HDI France, Spéracèdes, France,
1 Stockholm Health Economics Consulting AB, Uppsala, Sweden,
2 Department of Rheumatology, City Hospital, St Albans, UK (for the Early RA Study group) and
3 Department of Rheumatology, Lund University Hospital, Lund, Sweden
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Abstract |
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Methods. The effect of infliximab on disease progression and related costs and utilities was estimated using two disease progression models based on epidemiological cohorts followed for up to 15 yr in Sweden and the UK. The clinical trial data were used directly in the model and extrapolated to 10 yr using a cohort from the epidemiological studies matched for gender, age, time since onset of RA and disease severity.
Results. One to two years of treatment with infliximab treatment reduced direct and indirect resource consumption in both countries, thereby partly offsetting the treatment cost. In the base case, including both direct and indirect costs, the cost per QALY gained was SEK 32 000 (€3440) in Sweden and GBP 21 600 (€34 800) for 1 yr of treatment. The respective QALY gains were 0.248 and 0.298. With 2 yr of treatment, the costs per QALY gained were SEK 150 000 (€16 100) and GBP 29 900 (€48 200).
Conclusions. Although 12 yr of treatment with infliximab will lead to savings in both direct and indirect costs, these will not offset the drug cost. However, the cost-effectiveness ratios remain within the usual range for treatments to be recommended for use.
KEY WORDS: RA, Cost-effectiveness, Utility, QALY, Cost, Infliximab.
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Introduction |
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Direct health-care consumption represents about one-quarter of all costs in Sweden and the UK and is dominated by in-patient care [14, 15]. Drugs represent currently a minor fraction of total costs (34% of total and 1315% of direct costs). However, several new treatments have recently been introduced, and both the widely used and typically generic disease-modifying anti-rheumatic drugs (DMARDs) and non-steroidal anti-inflammatory drugs (NSAIDs) are being replaced with more potent and/or more tolerable, but also more expensive, treatments. Thus, the economic question is how the added benefit of these treatments compares with the increased drug costs.
When compared with methotrexate alone, infliximab (Remicade®) in combination with methotrexate has been shown in a 1 yr double-blind clinical trial [Anti-Tumour Necrosis Factor Trial in Rheumatoid Arthritis with Concomitant Therapy (ATTRACT)] to reduce disease symptoms significantly and to slow disease progression in patients with RA who are not adequately controlled on DMARDs including methotrexate [16]. In the open extension, this effect was maintained [16]. The objective of the present analysis was to estimate the cost-effectiveness of infliximab plus methotrexate vs methotrexate alone in this patient population.
The key issue when performing cost-effectiveness analyses of new treatments in chronic diseases is that clinical trials are generally short compared with the duration of the disease, and limited data on the use of the new treatments in clinical practice are available. Health benefits, as well as the potential economic impact, of treatments that affect the progression of RA will, however, be most evident in the longer term. If the development of functional disability is delayed, the resource consumption of patients can be expected to be lower, their ability to work maintained longer, and consequently their quality of life (QoL) increased. Several studies in RA patients have shown that resource consumption increases as the disease progresses, while the patients' QoL decreases [13, 17, 18].
Thus, we require a baseline against which we can evaluate new treatments within a time-frame that exceeds that of the clinical trials, making modelling unavoidable. Economic evaluations compare treatment strategies in terms of their costs (resources used) and their effectiveness (health benefits), and results are expressed as the extra cost for each unit of additional health benefit obtained with one treatment strategy compared with another [1921]. A baseline disease model must therefore incorporate good epidemiological data over a relevant time-frame, detailed resource consumption for patients at all levels of disease severity, and an effectiveness measure that is generally available in both epidemiological studies and clinical trials. The model must also be adaptable to different patient populations, as different clinical trials select patients at different levels of disease severity or at different times since disease onset. We have proposed such a framework earlier, on the basis of two cohort studies in Sweden and in the UK [17], and the present analysis of infliximab uses these two disease models.
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Materials and methods |
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Epidemiological data
The RA models have six disease states based on functional disability (state 1 represents least disability and state 6 worst disability) measured with the Health Assessment Questionnaire (HAQ) [24] and one state for death. Disease progression is based on changes in annual HAQ scores in two cohort studies in Sweden (Lund) [2528] and the UK [Early RA Study (ERAS)] [29, 30]. The Lund study followed 183 patients for up to 16 yr (mean 11.3 yr), and the ERAS study currently includes 1473 patients followed for up to 15 yr (mean 7.8 yr). The basic demographics of the two cohorts are shown in Table 1 and disease progression is illustrated in Fig. 1
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Transition probabilities
The basic structure of the models is shown in Fig. 2. The cycle length is 1 yr, in line with the annual follow-up data in the epidemiological studies, and the models run for 10 yr. Transition probabilities between states were estimated using an ordered probit regression model that allowed controlling for the age and gender of the patient and the time since onset of disease. The regression function can be used to generate transition probabilities for a cohort that will match the patients included in ATTRACT in terms of age, gender and time since onset of RA. In the ordered probit regression model, a latent variable, y, determines the current HAQ state of a patient. This latent variable is explained by the regression equation
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Outcome measure
Economic evaluation requires that effectiveness be expressed with one measure, in order to estimate the cost per additional health unit gained by an intervention. RA, like many other chronic diseases, has a continuous effect on several functions over a long period of time, and several disease measures are used. In such cases, the effectiveness measure most used in economic evaluation is the quality-adjusted life-year (QALY). The QALY combines quality of life with time by adjusting life-years with a quality weight, measured as utility. Utility is defined as the preference patients and/or the general population have for given states of health, expressed as a value on a scale between 0 (death) and 1 (full health), and is measured using interview-based techniques from decision analysis or preference-based QoL instruments, such as the EQ-5D (EuroQol) [3133]. This instrument has been shown to be sensitive to disease severity in RA [13, 18] and was therefore used to estimate country-specific utilities for the different Markov states, as shown in Fig. 3 [17].
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Resource utilization and costs
Resource consumption was estimated from the cohort studies and from a cross-sectional subsample of patients in ERAS [17]. All observations for patients in a given state, at any year in the follow-up, were used to calculate the average annual cost for each state. One limitation is that in both cohorts, the number of patients with very severe disability (HAQ >2.6) was rather limited, and direct costs in state 6 should therefore be considered with caution. Direct resources included were hospitalization, surgical interventions, ambulatory and community care and RA medication. NSAID usage was not included, as most patients used them and usage did not differ significantly between the states. Also excluded were non-medical direct costs and informal care, as these were not collected in the data sets.
The cost of hospitalization was based on the number of in-patient days in different wards and ward-specific daily costs, while the cost of surgical interventions was calculated from the type of intervention and its duration multiplied by the cost per minute of operating theatre use. Out-patient care was based on the number of visits to different health-care professionals. The cost of RA drugs was calculated from the number of months of use of each drug, associated with the cost of standard drug-monitoring protocols in place in the rheumatology departments participating in the cohort studies. Unit costs were taken from hospital accounting data and official price lists [3438].
Indirect costs were calculated as the loss of work capacity of patients in the more advanced disease states compared with patients in state 1, i.e. a HAQ score below 0.6. This is based on the finding that although these patients reported short-term sick leave, their overall work capacity was not different from that of the general population [13, 17]. Economic evaluation in RA should only include productivity losses due to the disease, and it is hence the difference in work capacity in the more severe disease states compared with a baseline (state 1 in our analysis) that is relevant, rather than the absolute work capacity. Therefore, for patients below HAQ 0.6, only short-term sick leave was included. When patients reach the average retirement age in each country, they are excluded from these calculations. Indirect costs were calculated using the human capital approach, in which an individual's productivity is valued at the market price, i.e. at the gross income including employers' contribution, until retirement. For the models, the total number of productive years lost at each stage (Markov states) was compared with the number for state 1, and the difference multiplied by the average gross annual income, including employers' contributions [SEK 327 000 (US$31 145) in Sweden and GBP 17 658 (US$26 355) in the UK] [39, 40].
Direct and indirect costs by disease states are shown in Fig. 4.
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Effectiveness of infliximab
ATTRACT included 428 patients from 34 study sites. Patients received four different active drug regimens (3 or 10 mg/kg, every 4 weeks or every 8 weeks) or placebo, in addition to methotrexate. After a double-blind period of 54 weeks, patients were given the option of continuing on their current treatment for another year, in an open extension.
The main economic evaluation was based on 54 weeks of double-blind treatment, as the number of patients continuing into the second year was limited, reducing the number of patients in each of the Markov states. More importantly, the methotrexate group could not be used reliably as a comparison in the second year as these patients were able to convert to active drug as soon as all patients in the trial had completed the double-blind phase and the blind was broken. We included all patients with follow-up data at 54 months in order to calculate transition probabilities, regardless of whether they had discontinued treatment, as non-compliance is incorporated into the cost of treatment. Patients with missing values were excluded, and transition probabilities were calculated on the basis of 287 patients in the treatment group and 58 patients in the comparator group. As there was no statistically significant difference in efficacy between the four dosage arms of infliximab at the end in the double-blind phase, we merged the groups for the purpose of this analysis. The demographics of patients in ATTRACT are shown in Table 2. There was no statistical difference in the demographics of the full trial population and the patients used in the economic evaluation.
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Basic model
In the basic model, both groups from the clinical trial data were used directly for the first year. For the following years, the Lund and ERAS data were used to simulate a 10-yr follow-up, controlling for the difference in the population in terms of age, sex, disease duration and methotrexate use. In order to model the second year of treatment, a different approach had to be used because of the limited number of patients remaining on methotrexate alone (11), and matched patients from the Lund and ERAS cohorts were used for comparison. These calculations assumed that treatment was stopped after 1 or 2 yr, when no further clinical data were available, and no further treatment costs and effects were therefore assumed; rather, both groups of the trial population followed the development of the epidemiological cohorts.
Alternative model (sensitivity analysis)
As it may be unrealistic to assume that the treatment effect achieved in the trial will be fully maintained when treatment is withdrawn, we present a different modelling approach which incorporates a loss of effect in the year after discontinuation, expressed as faster disease progression than that in the epidemiological cohorts. We calculated the difference in the HAQ changes between the infliximab and methotrexate groups during the clinical trial, and applied the difference (odds ratios for progression) to the Lund and ERAS cohorts for the treatment arm for the first year. Thus, treatment was compared directly with that of the epidemiological cohorts, thereby also eliminating the placebo effect in the clinical trial. The loss of effect at withdrawal during the first year in the trial was already incorporated into the calculations, as the intent-to-treat group was used. Effect loss after the trial was estimated by comparing the HAQ transitions of patients in both groups in the trial who discontinued treatment in the second year but were followed for the entire study period (i.e. with HAQ scores at 102 weeks). A total of 113 patients were available for this analysis, 77 in the active group and 36 in the methotrexate group. We defined improvement as a decline in HAQ score of more than 0.5, while deterioration was defined as an increase in HAQ score by more than 0.5 (i.e. the difference between the Markov states). The difference between the two groups was then applied to the transition probabilities in the cycle following treatment discontinuation, with the assumption that patients on methotrexate alone would not experience a loss of effect, while patients on infliximab would.
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Results |
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Disease progression in the clinical trial is illustrated with the first-year transitions for the infliximab and methotrexate groups (Table 3). The same calculations were performed for the treatment group in the second year. Figures 5
and 6
illustrate the progression of average HAQ levels for the two groups when transitions from ATTRACT were used directly for 1 and 2 yr, respectively, using the basic model illustrated for Sweden.
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In the base case, when all costs were included, the incremental cost in the treatment arm was SEK 8031 (€864) and GBP 6440 (€10 387) in Sweden and the UK, respectively. The cost of infliximab treatment for 1 yr was SEK 71 794 (€7720) and GBP 7616 (€12 284), and treatment thus reduced other costs by SEK 63 736 (€6853) and GBP 1176 (€1897). The QALY gain was 2.48 and 2.98, respectively, the difference being partly due to different discount rates in the two countries. The cost per QALY gained was SEK 32 000 (€3440) and GBP 21 600 (€34 800). When treatment was given for 2 yr, the cost per QALY gained increased to SEK 150 000 (€16 000) and GBP 299 000 (€48 200).
Table 4 shows the cost-effectiveness calculations for the 1- and 2-year treatment scenarios in the basic model, and Table 5
gives the results of the alternative model with a loss of effect at treatment discontinuation. The sensitivity analysis on the cost of infliximab is presented in Table 6
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Discussion |
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Economic evaluation requires that effectiveness be expressed with a single measure, and we therefore used the QALY as the effectiveness measure in the model. The advantage of the QALY is its ability to capture health improvements in terms of both life expectancy and QoL. Thus, the QALY allows comparison of outcomes in different disease areas, a prerequisite for resource allocation. Most reimbursement agencies in countries where economic evaluation is used formally or informally for decision-making therefore prefer evaluations using the QALY. Although the QALY remains somewhat controversial, the difficulty lies less in the concept than in the methods used to assess utility. The EQ-5D has been shown in a very large number of studies in all types of diseases to be a valid instrument and its use is therefore well accepted. In RA in particular, we have shown earlier [13, 17] that the EQ-5D is able to discriminate between patients with differences in HAQ within the same ACR group.
The QALY gain over 10 yr is between 0.2 and 0.3 in Sweden and between 0.3 and 0.4 in the UK, the major reason for this difference being the different discount rates used (3 and 1.5% respectively); for instance, 0.3 discounted QALYs would be 0.4 and 0.35 undiscounted QALYs in Sweden and the UK, respectively, using these rates. The total gain of 0.30.4 QALYs over 10 yr may appear small, even undiscounted. However, the gain has to be considered in relation the total number of QALYs that an average RA patient in this group has over 10 yr, i.e. about 4.5. Undiscounted, this would be a total of 6 QALYs, which compares to about 8 QALYs for a healthy individual of a similar age. Hence, considering an average loss of 2 QALYs over 10 yr due to the disease, a gain of 0.4 QALYs with treatment appears very important.
Costs in RA are clearly driven by the loss in work capacity (indirect costs). We calculated the loss of productivity as the difference in the ability to work of patients with more advanced disease and patients with very limited disability (HAQ <0.6). Thus, productivity losses due to other causes were excluded. Work capacity in the models is based on the cohort studies, and one issue could be that the population in the clinical trial was different. We verified total work capacity (all patients, regardless of age) in ATTRACT by grouping patients into the disease states at baseline and estimating work capacity in the same way as in the cohort studies. The values were very similar, ranging from 60 to 7% in the trial compared with 57 to 0% in the Lund cohort and 54 to 8% in the ERAS cohort. The slightly higher values overall can probably be explained by the higher average age in the cohort studies compared with ATTRACT. However, in the model this has no impact, as age is controlled for.
No indirect costs for premature mortality due to RA were included in these calculations, as evidence on the effect of RA on life expectancy is conflicting. Several epidemiological studies have shown increased mortality in patients with severe RA and the mean standardized mortality ratio has recently been estimated to be 1.87 [46]. Earlier studies showed rates as high as 2.26 [47]. Also, a link between functional status (HAQ) and mortality has been reported [48]. However, more recent studies have not found any effect of RA on mortality [50, 51]. Most importantly, however, the data available do not allow the calculation of an annual age- and gender-specific mortality risk for each of the six disease states in the model.
In our basic analysis, the cost per QALY of 12 yr of treatment with infliximab in Sweden was well within the range of generally accepted cost-effectiveness ratios. When the alternative model was used, 1 yr treatment became cost-saving, and remained cost-saving even when a loss of effect at treatment discontinuation was incorporated in the calculations. The explanation for the difference is that, in the alternative model, the trial effect in the placebo (methotrexate) group is eliminated and the infliximab treatment group is compared directly with the epidemiological cohorts. Thus the difference between the two groups increases.
In the UK, cost-effectiveness ratios were substantially higher in both models. This difference is entirely driven by indirect costs, as direct costs were almost identical in the two countries and cost-effectiveness ratios including only direct costs were therefore in similar ranges. However, in the UK, a much lower proportion of patients in the advanced HAQ states were on early retirement compared with Sweden. For instance, in state 5 (HAQ 2.1 to <2.6), only 7% of patients below 65 yr were working in the Lund cohort, while the proportion in ERAS was 50%. In state 6 (HAQ >2.6) no patient was working in Sweden, while in ERAS the proportion remained at 50%. The most likely reason for this is the limited number of patients in the Lund cohort, in which only a few patients progressed to these very severe states, and those who did were over 65 yr old. Another reason may be that Sweden had a more generous policy for according long-term illness benefits during these years. Lastly, the average annual salary in Sweden was found to be higher than in the UK. As a consequence, with progressing functional disability, the increase in indirect costs was much steeper in Sweden, thereby increasing the savings if the progression of the disease were slowed.
A further important explanation for the differences between the two countries is the discount rate. In Sweden, costs are generally discounted by 3%, while in the UK, according to guidelines from the National Institute for Clinical Excellence (NICE), a rate of 6% is used. Thus, savings achieved over the years through slower disease progression will have a lower net present value in the UK.
We included both direct and indirect costs in our main analysis. In a disease in which the main economic effect is that patients lose their ability to maintain a professional activity, we would argue that indirect costs must be considered when the impact of a treatment is assessed, despite health-care budget considerations. Direct costs are currently very low, as treatment is limited and drugs, both DMARDs and NSAIDs, are generally generic and inexpensive. We did include NSAID use in our costs, as all patients in the cohorts used them at given times regardless of the level of the disease, and costs were minimal. Clearly this will change with the use of the newer cyclooxygenase 2 inhibitors, but it is probable that costs at all levels of HAQ will increase. As Markov models are driven by the difference in costs and utilities between the Markov states, and not by absolute values within the states, our results should not have been affected by this.
The most difficult issue when results from short-term trials are extrapolated to the longer term is the assumptions made for treatment continuation, as no data are available. We therefore present only results for the period during which trial data are available and estimate the effect of the benefit achieved within the trial carried over to a longer period, including, however, a potential loss of effect at treatment discontinuation. It can be argued that it is unrealistic to assume that in clinical practice patients will only be treated for 1 or 2 yr. However, there are no data from which to estimate which patients will continue and whether the treatment will continue to improve symptoms, maintain the effect or lose some of its effectiveness over time. From the second-year extension of ATTRACT, it appears that the effect is maintained over time, and we incorporated this into the estimates, despite the impossibility of using the comparator group for comparison. Compliance observed in the trial was incorporated into the analysis, but it is impossible to predict compliance in clinical practice beyond the trial based on these data. In our opinion, therefore, it is preferable to estimate the cost-effectiveness of the treatment only for the period for which data are available. A similar approach has been taken by another group developing methodologically different models in this field, with comparable results [51, 52].
The results of our models indicate that 12 yr of treatment with infliximab and methotrexate, compared with methotrexate alone, will lead to offsets both in direct and indirect costs. Savings in direct costs are €15002000 in Sweden and up to €800 in the UK and will thus not offset the cost of infliximab. The majority of the savings will come from maintaining the patients' ability to work. However, even when only direct costs are included, the cost-effectiveness ratios remain within the usual range for a treatment to be recommended for use.
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Acknowledgments |
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Notes |
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References |
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