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BAYESIAN HIERARCHICAL META-ANALYSIS MODEL FOR MEDICAL DEVICE EVALUATION: APPLICATION TO INTRACRANIAL STENTS

  • Leslie Pibouleau (a1) and Sylvie Chevret (a1)
Abstract

Objectives: The aim of this study was to propose a statistical model that takes into account clinical data on earlier versions when evaluating the latest version of an implantable medical device (IMD).

Methods: We compared the performances of a Bayesian three-level hierarchical meta-analysis model with those of a Bayesian random-effects model through a simulation study. Posterior mean estimates of the success rate for each IMD version were computed as well as the probability that the latest version improved in effectiveness. Models were compared using the Deviance Information Criterion (DIC), the estimated bias and the standard deviation of the mean success rates. Sensitivity analyses to the choice of the priors were performed. These methods were applied to the evaluation of an intracranial stent used to treat wide-necked aneurysms.

Results: When IMD versions did not differ in effectiveness, the best-fitting model was the random-effects model. By contrast, when there was a version effect, the hierarchical model was selected in more than 95 percent of the cases. It provided precise estimations of success rates of each IMD version and allowed detecting an improvement in effectiveness of the latest version, with a low influence of the choice of the priors. No evidence of benefit from the latest version of the intracranial stent was found.

Conclusions: In the setting of IMD assessment, comparison of DIC between the two proposed models appeared useful for detecting version effects. In that case, Bayesian hierarchical meta-analysis model may help the decision maker by providing useful information on the latest version of IMD compared with the previous versions.

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References
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1.Cohen D, Billingsley M. Europeans are left to their own devices. BMJ. 2011;342:d2748.
2.Curfman GD, Redberg RF. Medical devices–balancing regulation and innovation. N Engl J Med. 2011;365:975977.
3.Sedrakyan A, Marinac-Dabic D, Normand SL, Mushlin A, Gross T. A framework for evidence evaluation and methodological issues in implantable device studies. Med Care. 2010;48 (Suppl):S121S128.
4.Sutton AJ, Abrams KR. Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res. 2001;10:277303.
5.Pibouleau L, Chevret S. Bayesian statistical method was underused despite its advantages in the assessment of implantable medical devices. J Clin Epidemiol. 2010;64:270279.
6.McCarron CE, Pullenayegum EM, Thabane L, Goeree R, Tarride JE. The importance of adjusting for potential confounders in Bayesian hierarchical models synthesising evidence from randomised and non-randomised studies: An application comparing treatments for abdominal aortic aneurysms. BMC Med Res Methodol. 2010;10:64.
7.Prevost TC, Abrams KR, Jones DR. Hierarchical models in generalized synthesis of evidence: An example based on studies of breast cancer screening. Stat Med. 2000;19:33593376.
8.Benitez RP, Silva MT, Klem J, Veznedaroglu E, Rosenwasser RH. Endovascular occlusion of wide-necked aneurysms with a new intracranial microstent (Neuroform) and detachable coils. Neurosurgery. 2004;54:13591367.
9.Biondi A, Janardhan V, Katz JM, et al.Neuroform stent-assisted coil embolization of wide-neck intracranial aneurysms: Strategies in stent deployment and midterm follow-up. Neurosurgery. 2007;61:460468; discussion 468–469.
10.Dos Santos Souza MP, Agid R, Willinsky RA, et al.Microstent-assisted coiling for wide-necked aneurysms. Can J Neurol Sci. 2005;32:7181.
11.Gordhan A, Invergo D. Stent-assisted aneurysm coil embolization: Safety and efficacy at a low-volume center. Neurol Res. 2011;33:942946.
12.Jabbour P, Koebbe C, Veznedaroglu E, Benitez RP, Rosenwasser R. Stent-assisted coil placement for unruptured cerebral aneurysms. Neurosurg Focus. 2004;17:E10.
13.Kadkhodayan Y, Somogyi CT, Cross DT III, et al.Technical, angiographic and clinical outcomes of Neuroform 1, 2, 2 Treo and 3 devices in stent-assisted coiling of intracranial aneurysms. J Neurointerv Surg. 2012;4:368374.
14.Katsaridis V, Papagiannaki C, Violaris C. Embolization of acutely ruptured and unruptured wide-necked cerebral aneurysms using the neuroform2 stent without pretreatment with antiplatelets: A single center experience. AJNR Am J Neuroradiol. 2006;27:11231128.
15.Lee YJ, Kim DJ, Suh SH, et al.Stent-assisted coil embolization of intracranial wide-necked aneurysms. Neuroradiology. 2005;47:680689.
16.Liang G, Gao X, Li Z, Wei X, Xue H. Neuroform stent-assisted coiling of intracranial aneurysms: A 5 year single-center experience and follow-up. Neurol Res. 2010;32:721727.
17.Sani S, Jobe KW, Lopes DK. Treatment of wide-necked cerebral aneurysms with the Neuroform2 Treo stent. A prospective 6-month study. Neurosurg Focus. 2005;18:E4.
18.Wajnberg E, de Souza JM, Marchiori E, Gasparetto EL. Single-center experience with the Neuroform stent for endovascular treatment of wide-necked intracranial aneurysms. Surg Neurol. 2009;72:612619.
19.Wanke I, Doerfler A, Goericke S, et al.Treatment of wide-necked intracranial aneurysms with a self-expanding stent: Mid-term results. Zentralbl Neurochir. 2005;66:163169.
20.Agresti A, Coull BA. Approximate is better than “exact” for interval estimation of binomial proportions. Am Stat. 1998;52:119126.
21.Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:15391558.
22.Smith TC, Spiegelhalter DJ, Thomas A. Bayesian approaches to random-effects meta-analysis: A comparative study. Stat Med. 1995;14:26852699.
23.Spiegelhalter DJ, Abrams KR, Myles JP. Bayesian approaches to clinical trials and health-care evaluation. New York: Wiley; 2004.
24.Youn JH, Lord J, Hemming K, et al.Bayesian meta-analysis on medical devices: Application to implantable cardioverter defibrillators. Int J Technol Assess Health Care. 2012;28:115124.
25.Spiegelhalter D, Best N, Carlin BP, Van der Linde A. Bayesian measures of model complexity and fit. J R Statist Soc B. 2002;64:583639.
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International Journal of Technology Assessment in Health Care
  • ISSN: 0266-4623
  • EISSN: 1471-6348
  • URL: /core/journals/international-journal-of-technology-assessment-in-health-care
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