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Combining OCT parameters improves glaucoma detection
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Researchers have found that the retinal ganglion cell-inner plexiform and retinal nerve fiber layer parameters of optical coherence tomography had similar diagnostic value, while combining the two increased that value.
Larrosa and colleagues, as reported in Investigative Ophthalmology and Visual Science, aimed to develop a predictive model to detect glaucoma. They included 500 eyes in the study group and 187 in the validation group. Those with glaucoma were organized into five groups depending on their visual field damage.
“The combined model includes information from eight parameters from three structures: optic nerve head, peripapillary retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiforms (GCIPLs), and requires only 1 minute to determine the probability of glaucoma in a suspected patient using the diagnostic calculator,” the researchers said.
Larrosa and colleagues found that the best parameters were: inferior RNFL, average RNFL, vertical cup-to-disc ratio, minimal GCIPL and inferior-temporal GCIPL.
They explained that the areas under the receiver operating characteristic curves (AUC) were used to determine the discriminatory capabilities between healthy and glaucomatous eyes. They found that the highest AUC was in the combined predictive model and was significantly higher than the other isolated parameters considered in early and advanced glaucoma.
The combined predictive formula improved glaucoma detection vs. the best isolated parameters, according to researchers. – by Abigail Sutton
Disclosure: The researchers reported no relevant financial disclosures.
Perspective
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Carl H. Jacobsen, OD, FAAO
Full disclosure: I am not a big fan of glaucoma risk calculators and I do not use them in my practice. Although some find the specific probability percentages helpful in establishing risk and making an initial treatment decision, I find my patients’ eyes glaze over as I review these numbers.
In the end, I usually classify patient risk as low, moderate or high based on their personal data and my clinical experience and treat/monitor accordingly. Ultimately, careful characterization and monitoring will establish an individual’s rate of change and, hence, their risk of sight loss based on their personal data, not the combined data of many.
Having said that, I am happy that Larrosa and colleagues have produced an updated risk calculator. For those who enjoy using them, this study introduces a more accurate way of determining risk by incorporating SD-OCT data. Additionally, they have found that incorporating ganglion cell, nerve fiber layer and disc parameter data together improves the predictability of their calculator.
Similarly, in practice we need to consider all available metrics in order to provide the best glaucoma care, regardless of whether or not you choose to use a risk calculator.
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