Application of a Partial Least Squares Regression Algorithm for Posterior Chamber Phakic Intraocular Lens Sizing and Postoperative Vault Prediction.

PURPOSE: To develop and validate a new algorithm for predicting the postoperative vault of the myopic EVO Visian Implantable Collamer Lens (ICL) V4c (STAAR Surgical AG). METHODS: This study included 81 eyes of 43 patients who had undergone ICL implantation. Preoperative data obtained by swept-source optical coherence tomography, Scheimpflug camera, and anterior segment optical coherence tomography were applied to develop a new partial least squares (PLS) regression algorithm. ICL sizing was performed using the standard white-to-white method with the online calculation and ordering system. The postoperative vault was assessed based on anterior segment optical coherence tomography. The PLS approach was applied to create the calibration model for predicting the postoperative vault. The new PLS model was cross-validated using the leave-one-out method and compared to a recently published linear regression model. Agreement between the actual and predicted vault values for the two methods was assessed by the Bland-Altman method. RESULTS: There was a statistically significant correlation (P < .001, r = 0.73) between the postoperative vault values and those predicted by the PLS algorithm. Validation of the PLS model yielded lower mean differences and limits of agreement (0 and 410 µm, respectively) than the linear regression method (400 and 750 µm, respectively). CONCLUSIONS: The PLS algorithm increases the precision of ICL vault prediction. However, it shows a tendency to overestimate small vault values and underestimate high vaults. [J Refract Surg. 2020;36(9):606-612.].