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Evidence in Neurosurgery: Perspectives

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Abstract

The previous chapters of this book have shown that becoming an evidence-based neurosurgeon is not a simple task. Both the editors and the authors have tried to take the next step in the synthesis of higher-level evidence for practicing neurosurgeons. The chapters are organized around common clinical scenarios taken from real-life experience. The results show that some scenarios are more common and subsequently comprise more high quality evidence, whereas others are extremely rare resulting on only a few retrospective case series. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) was used in this book for grading the quality of evidence [1]. GRADE provides a comprehensive framework for evaluation of the quality of evidence in systematic reviews and clinical guidelines, succeeding the hierarchical levels of evidence classification system which has been widely used for the past decades [2].

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References

  1. Guyatt G, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64(4):383–94.

    Article  PubMed  Google Scholar 

  2. The periodic health examination. Canadian task force on the periodic health examination. Can Med Assoc J. 1979;121(9):1193–254.

    Google Scholar 

  3. Martens J, et al. Importance and presence of high-quality evidence for clinical decisions in neurosurgery: international survey of neurosurgeons. Interact J Med Res. 2018;7(2):e16.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Mansouri A, et al. Randomized controlled trials and neurosurgery: the ideal fit or should alternative methodologies be considered? J Neurosurg. 2016;124(2):558–68.

    Article  PubMed  Google Scholar 

  5. Turk AS 3rd, et al. Flow diversion versus traditional endovascular coiling therapy: design of the prospective LARGE aneurysm randomized trial. AJNR Am J Neuroradiol. 2014;35(7):1341–5.

    Article  PubMed  PubMed Central  Google Scholar 

  6. London AJ. Equipoise in research: integrating ethics and science in human research. JAMA. 2017;317(5):525–6.

    Article  PubMed  Google Scholar 

  7. Freedman B. Equipoise and the ethics of clinical research. N Engl J Med. 1987;317(3):141–5.

    Article  CAS  PubMed  Google Scholar 

  8. Bothwell LE, et al. Assessing the gold standard—lessons from the history of RCTs. N Engl J Med. 2016;374(22):2175–81.

    Article  CAS  PubMed  Google Scholar 

  9. Ingelfinger FJ. The randomized clinical trial. N Engl J Med. 1972;287(2):100–1.

    Article  CAS  PubMed  Google Scholar 

  10. Armitage P. Fisher, Bradford Hill, and randomization. Int J Epidemiol. 2003;32(6):925–8.

    Article  PubMed  Google Scholar 

  11. Jones DS, Podolsky SH. The history and fate of the gold standard. Lancet. 2015;385(9977):1502–3.

    Article  PubMed  Google Scholar 

  12. Liu JM, et al. Parent artery reconstruction for large or giant cerebral aneurysms using the tubridge flow diverter: a multicenter, randomized, controlled clinical trial (PARAT). AJNR Am J Neuroradiol. 2018;39(5):807–16.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Raymond J, et al. Flow diversion in the treatment of aneurysms: a randomized care trial and registry. J Neurosurg. 2017;127(3):454–62.

    Article  PubMed  Google Scholar 

  14. Raymond J. DIVERT: Diversion of Flow in Intracranial VErtebral and Blood Blister-like Ruptured Aneurysms Trial: a randomized trial comparing pipeline flow diversion and best-standard-treatment (DIVERT). Bethesda: ClinicalTrials.gov NCT01976026; 2013.

    Google Scholar 

  15. Turjman F, et al. EVIDENCE trial: design of a phase 2, randomized, controlled, multicenter study comparing flow diversion and traditional endovascular strategy in unruptured saccular wide-necked intracranial aneurysms. Neuroradiology. 2015;57(1):49–54.

    Article  PubMed  Google Scholar 

  16. Moret J. Efficacy trial of intracranial aneurysm treatment using two different endovascular techniques. 2010. Available from: https://clinicaltrials.gov/ct2/show/NCT01084681?term=marco+polo&rank=1.

  17. Speich B, et al. Systematic review on costs and resource use of randomized clinical trials shows a lack of transparent and comprehensive data. J Clin Epidemiol. 2018;96:1–11.

    Article  PubMed  Google Scholar 

  18. Berndt ER, Cockburn I, the National Bureau of Economic Research. Price indexes for clinical trial research: a feasibility study. Cambridge: NBER; 2013.

    Book  Google Scholar 

  19. Wilson-Kovacs D. When experiments travel: clinical trials and the global search for human subjects Adriana Petryna, Princeton University Press, 2009. Geno Society Policy. 2009;5(2):84.

    Article  Google Scholar 

  20. Scannell J. Four reasons drugs are expensive, of which two are false. Forbes.com. 2015 October 13.

    Google Scholar 

  21. Frieden TR. Evidence for health decision making—beyond randomized, controlled trials. N Engl J Med. 2017;377(5):465–75.

    Article  PubMed  Google Scholar 

  22. Love JW. Drugs and operations: some important differences. JAMA. 1975;232(1):37–8.

    Article  CAS  PubMed  Google Scholar 

  23. Ergina PL, et al. Challenges in evaluating surgical innovation. Lancet. 2009;374(9695):1097–104.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Blencowe NS, et al. Interventions in randomised controlled trials in surgery: issues to consider during trial design. Trials. 2015;16:392.

    Article  PubMed  PubMed Central  Google Scholar 

  25. McCulloch P, et al. Tolerance of uncertainty, extroversion, neuroticism and attitudes to randomized controlled trials among surgeons and physicians. Br J Surg. 2005;92(10):1293–7.

    Article  CAS  PubMed  Google Scholar 

  26. Ford I, Norrie J. Pragmatic trials. N Engl J Med. 2016;375(5):454–63.

    Article  PubMed  Google Scholar 

  27. Boutron I, et al. CONSORT statement for randomized trials of nonpharmacologic treatments: a 2017 update and a CONSORT extension for nonpharmacologic trial abstracts. Ann Intern Med. 2017;167(1):40–7.

    Article  PubMed  Google Scholar 

  28. Boutron I, et al. Extending the CONSORT statement to randomized trials of nonpharmacologic treatment: explanation and elaboration. Ann Intern Med. 2008;148(4):295–309.

    Article  PubMed  Google Scholar 

  29. Ramsay CR, et al. Statistical assessment of the learning curves of health technologies. Health Technol Assess. 2001;5(12):1–79.

    Article  CAS  PubMed  Google Scholar 

  30. Oltean H, Gagnier JJ. Use of clustering analysis in randomized controlled trials in orthopaedic surgery. BMC Med Res Methodol. 2015;15:17.

    Article  PubMed  PubMed Central  Google Scholar 

  31. ICH Harmonised Tripartite Guideline. Statistical principles for clinical trials. International Conference on Harmonisation E9 Expert Working Group. Stat Med. 1999;18(15):1905–42.

    Google Scholar 

  32. Conroy EJ, et al. Randomized trials involving surgery did not routinely report considerations of learning and clustering effects. J Clin Epidemiol. 2019;107:27–35.

    Article  PubMed  Google Scholar 

  33. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutical trials. J Chronic Dis. 1967;20(8):637–48.

    Article  CAS  PubMed  Google Scholar 

  34. Groenwold RHH, Dekkers OM. Designing pragmatic trials-what can we learn from lessons learned? J Clin Epidemiol. 2017;90:3–5.

    Article  PubMed  Google Scholar 

  35. Sox HC, Lewis RJ. Pragmatic trials: practical answers to “real world” questions. JAMA. 2016;316(11):1205–6.

    Article  PubMed  Google Scholar 

  36. Hutchinson PJ, et al. Trial of decompressive craniectomy for traumatic intracranial hypertension. N Engl J Med. 2016;375(12):1119–30.

    Article  PubMed  Google Scholar 

  37. Zwarenstein M, et al. Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ. 2008;337:a2390.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Loudon K, et al. The PRECIS-2 tool: designing trials that are fit for purpose. BMJ. 2015;350:h2147.

    Article  PubMed  Google Scholar 

  39. Fiore LD, Lavori PW. Integrating randomized comparative effectiveness research with patient care. N Engl J Med. 2016;374(22):2152–8.

    Article  CAS  PubMed  Google Scholar 

  40. Mosis G, et al. A randomized database study in general practice yielded quality data but patient recruitment in routine consultation was not practical. J Clin Epidemiol. 2006;59(5):497–502.

    Article  PubMed  Google Scholar 

  41. Feudtner C, Schreiner M, Lantos JD. Risks (and benefits) in comparative effectiveness research trials. N Engl J Med. 2013;369(10):892–4.

    Article  CAS  PubMed  Google Scholar 

  42. Pallmann P, et al. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med. 2018;16(1):29.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Thorlund K, et al. Key design considerations for adaptive clinical trials: a primer for clinicians. BMJ. 2018;360:k698.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Bhatt DL, Mehta C. Adaptive designs for clinical trials. N Engl J Med. 2016;375(1):65–74.

    Article  PubMed  Google Scholar 

  45. Bauer P, Koenig F. The reassessment of trial perspectives from interim data--a critical view. Stat Med. 2006;25(1):23–36.

    Article  PubMed  Google Scholar 

  46. Ning J, Huang X. Response-adaptive randomization for clinical trials with adjustment for covariate imbalance. Stat Med. 2010;29(17):1761–8.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Mathes T, et al. Registry-based randomized controlled trials merged the strength of randomized controlled trails and observational studies and give rise to more pragmatic trials. J Clin Epidemiol. 2018;93:120–7.

    Article  PubMed  Google Scholar 

  48. Sherman RE, et al. Real-world evidence—what is it and what can it tell us? N Engl J Med. 2016;375(23):2293–7.

    Article  PubMed  Google Scholar 

  49. AHRQ. AHRQ methods for effective health care. In: Gliklich RE, Dreyer NA, Leavy MB, editors. Registries for evaluating patient outcomes: a user’s guide. Rockville: Agency for Healthcare Research and Quality; 2014.

    Google Scholar 

  50. Li G, et al. Registry-based randomized controlled trials- what are the advantages, challenges, and areas for future research? J Clin Epidemiol. 2016;80:16–24.

    Article  PubMed  Google Scholar 

  51. Pieper DA, Neugebauer EA. Learning curve effects can be investigated with the randomized registry trial. J Clin Epidemiol. 2015;68(10):1242–3.

    Article  PubMed  Google Scholar 

  52. Haneuse S, VanderWeele TJ, Arterburn D. Using the e-value to assess the potential effect of unmeasured confounding in observational studies. JAMA. 2019;321(6):602–3.

    Article  PubMed  Google Scholar 

  53. Haukoos JS, Lewis RJ. The propensity score. JAMA. 2015;314(15):1637–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. James S, Rao SV, Granger CB. Registry-based randomized clinical trials—a new clinical trial paradigm. Nat Rev Cardiol. 2015;12:312.

    Article  PubMed  Google Scholar 

  55. Fröbert O, et al. Thrombus aspiration during ST-segment elevation myocardial infarction. N Engl J Med. 2013;369(17):1587–97.

    Article  PubMed  CAS  Google Scholar 

  56. Thuesen L, et al. Event detection using population-based health care databases in randomized clinical trials: a novel research tool in interventional cardiology. Clin Epidemiol. 2013;5:357.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Wasserstein RL, Lazar NA. The ASA’s statement on p-values: context, process, and purpose. Am Stat. 2016;70(2):129–33.

    Article  Google Scholar 

  58. Ioannidis JPA. Why most published research findings are false. PLoS Med. 2005;2(8):e124.

    Article  PubMed  PubMed Central  Google Scholar 

  59. McGlothlin AE, Lewis RJ. Minimal clinically important difference: defining what really matters to patients. JAMA. 2014;312(13):1342–3.

    Article  CAS  PubMed  Google Scholar 

  60. Zannikos S, Lee L, Smith HE. Minimum clinically important difference and substantial clinical benefit: does one size fit all diagnoses and patients? Semin Spine Surg. 2014;26(1):8–11.

    Article  Google Scholar 

  61. Jaeschke R, Singer J, Guyatt GH. Measurement of health status: ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10(4):407–15.

    Article  CAS  PubMed  Google Scholar 

  62. Glassman SD, et al. Defining substantial clinical benefit following lumbar spine arthrodesis. JBJS. 2008;90(9):1839–47.

    Article  Google Scholar 

  63. Bigirumurame T, Kasim AS. Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review. BMC Res Notes. 2017;10(1):775.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Larson CM. Editorial commentary: patient-related outcome measures, minimal clinically important differences, and substantial clinical benefits for adolescent hip arthroscopy: making progress with outcome measures or unquestionably spinning out of control? Arthroscopy. 2017;33(10):1819–20.

    Article  PubMed  Google Scholar 

  65. Reddy VK, et al. Microvascular decompression for classic trigeminal neuralgia: determination of minimum clinically important difference in pain improvement for patient reported outcomes. Neurosurgery. 2013;72(5):749–54; discussion 754.

    Article  PubMed  Google Scholar 

  66. PROMIS (patient-reported outcomes measurement information system). Available from: http://www.healthmeasures.net/index.php?option=com_content&view=category&layout=blog&id=147&Itemid=806.

  67. Core outcome measures in effectiveness trials. Available from: http://www.comet-initiative.org/.

  68. Patient-centered outcomes research institute. Available from: https://www.pcori.org/.

  69. Elwyn G, et al. A three-talk model for shared decision making: multistage consultation process. BMJ. 2017;359:j4891.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Stacey D, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;(1):Cd001431.

    Google Scholar 

  71. Wennberg DE, et al. A randomized trial of a telephone care-management strategy. N Engl J Med. 2010;363(13):1245–55.

    Article  CAS  PubMed  Google Scholar 

  72. Mulley AG, Trimble C, Elwyn G. Stop the silent misdiagnosis: patients’ preferences matter. BMJ. 2012;345:e6572.

    Article  PubMed  Google Scholar 

  73. Scheunemann LP, et al. How clinicians discuss critically ill patients’ preferences and values with surrogates: an empirical analysis. Crit Care Med. 2015;43(4):757–64.

    Article  PubMed  PubMed Central  Google Scholar 

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Correspondence to Ronald H. M. A. Bartels .

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Shimanskaya, V., Martens, J., Boogaarts, J., Westert, G.P., Rovers, M.M., Bartels, R.H.M.A. (2019). Evidence in Neurosurgery: Perspectives. In: Bartels, R., Rovers, M., Westert, G. (eds) Evidence for Neurosurgery. Springer, Cham. https://doi.org/10.1007/978-3-030-16323-5_22

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  • DOI: https://doi.org/10.1007/978-3-030-16323-5_22

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