Global consensus on the evidence-based functional classification of simultaneous vision IOLs

激光矫视 验光服务 一致性(知识库) 医学 白内障手术 人工晶状体 眼科 人工晶状体 生活质量(医疗保健) 镜头(地质) 质量(理念) 折射误差 超声乳化术 人眼 梅德林 医学物理学
作者
Joaquín Fernández,Douglas D. Koch,Graham D. Barrett,Newton Avelino de Andrade,Filomena Ribeiro,Functional Vision Working Group
出处
期刊:Journal of Cataract and Refractive Surgery [Lippincott Williams & Wilkins]
卷期号:52 (3): 219-222 被引量:3
标识
DOI:10.1097/j.jcrs.0000000000001880
摘要

In a landscape defined by the rapid and sustained proliferation of intraocular lens (IOL) models after the first IOL introduced by Sir Harold Ridley in 1949, alongside a growing volume of clinical studies providing evidence of their functional benefits, the need for a unified, comprehensive, and internationally standardized Functional Vision Framework for both Functional Classification and the consistent measurement and reporting of clinical outcomes has become a matter of great importance.1 The European Society of Cataract and Refractive Surgeons (ESCRS), the American Society of Cataract and Refractive Surgery (ASCRS), the Asia-Pacific Association of Cataract and Refractive Surgeons (APACRS), and the Latin American Society of Cataract and Refractive Surgery (LATAMSCRS) have collectively propelled the evolution of the Functional Vision Framework, advancing them beyond the limitations of purely optical design. Their work emphasizes clinically meaningful outcomes that more accurately reflect patients' daily visual performance and overall quality of life. The ESCRS proposal for a Functional Classification based on the range of the depth of field (ROF), the ASCRS recommendations to use the term “depth of field” with the abbreviation DOFi in lieu of “range of the depth of field” with the abbreviation ROF, and to adopt the Assessment of IntraOcular Implant Symptoms (AIOLIS) questionnaire, a tool developed by the American Academy of Ophthalmology (AAO) to enhance consistency in postoperative symptom assessment, and APACRS and LATAMSCRS's emphasis on the role of optical bench data during early stages of evaluation were all highlighted during the Functional Vision Working Group (FVWG) meeting at the 43rd Congress of the ESCRS in Copenhagen, Denmark, in September 2025.2,3 Recognizing the overlap in objectives and the need for harmonization, ESCRS, ASCRS, APACRS, and LATAMSCRS established the Global Functional Vision Working Group (FVWG). Its goal is to set a global standard for evidence-based knowledge generation in IOL research and clinical practice. Functional Classification Terminology and Aims The Functional Classification of IOLs is based on the ROF and the enhancement of visual acuity from intermediate to near distances. However, based on commentary by Riaz et al., the FVWG agreed that the abbreviation ROF could be confused with peripheral visual field terminology.4 As a result, we recommend using depth of field (DOFi) exclusively because it promotes clearer and more consistent communication among clinicians and researchers (Figure 1).Figure 1.: Updated diagram of Functional Classification depending on (1) the DOFi achieved in the monocular defocus curve with best correction at distance at 0.2 logMAR VA level and (2) the improvement of VA from intermediate to near (ΔVA).2 DOFi = depth of fieldAlthough the number of categories and cutoffs derived from a synthesis of current evidence remains at 6, the FVWG agreed to rename them as follows: Partial-DOFi Narrowed, Enhanced, and Extended; and Full-DOFi Steep, Smooth, and Continuous. Members also agreed to order the subcategories according to the functional benefits they provide to patients. Although 1.1.—Narrowed, 1.2.—Enhanced, and 1.3.—Extended reflect a progressive increase in DOFi accompanied by a gradual compromise in far distance visual quality, the 2.1.—Steep, 2.2.—Smooth, and 2.3.—Continuous categories represent a progressive enhancement in intermediate visual performance, which may be associated with a corresponding progressive reduction in near visual quality (Table 1; Figure 2).2,5 Table 1. - Functional classification of IOLs by depth and shape of defocus curves (normalized to 0 logMAR at best distance correction) DOFi for 0.2 logMAR (Diopters, D) DOFi for 0.3 logMAR (Diopters, D) ΔVA (logMAR) 1. PARTIAL-DOFi <2.3 <2.75 0 1.1. Narrowed <1.2 <1.61 0 1.2. Enhanced ≥1.2 and <1.58 ≥1.61 and <1.98 0 1.3. Extended ≥1.58 and <2.3 ≥1.98 and <2.75 0 2. FULL-DOFi ≥2.3 ≥2.75 ≥0 2.1 Steep ≥2.3 ≥2.75 ≥0.14 2.2 Smooth ≥2.3 ≥2.75 ≥0.05 and <0.14 2.3 Continuous ≥2.3 ≥2.75 <0.05 DOFi = depth of field; ΔVA = visual acuity increase from intermediate to near Figure 2.: Mean defocus curve obtained for each IOL classification. The colored background shows the cutoff zones for PARTIAL-DOFi (left) and FULL-DOFi (right) IOLs. FULL-DOFi IOLs are characterized by an increase in VA from intermediate to near.2 DOFi = depth of fieldOne of the central discussions within the FVWG was the need to clearly define the purpose of the Functional Classification and how it differs from the intent of classification systems outlined in international standards, such as those used for premarket regulatory approval (eg, ISO 11979-7:2024).6–8 ISO classifies Simultaneous Vision Lenses (SVIOL) in 3 types: multifocal (MIOL), Extended Depth of Focus (EDF), and Full Visual Range (FVR). The endpoints defined in the ISO standard, summarized in Table 2, ultimately replaced the previously reported absolute DOFi, as described in an earlier special report, with additional measures of distance-corrected visual acuity at intermediate (100 cm) for EDF and FVR, and at near (50 cm) for FVR.2,8 Table 2. - Summary of the final approved endpoints for Standard ISO 11979-7:2024 classification for MIOL, EDF, and FVR lenses MIOL EDF FVR Mesopic (logCS) without glare ≤0.3a* ≤0.3a* ≤0.3a* CDVA (logMAR) ≤0.2b ≤0.1a* ≤0.1a* DCIVA at 100 cm (logMAR) ≤0.2b ≤0.2b DCIVA at 66 cm (logMAR) ≤0.2b and Xa* ≤0.2b and Xa* DCNVA at 50 cm (logMAR) ≤0.2b DCNVA at 40 cm (logMAR) Xa* ≤0.2b and Xa* ΔDOFi in 0.2 (logMAR) 0.5a* CDVA = corrected distance visual acuity; DCIVA = distance-corrected intermediate visual acuity; DCNVA = distance-corrected near visual acuity; DOFi = depth of field; EDF = extended depth of focus; FVR = full visual range; MIOL = multifocalX = relative difference for any magnitude X vs monofocal control group*One-tailed test vs control (P = .025)aRelative difference for established value vs monofocal control groupbAbsolute value The ISO focuses on technical specifications and performance benchmarks to ensure safety and efficacy before a product enters the market. However, the FVWG Functional Classification serves as a postmarket, evidence-based framework. Its goal is to organize IOL performance into mutually exclusive, clinically meaningful, and progressive categories based on outcomes that matter to patients. These differing aims are not contradictory but complementary. Regulatory classification ensures product safety and performance by using fewer categories and more easily reproducible endpoints, enabling industry to generate consistent data that can be used by authorities during the approval process. By contrast, the Functional Classification involves a greater number of categories and relies on endpoints that, while less easily reproducible, offer more comprehensive information to support ophthalmologists, patients, and healthcare payers in shared decision-making and the optimization of individualized, patient-centered care. In other words, the ISO standard defines what must be proven clinically for a lens to be marketed in a category, while the Functional Classification provides a more nuanced performance profile both within and across categories. Expanding Endpoints: Beyond DOFi Members of the FVWG also emphasized the importance of incorporating additional visual quality metrics beyond visual acuity and the depth of field required to achieve a specific level of best-corrected visual acuity as assessed from the monocular defocus curve. These include contrast sensitivity and patient-reported outcomes (PROMS) (eg, positive dysphotopsia, satisfaction, and spectacle dependence), as well as the influence of biometric parameters such as pupillometry and corneal aberrations. Furthermore, procedure efficacy involving binocular outcomes should not be overlooked, particularly when evaluating strategies such as monovision or mix-and-match approaches. These concerns had already been addressed in the original study in which the authors explained that the high variability of these outcomes within the same category precluded their use as endpoints in the cluster analysis for IOL classification.5 As a result, the authors recommended that contrast sensitivity and PROMs be investigated through individual randomized clinical trials involving paired comparisons between technologies.5 Considering this limitation, one of the proposed future directions is to develop evidence-based strategies for integrating these additional endpoints into the Functional Vision Framework. To achieve this goal, reducing between-study bias is essential and can be facilitated by encouraging researchers to adhere to standardized methods for measuring and reporting outcomes.9 In the particular case of PROMs, current standards recommend that investigators select validated questionnaires that best align with the specific domain of interest. However, from a clinically relevant perspective, reporting the proportion of participants achieving a particular level on individual items, such as those rated on a 5-point Likert scale, can provide valuable insights.9 The FVWG agreed that the AIOLIS questionnaire best captures a wide range of single-item questions related to the frequency and severity of visual symptoms, as well as grading of visual quality, satisfaction, and spectacle independence.3 In light of this, the FVWG will support research initiatives aimed at refining the AIOLIS questionnaire and translating it into multiple languages to promote its broader adoption and facilitate standardization in clinical research. Future Directions and Guidelines Although cutoff for Functional Classification criteria has been clearly defined by evidence, variability in testing methods and individual biometric eye parameters can influence the outcomes of the monocular corrected distance defocus curve.5 As a result, a single IOL may fall into more than 1 category depending on these factors. Conversely, the ophthalmologic community could benefit from information provided by industry that outlines the general Functional Classification performance of their IOLs, along with the specific conditions under which this performance may vary. The FVWG agreed that guidelines are needed to evaluate the body of evidence supporting the classification of a given IOL, including a system to grade the level of certainty, defined as the degree of confidence that an IOL will deliver a given functional performance based on the Functional Classification. This grading process should begin with predictions derived from optical bench data, with particular emphasis on presenting information through predictive models that translate optical measurements into functional outcomes while acknowledging their inherent limitations. It should then progress to the generation of early clinical evidence from pilot studies and culminate in the highest levels of certainty, supported by peer-reviewed clinical research and subsequent meta-analyses. The FVWG is currently working on the development of these guidelines, aiming to balance rigorous assessment of evidence quality with the simplicity necessary to ensure broad adoption by both industry stakeholders and ophthalmologists. Conclusion The joint development of a Functional Vision Framework by ESCRS, ASCRS, APACRS, and LATAMSCRS marks an important milestone in modern IOL classification. By emphasizing patient-centered outcomes such as depth of field and real-life visual function, this framework complements regulatory classifications and enriches shared decision-making. Future enhancements, including the incorporation of PROMs and contrast sensitivity, will further improve its clinical utility. The FVWG remains committed to fostering global standardization and continuous refinement of this evidence-based approach.
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