Author Affiliations: Center for Health Policy (Dr Kymes), and Department of Ophthalmology and Visual Sciences (Drs Kymes, Kass, and Gordon) and Division of Biostatistics (Drs Kymes and Gordon), School of Medicine, Washington University, St Louis, Missouri; Abt Associates Inc, Cambridge, Massachusetts (Dr Plotzke); and Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland (Dr Boland).
To assess the influence of expected life span on the cost-effectiveness of treating ocular hypertension to prevent primary open-angle glaucoma.
We used a Markov simulation model to estimate the cost and benefit of ocular hypertension treatment over a person's remaining life. We examined the influence of age on the cost-effectiveness decision in 2 ways: (1) by evaluating specific age cohorts to assess the influence of age at the initiation of treatment; and (2) by evaluating the influence of a specific life span.
At a willingness to pay $50 000/quality-adjusted life year to $100 000/quality-adjusted life year, treatment of people with a 2% or greater annual risk of developing glaucoma was cost-effective for people aged 45 years with a life expectancy of at least 18 remaining years. However, to be cost-effective, a person aged 55 years must have a life expectancy of 21 remaining years and someone aged 65 years must have a life expectancy of 23 remaining years.
A person with ocular hypertension must have a life expectancy of at least 18 remaining years to justify treatment at a threshold of a 2% or greater annual risk of developing glaucoma. Persons at higher levels of risk require a life expectancy of 7 to 10 additional years to justify treatment.
The effects of glaucoma on quality of life, visual function, and heath care costs have been widely documented.1- 3 Recent reports indicate a prevalence of glaucoma in excess of 2 million people in the United States, with an expectation that this will increase to more than 3 million people by 2020.4 Investigators from the Ocular Hypertension Treatment Study (OHTS) reported that treatment of ocular hypertension to prevent glaucoma was cost-effective when limited to individuals with a 2% or greater annual risk of developing glaucoma.5 Based on the prevalence of risk factors in the OHTS, the investigators estimated that this represents nearly one-third of those with intraocular pressure greater than 24 mm Hg.
The purpose of the OHTS economic evaluation was to examine the cost-effectiveness of treatment as a national policy. Specifically, the investigators questioned whether the benefits of ocular hypertension treatment to prevent glaucoma outweighed the costs when treating all people in the United States with ocular hypertension. However, this analysis did not consider the effect of the individual's nonocular prognosis on the treatment decision. Life expectancy is an important element of the cost-effectiveness calculations for glaucoma prevention as it affects the period in which a person with ocular hypertension is at risk for developing glaucoma. In addition, age itself is an independent risk factor for glaucoma. Economic investigators have often found that consideration of prognostic factors such as age or sex will frequently affect the cost-effectiveness decision.6,7
In this article, we examine how the cost-effectiveness of treating ocular hypertension to prevent primary open-angle glaucoma (POAG) is affected by a patient's life expectancy. First, we will look at the cost-effectiveness of treatment based on the person's age at the initiation of treatment by testing simulated cohorts of people aged 45, 55, and 65 years. In doing this, we are testing the cost-effectiveness of treatment assuming that each member of our hypothetical cohort faces the annual mortality risk of the average person of their age. Next, we will directly examine the influence of life expectancy on the cost-effectiveness of treatment by modeling specific life expectancies of individuals.
We constructed a Markov decision model to estimate the cost and effectiveness of treating ocular hypertension over a person's remaining years of life. Parameters in the model included estimates of the risk of developing POAG among those who were prescribed intraocular pressure–lowering medication and those who were not, the probability of progression from early POAG to more severe disease, and estimates of the effect of POAG and blindness on quality of life. In this simulation, an incident case of POAG was defined in the same manner as in the OHTS8 and we defined the stages of POAG with the modified Hodapp-Anderson-Parrish taxonomy used by Lee et al2 (Table 1 and Figure 1). We considered the cost of medical treatment of ocular hypertension and POAG by the stage of disease and by the cost of blindness. We examined the influence of life expectancy on cost-effectiveness by running 3 simulated cohorts each with a single baseline age: 45, 55, and 65 years. The parameters used in the model are detailed in Table 2.
Diagram of the Markov model used to evaluate the effect of life expectancy on the cost-effectiveness of ocular hypertension treatment to prevent glaucoma. POAG indicates primary open-angle glaucoma.
We used a Markov model to describe the progression of a chronic disease through a series of mathematical relationships.17 During the first year, a certain percentage of a cohort progressed to the first stage of glaucoma or died of other causes. During the next year, a certain percentage of the cohort died, a certain percentage of those with ocular hypertension progressed to the first stage of glaucoma (joining those who progressed there during the first year), and a certain percentage of those who progressed to the first stage of glaucoma during the first year progressed to the second stage of glaucoma. Estimation of the model continued in an iterative manner until the entire cohort died of other causes (Figure 1). For more details, see the eAppendix (also see http://ohts.wustl.edu).
We examined 5 treatment thresholds: (1) treat no one until there is evidence of glaucoma-related nerve damage; (2) treat those with a 5% or greater annual risk of developing glaucoma; (3) treat those with a 4% or greater annual risk; (4) treat those with a 3% or greater annual risk; and (5) treat those with a 2% or greater annual risk. We estimated the incremental cost-effectiveness ratio for each of the treatment thresholds by comparing the costs and quality-adjusted life years (QALYs) associated with that management strategy vs those associated with the strategy of treating no one until there is evidence of glaucoma-related nerve damage. We chose to take this approach as it best represented the decision that an individual and his or her physician would make (ie, treat or not treat) rather than a consideration of setting a treatment threshold that would reflect a population-based policy decision.18 To determine the number of years someone must live before treatment would be considered cost-effective, we eliminated annual mortality from the model and sequentially tested different life spans ranging from 1 to 54 additional years of life. We report the minimum number of additional years of life past an individual's baseline age needed to result in an incremental cost-effectiveness ratio that meets accepted standards for cost-effectiveness (ie, in cost per QALY).
The robustness of the model to changes in assumptions concerning the underlying parameters was tested using 1-way sensitivity analyses. An intervention is considered cost-effective if the value society places on a QALY is greater than the resources required to “purchase” the QALY. This is based on the willingness-to-pay (WTP) threshold or the social value of the QALY.19 While some health economists argue that the true threshold exceeds $200 000/QALY,20 most recognize $100 000/QALY as the upper limit.21 In these analyses, we tested 3 WTP thresholds: $50 000/QALY, $75 000/QALY, and $100 000/QALY. We used a standard of $75 000/QALY for sensitivity analyses. Our group took a similar approach in a previous report.5
Model calibration is an important step in providing evidence of the internal and external validity of the decision model.19 Details of the process and results of calibration of the OHTS model are included in our previous report.5 In brief, the OHTS economic model was calibrated by comparing the expected prevalence of glaucoma predicted by the model with that of published estimates. In addition, we evaluated the expected incidence of blindness among members of the simulated cohort. In both cases, the model was found to reflect an acceptably conservative estimate of the disease process.
We conducted this evaluation according to the guidelines described by the Panel on Cost-effectiveness in Health and Medicine.19 We took a societal perspective by considering all relevant costs and benefits associated with the intervention regardless of whether they were borne by the person or society. All costs and benefits in the model were discounted at a 3% annual rate.19 Statistical analyses were performed with SAS version 9.1 statistical software (SAS Institute, Inc, Cary, North Carolina), and decision analyses were performed with TreeAge Pro 2007 Suite version release 1.1 software (TreeAge Software, Inc, Williamstown, Massachusetts).
The minimum annual risk of POAG at which it is cost-effective to treat ocular hypertension for each age cohort is presented in Figure 2. This shows that, in general, younger people are more likely to benefit from treatment than are older people. For example, using a WTP threshold of $50 000/QALY, it is cost-effective to treat patients with a 2% or greater annual risk of developing glaucoma. However, using that same WTP threshold, treating those older than 65 years is only cost-effective with a 4% or greater annual risk of developing glaucoma.
Cost-effectiveness threshold for treatment by age and willingness-to-pay (WTP) threshold. POAG indicates primary open-angle glaucoma; QALY, quality-adjusted life year.
The minimum number of years needed to live for an intervention to be considered cost-effective for each age cohort is reported in Table 3. Within a particular age cohort, as the intervention is offered to fewer people (ie, only those with a higher annual risk of developing glaucoma), the minimum number of years of life needed for that intervention to be cost-effective decreases. That is, for those aged 45 years with a 2% or greater annual risk of developing glaucoma, the individual must live for 18 additional years for the intervention to be considered cost-effective (at a WTP threshold of $75 000/QALY) compared with needing to live only 7 additional years if the individual had a 5% or greater annual risk. Note also that there is considerable difference between age cohorts in the life expectancy necessary to justify treatment. For example, someone aged 65 years with a 2% or greater annual risk of glaucoma must have a life expectancy of 21 to 26 remaining years (depending on the WTP threshold chosen) for treatment to be cost-effective, while someone aged 45 years must have a life expectancy of 17 to 21 remaining years. For those with a 5% or greater annual risk of developing glaucoma, the difference is even more extreme. These differences are driven by the increased proportion of people in the age cohort who fall under the treatment threshold as the age cohort becomes older (given that age is a risk factor for the development of glaucoma).
The results of our sensitivity analyses are presented in Table 4. The range of utility values tested behaved as expected with the assumption that those with the least utility loss (0.0125) needed an additional 2 to 5 years of life expectancy to justify treatment compared with those with the highest utility loss (0.05). Those with the lowest rate of progression from stage 1 POAG to stage 2 POAG (0.01/year) needed to have a life expectancy of 1 to 6 years longer than those with the highest rate of progression (0.1/year). Those with the highest annual medication costs ($1000) needed a life expectancy of 6 to 16 years longer than those with the lowest annual medication costs ($150). For certain combinations of risk and age, facing the highest annual increase in incidence rates (2.7%) did not change a person's needed life expectancy to reach cost-effectiveness when compared with the lowest annual increase in incidence rates (0.9%). With the exception of the utility and medication cost results, the extremes tested here had little clinical relevance.
In our previous report,5 we found that treatment of people with ocular hypertension (ie, intraocular pressure ≥24 mm Hg in at least 1 eye) met accepted standards of cost-effectiveness when applied as a standard management strategy for people with a 2% or greater annual risk of developing glaucoma. However, in conducting that investigation, we took the broad perspective of a societal decision maker and did not give extensive consideration to the effect that prognostic factors might have on the cost-effectiveness of treatment of an individual.
In this work, we found that implementation of the 2% or greater threshold on an individual basis requires that the person have a life expectancy of at least 21 remaining years if they are aged 45 years or 24 remaining years if they are aged 55 years—both of which are well within the life expectancy of the average person of that age.22 However, if the patient is aged 65 years or older, the life expectancy (17 remaining years for men, 21 remaining years for women) is such that treatment to prevent glaucoma is not cost-effective for any other than those at relatively high risk for developing glaucoma (ie, ≥5% annual risk) and then only when we rely on the most liberal standard of cost-effectiveness.
Some may find it puzzling that a shorter life expectancy is required to justify treatment for a younger person than an older one. This is a function of the prevalence of risk factors among people of that age. While our model focuses on treatment of the individual, we must still recognize that the treatment recommendation affects all people of that cohort. There are proportionally fewer who meet the 2% or greater threshold for risk of developing glaucoma among people aged 45 years than among those aged 55 or 65 years. Therefore, from a societal perspective, it costs more to treat all 65-year-olds with a 2% or greater risk (because there are more being treated) than it costs to treat all 45-year-olds with a 2% or greater risk. As it is more costly to treat, more benefit must be generated to offset the cost of treatment; therefore, the person being treated must be treated for a longer time to gain the QALYs to offset the cost of care.
The Baltimore Eye Study investigators found that more than 50% of all people with intraocular pressure greater than 24 mm Hg were older than 65 years.5 The Beaver Dam Eye Study investigators reported similar findings.23 Some may find it unethical to incorporate life expectancy into a cost-effectiveness decision. However, it is important to remember that the result of an economic evaluation is but one component of a health policy decision and that the nature of economic evaluation is to remain radically neutral concerning qualitative factors such as equity and other social and ethical values.24 Therefore, if policy makers determine that noneconomic factors indicate that treatment of a person older than 65 years (or someone with a shortened life expectancy) is justified, they might disregard the findings presented here and offer treatment to older people (or younger people with life-threatening disease) based on the findings of our original study.5
Boland and colleagues recently reported the results of a survey of 58 glaucoma specialists asked to make treatment recommendations based on scenarios of patients with ocular hypertension (M.V.B., Harry A. Quigley, MD, and Harold P. Lehmann, MD, PhD, unpublished data, 2007). On average, before presentation of a risk estimate, the average threshold for treatment was 4.6% per year. After presentation of a risk estimate, the average threshold was 3.4% per year. Both of these thresholds are well above the 2% or greater threshold recommended in our previous report.5 Boland and colleagues also reported that the increased risk associated with age was not a significant predictor of physician treatment recommendations in the absence of a formal risk calculator. When the risk calculator was used, increasing age was predictive of a recommendation to treat, although the role of increasing age was not as significant as suggested by the OHTS results.8
As a tool for making a treatment decision, risk calculators only provide direction concerning one aspect of the treatment decision. They do not incorporate patients' attitudes toward disease and treatment. However, while we have discussed the role of anonymous decision makers in the use of our results, the insights they might give us into the patient's perspective are essential. In our sensitivity analysis, we found that utility loss associated with progression to the first stage of POAG was an important factor for determining cost-effectiveness. This is evidence that if treatment of an older person with moderate risk of progression to POAG is being considered, clinicians need to understand the patient's attitudes and knowledge of the risks and consequences of the disease. If the clinician learns that the patient's perception of his or her visual prognosis is unrealistically pessimistic, careful education concerning the risk of loss of visual function might be a more effective approach to treating ocular hypertension than medication. On the other hand, if the patient has a realistic understanding of the risks and consequences of the disease but is highly risk averse concerning visual impairment, the patient might benefit from treatment regardless of his or her life expectancy.
As with any economic model, the results may be biased to the extent that we have incomplete knowledge of the parameters or distributions used in the model. However, the results of our sensitivity analyses were robust to a wide range of parameters as tested through sensitivity analysis. An additional concern is that our results represent the cost-effectiveness related to treatment for particular age subgroups. Since we have found differences in the cost-effectiveness based on a person's age, it is possible that differences in cost-effectiveness will exist for other subgroups such as sex or race. At the same time, it is unclear how these characteristics may affect the progression of disease or other factors influencing cost-effectiveness.
Previous work from the OHTS showed that, on average, treatment of people with ocular hypertension and a 2% or greater annual risk of progression to glaucoma met commonly accepted standards of cost-effectiveness. Here we have found that when the person's life expectancy was taken into consideration, the 2% or greater threshold met standards of cost-effectiveness only when the person is aged 45 years and has a life expectancy of more than 20 remaining years. Treatment of those aged 55 years requires a life expectancy of 24 remaining years or acceptance of a more liberal standard of cost-effectiveness. Treatment of people older than 65 years did not meet most accepted standards of cost-effectiveness. However, the patient's attitude toward treatment and disease progression remains an important factor in determining the cost-effectiveness of treatment.
Correspondence: Steven M. Kymes, PhD, Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, Campus Box 8096, 660 S Euclid Ave, St Louis, MO 63110-1093 (firstname.lastname@example.org).
Submitted for Publication: September 27, 2008; final revision received August 10, 2009; accepted August 19, 2009.
Financial Disclosure: None reported.
Funding/Support: This work was supported by grants EY09341 and EY09307 from the National Eye Institute, the National Center on Minority Health and Health Disparities, Pfizer Inc, Research to Prevent Blindness, and core grant P30 EY 02687 from the National Institutes of Health.
Role of the Sponsor: No funding organization was involved in the design, conduct, review, or approval of this evaluation.
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