Accuracy of 8 Modern Intraocular Lens Power Calculation Formulas in Asian Eyes With Axial Length ≥ 32.00 mm.

Abstract

To compare the accuracy of 8 modern intraocular lens (IOL) power calculation formulas in Asian eyes with axial length (AL) ≥32.00 mm. Retrospective observational study to compare IOL power calculation formulas. A total of 330 eyes from 330 Asian cataract patients with AL ≥ 32.00 mm were included. Eyes with previous ocular surgery, vision-threatening corneal disease, or surgical complications were excluded. The accuracy of eight formulas was evaluated: Barrett Universal II, Cooke K6, EVO 2.0, Hill-RBF 3.0, Kane, Pearl-DGS, Hoffer QST, and Zhu-Lu. To minimize systematic refractive bias, prediction error (PE) values were arithmetically adjusted to zero the mean PE for each formula and each IOL model. Due to the 35.00 mm AL input limit of Hill-RBF and Kane, refractive outcomes were analyzed separately in the Main Group (32.00 mm ≤ AL < 35.00 mm, n = 307) and Ultra-Long Group (AL ≥ 35.00 mm, n = 23). The correlation between PE and AL was also assessed. Root mean square absolute error (RMSAE), median absolute error (MedAE), and percentages of eyes with prediction error within ±0.50 D. In the Main Group, Zhu-Lu showed the lowest RMSAE (0.562 D), with Cooke K6 ranking closely behind (0.563 D). Cooke K6 achieved the lowest MedAE (0.271 D), followed by EVO and Pearl-DGS (both 0.272 D). Pearl-DGS had the highest proportion of eyes within ±0.50 D (75.24%), whereas Zhu-Lu had the highest proportion within ±1.00 D (93.49%). Hoffer QST had the highest RMSAE (0.682 D), the highest MedAE (0.369 D), and the lowest proportion within ±0.50 D (61.89%). In the small Ultra-Long Group, Zhu-Lu yielded the lowest RMSAE (0.438 D) and the highest proportion within ±0.50 D (78.26%), whereas Cooke K6 had the lowest MedAE (0.281 D). Hoffer QST again showed the greatest hyperopic drift with increasing AL. In eyes with AL ≥ 32.00 mm, modern formulas showed distinct differences in predictive accuracy. Based on an integrated assessment across multiple accuracy metrics, Cooke K6, EVO, Pearl-DGS, and Zhu-Lu are clinically preferable options for this specific population, although their relative strengths differ across endpoints.