Literature DB >> 10345156

The use of meta-analysis in cost-effectiveness analysis. Issues and recommendations.

S Saint1, D L Veenstra, S D Sullivan.   

Abstract

Meta-analysis is used to statistically pool the results from individual studies, usually randomised trials, to obtain an estimate of the summary effect size across studies. The summary measure from a meta-analysis is often used to derive the probability of treatment success in a cost-effectiveness analysis. Recently, LeLorier and colleagues questioned the ability of meta-analysis to accurately predict the results of a subsequent large-scale trial, implying that the use of a summary measure from a meta-analysis may be inappropriate in an economic evaluation. We comment on this potential shortcoming by first providing an outline of the use of meta-analysis results in a cost-effectiveness analysis. Then, using examples of discrepancies between meta-analyses and subsequent large trials noted by LeLorier and colleagues, we examine the potential impact of using the results from a small trial versus a meta-analysis. We found that the meta-analyses were comparable to or better than small trials at predicting the results of subsequent large trials. We, therefore, argue that a meta-analysis of homogeneous studies can provide a reasonable estimate of the treatment effect for use in a cost-effectiveness analysis when no large, definitive clinical trial has been performed. However, care must be taken not to over-interpret the precision of the estimate, since both the homogeneity and quality of the primary studies need to be considered. We conclude by providing guidance on the appropriate use of summary measures derived from meta-analyses for cost-effectiveness studies.

Mesh:

Year:  1999        PMID: 10345156     DOI: 10.2165/00019053-199915010-00001

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  36 in total

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Journal:  J Clin Epidemiol       Date:  1995-01       Impact factor: 6.437

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Authors:  A Liberati
Journal:  J Clin Epidemiol       Date:  1995-01       Impact factor: 6.437

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Journal:  Lancet       Date:  1995-03-25       Impact factor: 79.321

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Journal:  Lancet       Date:  1994-05-07       Impact factor: 79.321

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Authors:  S Yusuf; R Collins; S MacMahon; R Peto
Journal:  Lancet       Date:  1988-05-14       Impact factor: 79.321

10.  Doppler ultrasound and aspirin in recognition and prevention of pregnancy-induced hypertension.

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Journal:  Lancet       Date:  1990-06-30       Impact factor: 79.321

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  2 in total

Review 1.  Targeting Health Behaviors to Reduce Health Care Costs in Pediatric Psychology: Descriptive Review and Recommendations.

Authors:  Meghan E McGrady; Kevin A Hommel
Journal:  J Pediatr Psychol       Date:  2015-09-10

2.  Difference in Restricted Mean Survival Time for Cost-Effectiveness Analysis Using Individual Patient Data Meta-Analysis: Evidence from a Case Study.

Authors:  Béranger Lueza; Audrey Mauguen; Jean-Pierre Pignon; Oliver Rivero-Arias; Julia Bonastre
Journal:  PLoS One       Date:  2016-03-09       Impact factor: 3.240

  2 in total

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