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

Published online by Cambridge University Press:  19 April 2013

Leslie Pibouleau  and
Sylvie Chevret
Leslie Pibouleau
Affiliation:
Univ Paris Diderot, Sorbonne Paris Cité; INSERM, UMR 717; AP-HP, Hop Saint Louis, Service de Biostatistique et Information Médicale
Sylvie Chevret
Affiliation:
Univ Paris Diderot, Sorbonne Paris Cité; INSERM, UMR 717; AP-HP, Hop Saint Louis, Service de Biostatistique et Information Médicale
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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.

Keywords

Medical deviceMeta-analysisBayesianRandom-effects modelHierarchical models
Type
METHODS
Information
International Journal of Technology Assessment in Health Care , Volume 29 , Issue 2 , April 2013 , pp. 123 - 130
Copyright
Copyright © Cambridge University Press 2013

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References

REFERENCES

1.Cohen, D, Billingsley, M. Europeans are left to their own devices. BMJ. 2011;342:d2748.CrossRefGoogle ScholarPubMed
2.Curfman, GD, Redberg, RF. Medical devices–balancing regulation and innovation. N Engl J Med. 2011;365:975–977.CrossRefGoogle ScholarPubMed
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):S121–S128.CrossRefGoogle ScholarPubMed
4.Sutton, AJ, Abrams, KR. Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res. 2001;10:277–303.CrossRefGoogle ScholarPubMed
5.Pibouleau, L, Chevret, S. Bayesian statistical method was underused despite its advantages in the assessment of implantable medical devices. J Clin Epidemiol. 2010;64:270–279.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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;19:3359–3376.3.0.CO;2-N>CrossRefGoogle ScholarPubMed
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;54:1359–1367.CrossRefGoogle ScholarPubMed
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;61:460–468; discussion 468–469.CrossRefGoogle ScholarPubMed
10.Dos Santos Souza, MP, Agid, R, Willinsky, RA, et al.Microstent-assisted coiling for wide-necked aneurysms. Can J Neurol Sci. 2005;32:71–81.CrossRefGoogle Scholar
11.Gordhan, A, Invergo, D. Stent-assisted aneurysm coil embolization: Safety and efficacy at a low-volume center. Neurol Res. 2011;33:942–946.CrossRefGoogle Scholar
12.Jabbour, P, Koebbe, C, Veznedaroglu, E, Benitez, RP, Rosenwasser, R. Stent-assisted coil placement for unruptured cerebral aneurysms. Neurosurg Focus. 2004;17:E10.CrossRefGoogle ScholarPubMed
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;4:368–374.CrossRefGoogle Scholar
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;27:1123–1128.Google ScholarPubMed
15.Lee, YJ, Kim, DJ, Suh, SH, et al.Stent-assisted coil embolization of intracranial wide-necked aneurysms. Neuroradiology. 2005;47:680–689.CrossRefGoogle ScholarPubMed
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;32:721–727.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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;72:612–619.CrossRefGoogle ScholarPubMed
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;66:163–169.Google ScholarPubMed
20.Agresti, A, Coull, BA. Approximate is better than “exact” for interval estimation of binomial proportions. Am Stat. 1998;52:119–126.Google Scholar
21.Higgins, JP, Thompson, SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–1558.CrossRefGoogle ScholarPubMed
22.Smith, TC, Spiegelhalter, DJ, Thomas, A. Bayesian approaches to random-effects meta-analysis: A comparative study. Stat Med. 1995;14:2685–2699.CrossRefGoogle ScholarPubMed
23.Spiegelhalter, DJ, Abrams, KR, Myles, JP. Bayesian approaches to clinical trials and health-care evaluation. New York: Wiley; 2004.Google Scholar
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;28:115–124.CrossRefGoogle ScholarPubMed
25.Spiegelhalter, D, Best, N, Carlin, BP, Van der Linde, A. Bayesian measures of model complexity and fit. J R Statist Soc B. 2002;64:583–639.CrossRefGoogle Scholar
Supplementary material: File

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