation de la recherche clinique dans leur contexte. Comme tout paradigme, la MFDP doit s'améliorer constamment en tenant compte des contributions du milieu pour demeurer bénéfique.

Type
Review Article
Information
Canadian Journal of Neurological Sciences , Volume 40 , Issue 4 , July 2013 , pp. 475 - 481
Copyright
Copyright © The Canadian Journal of Neurological 2013

References

1. Bastian, H, Glasziou, P, Chalmers, I. Seventy-five trials and eleven systematic reviews a day: how will we ever keep u.p? PLoS Med. 2010;7:e1000326.Google Scholar
2. Straus, SE, Glasziou, P, Richardson, WS, Haynes, RB. Evidence-based Medicine; 4th ed. Toronto: Churchill Livingstone Elsevier, 2011.Google Scholar
3. Montori, VM, Guyatt, GH. Progress in evidence-based medicine. JAMA. 2008;300:1814–6.Google Scholar
4. Feinstein, AR, Horwitz, RI. Problems in the “evidence” of “evidence-based medicine”. Am J Med. 1997;103:529–35.CrossRefGoogle Scholar
5. Schulz, KF, Altman, DG, Moher, D, CONSORT Group. CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med. 2010;152:726–32.CrossRefGoogle ScholarPubMed
6. Hirst, A, Altman, DG. Are peer reviewers encouraged to use reporting guidelines? survey of 116 health research journals. PLoS One. 2012;7:e35621.Google Scholar
7. CONSORT, group. [cited 2012 Dec 13]. Available from: http://www.consort-statement.org. Google Scholar
8. Berwanger, O, Ribeiro, RA, Finkelsztejn, A, et al. The quality of reporting of trial abstracts is suboptimal: survey of major general medical journals. J Clin Epidemiol. 2009;62:387–92.Google Scholar
9. Shukralla, AA, Tudur-Smith, C, Powell, GA, Williamson, PR, Marson, AG. Reporting of adverse events in randomised controlled trials of antiepileptic drugs using the CONSORT criteri for reporting harms. Epilepsy Res. 2011;97:20–9.CrossRefGoogle Scholar
10. Assadi, R, Zarghi, N, Sapehri, Shamloo A, Nikooiyan, Y. Evidence-based abstracts: what research summaries should contain to support evidence-based medicine. Int J Evid Based Healthc. 2012;10:154–8.Google Scholar
11. DeMauro, SB, Giaccone, A, Kirpalani, H, Schmidt, B. Quality of reporting of neonatal and infant trials in high-impact journals. Pediatrics. 2011;128:e639–44.Google Scholar
12. Kiehna, EN, Starke, RM, Pouratian, N, Dumont, AS. Standards for reporting randomized controlled trials in neurosurgery. J Neurosurg. 2011;114:280–5.CrossRefGoogle ScholarPubMed
13. Rutjes, AW, Reitsma, JB, Di Nisio, M, Smidt, N, van Rijn, JC, Bossuyt PM. Evidence of bias and variation in diagnostic accuracy studies. CMAJ. 2006;174:469–76.Google Scholar
14. STARD. [Update April 2008; cited 2012 Dec 13]. Available from: http://www.stard-statement.org. Google Scholar
15. Bossuyt, PM. STARD statement: still room for improvement in the reporting of diagnostic accuracy studies. Radiology. 2008;248:713–4.Google Scholar
16. Schunemann, HJ, Oxman, AD, Brozek, J, et al. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ. 2008;336:1106–10.Google Scholar
17. Hess, AS, Shardell, M, Johnson, JK, et al. Methods and recommendations for evaluating and reporting a new diagnostic test. Eur J Clin Microbiol Infect Dis. 2012;31:2111–6.Google Scholar
18. Atkins, D, Best, D, Briss, PA, et al. Grading quality of evidence and strength of recommendations. BMJ. 2004;328:1490.Google Scholar
19. Atkins, D, Eccles, M, Flottorp, S, et al. Systems for grading the quality of evidence and the strength of recommendations I: critical appraisal of existing approaches The GRADE Working Group. BMC Health Serv Res. 2004;4:38.CrossRefGoogle ScholarPubMed
20. Atkins, D, Briss, PA, Eccles, M, et al. Systems for grading the quality of evidence and the strength of recommendations II: pilot study of a new system. BMC Health Serv Res. 2005;5:25.CrossRefGoogle ScholarPubMed
21. Guyatt, GH, Oxman, AD, Vist, GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–6.Google Scholar
22. Guyatt, GH, Oxman, AD, Kunz, R, et al. What is “quality of evidence” and why is it important to clinicians? BMJ. 2008;336:995–8.Google Scholar
23. Guyatt, GH, Oxman, AD, Kunz, R, et al. Going from evidence to recommendations. BMJ. 2008;336:1049–51.CrossRefGoogle ScholarPubMed
24. Guyatt, GH, Oxman, AD, Kunz, R, et al. Incorporating considerations of resources use into grading recommendations. BMJ. 2008;336:1170–3.Google Scholar
25. Guyatt, G, Oxman, AD, Akl, EA, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64:383–94.Google Scholar
26. Thornton, J, Alderson, P, Tan, T, et al. Introducing GRADE across the NICE clinical guideline program. J Clin Epidemiol. 2013 Feb;66(2):124–31.CrossRefGoogle ScholarPubMed
27. Nakagawa, TA, Ashwal, S, Mathur, M, Mysore, M, Committee For Determination Of Brain Death In Infants Children. Guidelines for the determination of brain death in infants and children: an update of the 1987 task force recommendations-executive summary. Ann Neurol. 2012;71:573–85.Google Scholar
28. Pringsheim, T, Davenport, W, Mackie, G, et al. Canadian Headache Society guideline for migraine prophylaxis. Can J Neurol Sci. 2012;39:S1–59.Google Scholar
29. Goldenberg, MJ, Borgerson, K, Bluhm, R. The nature of evidence in evidence-based medicine: guest editors’ introduction. Perspect Biol Med. 2009;52:164–7.Google Scholar
30. Upshur, R. Making the grade: assuring trustworthiness in evidence. Perspect Biol Med. 2009;52:264–75.Google Scholar
31. Hartling, L, Fernandes, RM, Seida, J, Vandermeer, B, Dryden, DM. From the trenches: a cross-sectional study applying the GRADE tool in systematic reviews of healthcare interventions. PLoS One. 2012;7:e34697.Google Scholar
32. Centre for Evidence-Based Medicine, University of Oxford. Oxford, UK. [cited 2012 Dec 12]. Available from: http://www.cebm.net. Google Scholar
33. Oricha, BS, Yauri, MB. Uncertainty principle versus clincal equipoise in clinical trials in Sub-Saharan Africa: Are they really tenable? Ann African Med. 2003;2(2):99–100.Google Scholar
34. Jadad, AR, Enkin, MW. Randomized controlled trials. Oxford, UK: Blackwell Publishing BMJI Books, 2007.Google Scholar
35. Burneo, JG, Demaerschalk, BM, Jenkins, ME, editors. Neurology: An evidence-based approach. New York: Springer 2012.Google Scholar
36. Wiebe, S, Demaerschalk, B. Evidence based care in the neurosciences. Can J Neurol Sci. 2002;29:115–9.CrossRefGoogle ScholarPubMed
37. Gronseth, G, French, J. Practice parameters and technology assessments: what they are, what they are not, and why you should care. Neurology. 2008;71:1639–43.Google Scholar
38. French, J, Gronseth, G. Lost in a jungle of evidence: we need a compass. Neurology. 2008;71:1634–8.Google Scholar
39. Brigo, F. New anti-epileptic drugs: overcoming the limits of randomised controlled trials. Int J Evid Based Healthc. 2011;9:440–3.Google Scholar
40. Mattson, RH, Cramer, JA, Delgado, Escuet AV, Smith, DB, Collins, JF. A design for the prospective evaluation of the efficacy and toxicity of antiepileptic drugs in adults. Neurology. 1983;33:14–25.CrossRefGoogle ScholarPubMed
41. Mattson, RH, Cramer, JA, Collins, JF, et al. Comparison of carbamazepine, phenobarbital, phenytoin, and primidone in partial and secondarily generalized tonic-clonic seizures. N Engl J Med. 1985;313:145–51.Google Scholar
42. Anonymous. Clobazam has equivalent efficacy to carbamazepine and phenytoin as monotherapy for childhood epilepsy. Canadian Study Group for Childhood Epilepsy. Epilepsia. 1998;39:952–9.Google Scholar
43. Wiebe, S, Blume, WT, Girvin, JP, Eliasziw, M, Effectiveness and Efficiency of Surgery for Temporal Lobe Epilepsy Study Group. randomized, controlled trial of surgery for temporal-lobe epilepsy. N Engl J Med. 2001;345:311–8.Google Scholar
44. Barnett, HJM. Experiences with the execution of intercultural, intercontinental trials - Part I. Can J Neurol Sci. 2013;40:324–9.Google Scholar
45. Goodin, DS, Reder, AT. Evidence-based medicine: promise and pitfalls. Mult Scler. 2012;18:947–8.Google Scholar
46. Gronseth, GS, Ashman, E. The AAN response to evidence-based medicine: promise and pitfalls. Mult Scler. 2012;18:949–50.Google Scholar
47. Mendelson, AA, Gillis, C, Henderson, WR, Ronco, JJ, Dhingra, V, Griesdale, DE. Intracranial pressure monitors in traumatic brain injury: a systematic review. Can J Neurol Sci. 2012;39:571–6.Google Scholar
48. Cooper, DJ, Rosenfeld, JV, Murray, L, et al. Decompressive craniectomy in diffuse traumatic brain injury. N Engl J Med. 2011;364:1493–502.Google Scholar
49. Honeybul, S, Ho, KM. The influence of clinical evidence on surgical practice. J Eval Clin Pract 2012; May 8[Epub ahead of print]. PMID:22568805 Google Scholar
50. Honeybul, S, Ho, KM, Lind, CR. What Can Be Learned from the DECRA Study. World Neurosurg. 2013;79:159–61.Google Scholar
51. Iaccarino, C, Schiavi, P, Servadei, F. Decompressive Craniectomies: Time to Discuss Not the DECR Study but the Comments to the DECRA Study. World Neurosurg. 2013;79:78–9.CrossRefGoogle Scholar
52. Hutchinson, PJ, Timofeev, I, Kolias, AG, et al. Decompressive craniectomy for traumatic brain injury: the jury is still out. Br J Neurosurg. 2011;25:441–2.Google Scholar
53. Lemcke, J. Taming tyrannosaur: the decompressive craniectomy for traumatic brain injury has to become an evidence-based procedure. Eur J Neurol. 2011;18:543–4.Google Scholar
54. Chi, JH. Craniectomy for traumatic brain injury: results from the DECRA trial. Neurosurgery. 2011;68:N19–20.Google Scholar
55. Torres, R. DECRA…Where do we go from here? Surg Neurol Int. 2012;3:54.Google Scholar
56. Kitagawa, RS, Bullock, MR. Lessons from the DECRA Study. World Neurosurg. 2013;79:82–4.Google Scholar
57. Cooper, DJ, Rosenfeld, JV, Wolfe, R. DECRA Investigators’ Response to “The Future of Decompressive Craniectomy for Diffuse Traumatic Brain Injury” by Honeybul et al. J Neurotrauma. 2012;29:2595–6.CrossRefGoogle ScholarPubMed
58. Drazen, JM. Believe the data. N Engl J Med. 2012;367:1152–3.Google Scholar
59. Evidence-Based Medicine Working Group. Evidence-based medicine. A new approach to teaching the practice of medicine. JAMA. 1992;268:2420–5.Google Scholar
60. Kahlon, G, Mansi, IA, Banks, DE. Educating medical students in evidence-based medicine: what we should expect as a starting point for our house officers. South Med J. 2012;105:184–8.Google Scholar
61. Booth, A. Evidence-based practice: triumph of style over substance? Health Info Libr J. 2011;28:237–41.Google Scholar
62. Rawlins, M. De testimonio: on the evidence for decisions about the use of therapeutic interventions. Lancet. 2008;372:2152–61.Google Scholar
63. Rawlins, MD. De Testimonio: On the evidence for decisions about the use of therapeutic interventions. London, UK: Royal College of Physicians, 2008.Google Scholar
64. Patsopoulos, NA. A pragmatic view on pragmatic trials. Dialogues Clin Neurosci. 2011;13:217–24.Google Scholar
65. Sackett, DL, Rosenberg, WM, Gray, JA, Haynes, RB, Richardson, WS. Evidence based medicine: what it is and what it isn’t. BMJ. 1996;312:71–2.Google Scholar
66. Mills, JL. Dat torturing. N Engl J Med. 1993;329:1196–9.Google Scholar
67. Greenhalgh, T. How to read a paper. Statistics for the non-statistician. II: “Significant” relations and their pitfalls. BMJ. 1997;315:422–5.Google Scholar
68. Senn, S, Julious, S. Measurement in clinical trials: a neglected issue for statisticians? Stat Med. 2009;28:3189–209.Google Scholar
69. Hartling, L, Hamm, M, Milne, A, et al. Validity and inter-rater reliability testing of quality assessment instruments. Rockville (MD): Agency for health care research and policy, US department of health and human services, 2012.Google Scholar
70. Matcham, J, Julious, S, Pyke, S, et al. Proposed best practice for statisticians in the reporting and publication of pharmaceutical industry-sponsored clinical trials. Pharm Stat. 2011;10:70–3.Google Scholar
71. Mansi, BA, Clark, J, David, FS, et al. Ten recommendations for closing the credibility gap in reporting industry-sponsored clinical research: a joint journal and pharmaceutical industry perspective. Mayo Clin Proc. 2012;87:424–9.Google Scholar
72. Drazen, JM. Transparency for Clinical Trials - The TEST Act. N Engl J Med. 2012;367(9):863–4.Google Scholar
73. Strech, D, Littmann, J. Lack of proportionality. Seven specifications of public interest that override post-approval commercial interests on limited access to clinical data. Trials. 2012;13:100.Google Scholar
74. Kesselheim, AS, Wang, B, Studdert, DM, Avorn, J. Conflict of interest reporting by authors involved in promotion of off-label drug use: an analysis of journal disclosures. PLoS Med. 2012;9:e1001280.Google Scholar
75. Crosskerry, P, Nimmo, GR. Better clinical decision making and reducing diagnostic error. J R Coll Physicians Edinb. 2011;41:155–62.Google Scholar
76. Croskerry, P, Abbass, AA, Wu, AW. How doctors feel: affective issues in patients’ safety. Lancet. 2008;372:1205–6.Google Scholar
77. Croskerry, P. Context is everything or how could I have been that stupid? Healthc Q. 2009;12 Spec No Patient:e171–6.Google Scholar
78. Croskerry, P. A universal model of diagnostic reasoning. Acad Med. 2009;84:1022–8.Google Scholar
79. Crosskerry, P. Perspectives on diagnostic failure and patient safety. Healthc Q. 2012;15 suppl:50–6.Google Scholar
80. Hill, AB. Medical ethics and controlled trials. Br Med J. 1963;1:1043–9.Google Scholar