The following is a summary of “Performance evaluation of a simple strategy to optimize formula constants for zero mean or minimal standard deviation or RMS prediction error in intraocular lens power calculation,” published in the September 2024 issue of Ophthalmology by Langenbucher et al.
Researchers conducted a retrospective study to investigate the performance of a simple prediction scheme for formula constants optimized for mean (MPE), standard deviation (SDPE), or root-mean-squared refractive prediction error (RMSPE).
They used IOLMaster 700 biometric data from 888 eyes with Hoya Vivinex lenses and 821 with Alcon SA60AT lenses, implanted lens power, and postoperative spherical equivalent refraction. Optimized constants for SRKT, Hoffer Q, Holladay 1, Haigis, and K6 formulae were calculated using iterative nonlinear optimization for zero MPE and minimal SDPE and RMSPE. Start values were adjusted by ±1.5 from the MPE-optimized constants, and formula constants generated using the simple prediction scheme were compared to directly optimized constants.
The results showed all 5 formulae under test, and with both datasets, constants optimized using the simple scheme showed excellent agreement with those from the iterative method with either MPE or RMSPE used as the optimization metric and good agreement with SDPE as the metric. Constants optimized for zero MPE or minimal RMSPE agreed within 0.05. Meanwhile, constants for minimal SDPE could be systematically off by up to 0.6 from the MPE values, making SDPE unsuitable as an optimization metric.
They concluded the simple formula constant optimization scheme performed excellently for 4 disclosed formulae and one non-disclosed formula in our 2 monocentric datasets with zero MPE or minimal RMSPE as metrics. Multicentric studies with other study populations and biometers are required to investigate further.
Source: ajo.com/article/S0002-9394(24)00415-X/abstract
