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W. J. Foster, W. Tufail, A. M. Issa; Quality of Pharmacoeconomic Analyses of Macular Degeneration Therapies. Invest. Ophthalmol. Vis. Sci. 2008;49(13):4997. doi: https://doi.org/.
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To determine whether sufficient quality evidence exists regarding economic evaluations of therapeutics for age-related macular degeneration (AMD), and to identify predictors of study quality.
We conducted a systematic search of the literature, and performed database searches for economic studies of AMD therapeutics published since January 1990. We used the Quality of Health Economic Studies scale, a validated rating scale to grade articles that met our eligibility criteria. We performed regression analyses for predictors of quality.
Our initial evaluation yielded 90 articles. Of these, only 23 articles met our inclusion criteria for original papers that were determined to be comparative economic evaluations. The mean quality rating overall was 61.6, with quality scores ranging from 18 to 92. There was a higher mean evaluation score in the studies designed as clinical trials vs. observational type designed studies (mean = 74.7(11.4), 52.6(16.5) respectively, p=.002). Papers in which the statistical analyses were clearly presented had a higher mean evaluation score than papers in which the statistical analyses was not so clear (mean = 74.3(12.3), 53.1(16.1) respectively, p=.004). A general linear model was fitted using those independent variables which were significantly associated with evaluation score. The variables "type of study" and "statistics presented clearly" were found to be jointly significant in the model and explained nearly 70% of the variation in the dependent variable (R2=.68).
As far as we know, this was the first study to assess the quality of the evidence of pharmacoeconomic studies of AMD. Our analysis reveals that less than one quarter of AMD therapeutic economic studies meet criteria for high quality as assessed by a validated instrument. Future pharmacoeconomic analyses of AMD therapeutics should use consistent, standardized outcome measures so that policy makers can more accurately use these studies to make reimbursement and other decisions.
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