An Evidence-Based Pathway from Functional Classification to Intraocular Lens Specialization: A Case Example Applying the PECO Framework
摘要
Simultaneous vision intraocular lenses (SVIOLs) aim to extend postoperative depth of field (DOFi) and reduce spectacle dependence after cataract or refractive lens exchange surgery. To support evidence-based selection among the growing number of SVIOL models, the predict–explore–confirm–optimize (PECO) framework is proposed as a structured SVIOL evidence development framework to guide systematic evidence generation and clinical decision-making. PECO is implemented as a sequential pathway for evidence generation, in which optical bench testing is performed first (Predict), early clinical experience is subsequently accumulated (Explore), outcomes and safety are then confirmed in large peer-reviewed clinical studies (Confirm), and patient- and procedure-specific factors are finally addressed through targeted research (Optimize). This review applies the PECO framework to a case example: the Liberty trifocal SVIOL, which has been clinically validated as a Full-DOFi Smooth SVIOL. Beyond standard safety and efficacy outcomes, evidence in the Optimization stage addresses patient expectations, dysphotopsia risk, contrast sensitivity, biometric accuracy, corneal aberrations, pupil size, centration, and posterior capsular opacification. The Liberty example illustrates how evidence extending beyond functional classification can refine patient selection, surgical planning, and counseling. Overall, the PECO framework emphasizes that optimal SVIOL outcomes depend not only on confirmed functional performance, but also on individualized, evidence-informed specialization tailored to patient characteristics and clinical context.