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Editors Selection IGR 23-4

Surgical Treatment: Microhook Trabeculotomy vs. Dual Blade Goniotomy

Ronald Fellman
Davinder S. Grover

Comment by Ronald Fellman & Davinder S. Grover on:

107557 Comparison of Mid-Term Outcomes between Microhook ab Interno Trabeculotomy and Goniotomy with the Kahook Dual Blade, Okada N; Hirooka K; Onoe H et al., Journal of clinical medicine, 2023; 12:

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Comparing outcomes of two surgical procedures in a retrospective manner remains a formidable task. Propensity score matching is one statistical method to eliminate bias to have a 'best match' when comparing groups. The authors chose a genetic algorithm of propensity matching to eliminate bias to compare outcomes of microhook trabeculotomy (Tanito) to a goniotomy dual blade (KDB or Kahook dual blade). The title of the manuscript implies trabeculotomy versus goniotomy, but the nomenclature of canalbased MIGS is confusing, partly due to Current Procedural Terminology coding (CPT). The comparison is actually incise or excise the TM, different methods to reduce outflow resistance. In either event, with the propensity scoring algorithm, the authors found no statistical difference in outcomes or complications between the two groups. However, with the genetic propensity scoring method, the reader is left wondering what happened to the 50% of patients who were evaluated but excluded due to propensity matching.

The average reader may not be a statistician, (including ourselves) and would benefit from a brief explanation of how a random seed value set to 111 and a caliper coefficient set to 0.2 may potentially alter outcomes. An analysis of traditional outcomes to propensity scoring would be valuable to the surgeon.

One additional topic that is pertinent to the entire MIGS space is the health economics of MIGS and cost implications of surgical choices

One additional topic that is pertinent to the entire MIGS space is the health economics of MIGS and cost implications of surgical choices. The KDB is a disposable instrument and the Tanito blade is re-usable. This cost factor may play into a surgeon's treatment algorithm, depending on the health care system in which one operates.

Propensity matching should reduce selection bias, but the match is only as good as the variables that were studied. The authors looked at (Table 1) age, gender, type of glaucoma, preoperative IOP, no. of IOP-lowering medications and axial length. These are all very important variables. Another option would be to add two additional factors: (1) the duration of use of the antiglaucoma medication; and (2) the stage of disease. Both factors are implicated in outcome measurements. Including these variables may lead to a stratification match that may reveal valuable clinical pearls for the clinician. Only variables that are measured can be accounted for in a genetic propensity match.

The authors should be congratulated for their work that leads us all to think 'What is the optimal propensity score match for glaucoma surgical studies'? This remains to be explored and would be a meaningful exercise for national and international glaucoma societies. The authors should also be commended for performing a MIGS comparative study with two to three-year outcomes, more of which are greatly needed in this space.

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