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Editors Selection IGR 17-4
Combined Structure and Function Measurement: SLP+SAP combined and progression
Comment by Gustavo de Moraes on:
46389 Combining Structural and Functional Measurements to Improve Detection of Glaucoma Progression using Bayesian Hierarchical Models, Medeiros FA; Leite MT; Zangwill LM et al., Investigative Ophthalmology and Visual Science, 2011; 52: 5794-5803
Technologies that measure structure or function are routinely used to diagnose and monitor glaucoma. In the past decades, extensive research has focused on the investigation and comparison of the performance of these technologies, which ultimately aimed to answer the most frequent and relevant questions in glaucoma practice. Medeiros et al. (1381) have reported the first study to describe a methodology that combines both structural and functional measurements to detect glaucoma progression. Not only has this approach helped overcome the exhaustive discussion on which technology is more accurate to detect progression, but also it minimizes the need of repeated testing to differentiate measurement variability from true glaucomatous change. Thomas Bayes was an English mathematician and priest who helped develop the statistical approach that uses 'prior' events (or information) to determine posterior probabilities. For the present study, Medeiros et al. used information provided by a given technique (i.e., standard achromatic perimetry (SAP) or scanning laser polarimetry (SLP)) to improve the reliability of the results that each of these techniques would have presented if used alone. For instance, given that SLP results suggested that structural progression occurred, SAP changes otherwise considered non-significant or borderline are now more likely to represent true functional change as well. This approach has practical applications, as clinicians are frequently uncertain about how to interpret apparently conflicting results from different tests, which may delay initiation or advancement of therapy.
Clinicians are frequently uncertain about how to interpret apparently conflicting results from different tests
The determination of the sensitivity and specificity of a give technology to detect glaucoma progression is limited by the lack of a gold standard. For the present study, the authors used masked grading of optic disc stereophotographs as reference to compare the ability of a Bayesian approach from the ordinary least square (OLS) regression approach ‐ which is commonly provided by the statistical packages inbuilt in these technologies. This innovative methodology detected more progressing eyes than OLS and revealed better performance to detect glaucoma progression based on the reference method. It is possible, however, that the use of a structural method as reference (i.e., optic disc stereophotography grading) may have favored the Bayesian approach, which by definition employs the results of another structural test (SLP) to detect progression. The combination of the two techniques may also explain the finding that the correlation between VFI and RNFL slopes was far better using the Bayesian than the conventional OLS approach. Nevertheless, these observations should not be seen as limitations as these are inherent problems of a field that lacks a gold standard. The methodology described in the present paper is the first step towards the development of a benchmark criterion to define glaucoma progression, which should facilitate future research aimed to investigate therapeutic options to prevent vision loss due to glaucoma. The next step could be the application of Bayesian hierarchical models to improve the detection of glaucoma progression not only using global indices (as reported in this paper) but also employing topographic information to detect localized progression.
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