Highlights
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First cost-effectiveness analysis comparing EDOF and trifocal IOLs within a presbyopia-correcting IOL population.
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EDOF and trifocal IOLs demonstrate comparable economic value with small incremental differences and decision uncertainty.
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Lens selection should emphasize individualized, preference-sensitive decision-making rather than economic dominance.
Purpose
To evaluate the incremental cost-effectiveness of extended depth of focus (EDOF) compared with trifocal intraocular lenses (IOLs) among patients undergoing bilateral cataract surgery who elect for presbyopia-correcting IOL implantation.
Design
Cost-effectiveness analysis using a state-transition (Markov) model.
Subjects
Hypothetical cohort of 65-year-old patients undergoing bilateral cataract surgery with presbyopia-correcting IOLs.
Methods
A lifetime Markov model simulated postoperative health states reflecting spectacle independence, visual disturbances, and mortality. The analysis was framed as a conditional comparison within a presbyopia-correcting IOL population. Cost-effectiveness was assessed using the incremental cost-effectiveness ratio (ICER) and net monetary benefit (NMB). A willingness-to-pay (WTP) threshold of $100,000 per quality-adjusted life year (QALY) was applied. One-way and probabilistic sensitivity analyses were conducted to evaluate parameter uncertainty.
Results
EDOF IOLs resulted in an incremental gain of 0.02 QALYs at an additional cost of $106, yielding an ICER of $6,515 per QALY. The incremental net monetary benefit differed by $1,534 at a WTP threshold of $100,000 per QALY, reflecting minimal economic separation between strategies. One-way sensitivity analyses demonstrated that modest changes in spectacle dependence and visual disturbance resolution could reverse economic preference, indicating proximity to economic neutrality. In probabilistic sensitivity analysis, EDOF IOLs were cost-effective in 56.7% of 10,000 simulations at a WTP threshold of $100,000 per QALY, demonstrating persistent decision uncertainty.
Conclusions
EDOF and trifocal IOLs provide comparable economic value within a presbyopia-correcting IOL population. Given the small incremental differences and persistent uncertainty, lens selection should emphasize individualized, preference-sensitive decision-making rather than population-level economic preference.
The aging population in the United States, driven by the substantial baby boomer generation, will significantly impact Medicare and the broader healthcare landscape over the next 3 decades. By 2050, 82 million Americans will be aged 65 years and older, accounting for nearly 25% of the total population. This demographic shift poses substantial challenges in healthcare expenditures, particularly within ophthalmology, as the prevalence of age-related eye disease increases.
Among these conditions, cataracts remain nearly universal with aging. Cataract surgery is one of the most commonly performed surgical procedures among older adults in the United States. In 2012, approximately 3 million cataract surgeries were performed annually, accounting for more than $3.4 billion in Medicare spending. With surgical volumes increasing at an estimated rate of 3%–4% per year, the number of procedures is projected to approach six million annually by 2030. , The scale and economic impact of cataract surgery make it an important focus of value-based evaluation.
In recent years, presbyopia-correcting intraocular lenses (IOLs) have gained popularity by offering enhanced postoperative visual outcomes compared to conventional monofocal lenses. Since the introduction of the first multifocal IOL in the late 1990s, numerous presbyopia-correcting technologies have been developed. Two widely adopted options are trifocal and Extended Depth of Focus (EDOF) IOLs. Trifocal IOLs generate multiple focal points using refractive or diffractive optical designs, often achieving high rates of spectacle independence but with an increased risk of bothersome photic phenomena. In contrast, EDOF IOLs utilize a single elongated focal point to extend depth of focus, typically providing excellent intermediate and distance vision with reduced dysphotopsia, though often at the expense of near visual acuity and greater spectacle dependence. ,,
Given the growing utilization of presbyopia-correcting IOLs and their associated incremental costs, cost-effectiveness analysis plays an important role in informing clinical and policy decisions. Prior studies have evaluated the cost-effectiveness of presbyopia-correcting IOLs, including EDOF and trifocal IOLs, relative to monofocal lenses. ,,, However, in contemporary cataract practice, the decision to pursue presbyopia correction frequently represents a preference-sensitive choice that may involve additional out-of-pocket payment. Once that decision is made, the relevant clinical question often shifts from premium vs monofocal to selection among premium technologies.
To our knowledge, no published studies have evaluated the relative cost-effectiveness of presbyopia-correcting IOL technologies within this conditional decision framework. The present study does not address whether premium IOLs should be adopted over monofocal lenses; rather, it examines a subsequent clinical decision that arises after patients elect presbyopia correction. Specifically, we evaluate the incremental cost-effectiveness of Extended Depth of Focus (EDOF) vs trifocal IOLs within a defined premium IOL population. By isolating this within-premium comparison, this analysis aims to inform shared decision-making in a preference-sensitive setting where differences in spectacle independence and visual disturbances may meaningfully influence patient choice.
METHODS
Markov Model
A state-transition (Markov) model was constructed using TreeAge Pro 2025 (TreeAge Software, Williamstown, MA) to simulate lifetime outcomes among patients undergoing bilateral cataract surgery who elected presbyopia-correcting intraocular lens (IOL) implantation. The model compared Extended Depth of Focus (EDOF) and trifocal IOL technologies within this premium IOL population.
A lifetime time horizon was adopted to capture long-term differences in spectacle dependence, visual disturbances, quality of life, and cumulative costs. In the base case, patients entered the model at 65 years of age. One-way sensitivity analysis was conducted on age at surgery to reflect demographic variability. The model used annual cycles, and both costs and health outcomes were discounted at 3% per year in accordance with standard health economic practice.
The model estimated long-term costs and quality-adjusted life years (QALYs) associated with each IOL strategy.
Health States
The Markov model incorporated the following health states to reflect possible outcomes post-cataract surgery ( Figure 1 ):
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Well
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Patients in this state experience optimal visual outcomes, with no need for corrective lenses and absence of bothersome visual disturbances.
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Glasses
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This state represents patients who require corrective lenses for certain visual tasks but do not experience significant visual disturbances.
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Glare, Haloes, and/or Starbursts
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Patients in this state do not require corrective lenses but experience bothersome visual disturbances.
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Glare, Haloes, and/or Starbursts with Glasses
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This state encompasses patients who both require corrective lenses and experience bothersome visual disturbances.
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Death
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An absorbing state, representing patient mortality from any cause.
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Simplified state transition diagram.
These health states were chosen to capture the key clinical outcomes that differentiate the performance of EDOF and trifocal IOLs. By including states that combine spectacle independence and visual disturbances, the model can effectively simulate the trade-offs between these 2 important factors in post-cataract surgery outcomes. The inclusion of death as an absorbing state allows the model to account for overall patient survival and its impact on long-term cost-effectiveness.
Cost-Effectiveness Analysis
The cost-effectiveness was evaluated using both the Incremental Cost-Effectiveness Ratio (ICER) and the Net Monetary Benefit (NMB).
The ICER was calculated as:
ICER = (Cost of EDOF Intervention Arm- Cost of Trifocal Intervention Arm)/ (Effect of EDOF Intervention Arm- Effect of Trifocal Intervention Arm)
The primary willingness-to-pay (WTP) threshold was set at $100,000 per quality-adjusted life year (QALY), consistent with commonly applied contemporary U.S. cost-effectiveness benchmarks. Results were additionally reported across WTP thresholds ranging from $50,000 to $150,000 per QALY to facilitate multi-threshold interpretation.
Net Monetary Benefit (NMB) was calculated as:
NMB = (WTP threshold × Effectiveness measured in QALYs)– Costs
Because incremental differences in costs and QALYs between strategies were anticipated to be small, interpretation emphasized NMB across thresholds rather than reliance on a single ICER cutoff. NMB allows direct comparison of value under varying WTP assumptions and provides a more stable decision metric when incremental effectiveness differences are modest.
Sensitivity Analysis
To assess the robustness of the model results, both one-way sensitivity analysis and probabilistic sensitivity analysis (PSA) were conducted.
In the one-way sensitivity analysis, key model parameters were varied individually across plausible ranges to evaluate their impact on the cost-effectiveness outcomes. This analysis helps identify the most critical factors affecting the cost-effectiveness of the interventions.
For the PSA, we performed 10,000 Monte Carlo simulations, simultaneously varying all model parameters according to their predefined probability distributions. This comprehensive approach accounts for the joint uncertainty across all model inputs. The PSA results provide a more nuanced understanding of the overall uncertainty in the model’s outcomes and the probability of cost-effectiveness at different WTP thresholds.
Model Input Probabilities
The model’s transition probabilities ( Table 1 ) were primarily derived from published clinical trial data, providing base case estimates for key outcomes in both EDOF and trifocal IOL intervention groups including the probability of overall spectacle dependence and the likelihood of experiencing bothersome visual disturbances such as halos, glares, and starbursts. Additionally, a very small percentage of patients in our model required an IOL exchange due to visual dissatisfaction based on previously published data.
Table 1
Transition Probabilities
| Parameter | Application in Model | Value |
|---|---|---|
| Overall spectacle dependence with EDOF IOL | Within 1 year | 0.670 |
| Overall spectacle dependence with Trifocal IOL | Within 1 year | 0.170 |
| Bothersome glare, halos and/or starbursts with EDOF IOL | Within 1 year | 0.082 |
| Bothersome glare, halos and/or starbursts with trifocal IOL | Within 1 year | 0.635 , |
| Resolution of glares, halos and/or starbursts | After 1 year | 0.7 |
| Age-specific annual mortality per U.S. Social Security Actuarial Life Table (2024) | After 1 year | Variable |
IOL = intraocular lens.
The rate of resolution for bothersome visual disturbances was estimated using long-term follow-up data from patients who underwent cataract surgery with trifocal IOLs. The study reported that approximately 20% of patients still experienced persistently bothersome photic phenomena at 6.5 years post-operatively with trifocal IOLs. This long-term rate was compared to the aggregate rate of experiencing at least one photic phenomenon at 6 months post-operatively with trifocal IOLs to estimate the probability of resolution for bothersome visual disturbances. The same resolution rate was assumed for patients who underwent cataract surgery with EDOF IOLs and experienced bothersome visual disturbances at 6 months post-operatively. Based on clinical judgment, the model assumed that if visual disturbances did not resolve within the first year, the patient would continue to experience the photic phenomenon for the remaining cycles in the simulation. This assumption reflected the chronic nature of unresolved visual disturbances following cataract surgery.
Model Input Utility Scores
Utility scores quantify quality of life on a standardized scale from 0 (death) to 1 (perfect health). In cost-effectiveness analyses, utilities are used to estimate quality-adjusted life-years (QALYs) by accumulating the utility associated with each health state during each annual Markov cycle, applying a 3% annual discount rate to future values in accordance with standard health economic practice.
In this model, utilities reflected vision-specific quality-of-life differences following cataract surgery rather than overall systemic health. These utilities were derived from time trade-off studies anchored to perfect vision rather than perfect overall health. The well state, defined as complete spectacle independence without visual disturbances was assigned a utility of 1, representing optimal postoperative function. Dis-utilities were applied for visual impairments based on prior studies: −0.18 ,,, for very bothersome visual disturbances (glares/halos/starbursts) and − 0.065 for spectacle dependence. ,,, These vision-specific utilities ( Table 2 ) were integrated into the Markov model to quantify the quality-of-life impact of each postoperative state.
Table 2
Utility Inputs
| Health State | Utility Value |
|---|---|
| Wellness state | 1.000 |
| Bothersome visual disturbances | −0.18 , |
| Spectacle dependence | −0.065 , |
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