The burden of ankylosing spondylitis and the cost-effectiveness of treatment with infliximab (Remicade®)

G. Kobelt, P. Andlin-Sobocki1, S. Brophy2, L. Jönsson1, A. Calin3 and J. Braun4

Karolinska Institute, Stockholm, 1 Stockholm Health Economics, Stockholm, Sweden, 2 Swansea University, Swansea, 3 Royal National Hospital for Rheumatic Diseases, Bath, UK and 4 Freie Universität, Berlin, Germany.

Correspondence to: G. Kobelt, European Health Economics, Dannemoragatan 16A, 113 44 Stockholm, Sweden. E-mail: Gisela.kobelt{at}he-europe.com


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Objectives. In the past, treatment options for ankylosing spondylitis (AS) have been limited, and the introduction of new treatments such as infliximab will have a noticeable impact on health-care budgets. The objective of this study was therefore to assess the current burden of the disease and estimate the cost-effectiveness of infliximab treatments.

Methods. A cross-sectional retrospective observational study of resource consumption and utility related to disease severity was performed in patients who had participated in a population survey between 1992 and 1994 at the University of Bath and patients regularly followed at the Royal National Hospital for Rheumatic Diseases in Bath for up to 9 years. Mean costs and utility were estimated using a regression model including age, gender, disease duration, disease activity and functional status, and disease development was expressed as annual progression of functional disability. Cost-effectiveness of infliximab was modelled using a 3-month placebo-controlled clinical trial with open 1-yr extension in 70 patients, over a total time frame of 2 yr. In the model, costs and utility controlled for disease severity and age from the observational study were assigned to individual patients. The effect of long-term treatment was evaluated in a hypothetical model over 30 yr.

Results. Fifty-seven per cent of patients answered the questionnaires. The mean age was 57 (S.D. 11.2) yr, 74% were male and mean disease duration was 30.2 (11.7) yr. Mean total costs were estimated at £6765 (S.D. £166). Indirect costs represented 57.9% and non-medical costs such as investments and informal care accounted for 16.5% of total costs. Mean utility was 0.67 (0.21). In the main model, mean costs for untreated patients are estimated at £25,128. For the infliximab group, mean costs (excluding treatment) are estimated at £17,240, a reduction of 31%. Thus, part of the treatment cost was offset by savings in other resources (£7888), leaving an incremental cost of £6214. Treatment increased the number of quality-adjusted live years (QALYs) by 0.175 QALYs, leading to a cost per QALY gained of £35,400 for the first year of treatment. When treatment is assumed to continue for the full 2 yr, the cost per QALY is £32,800. When infliximab infusions are given every 8 weeks instead of every 6 weeks, the cost per QALY is reduced to £17,300. In the long-term model, the cost per QALY is estimated at £9600.

Conclusions. Non-medical costs and production losses dominate costs in AS, and economic evaluation must therefore adopt a societal perspective. The cost of treatment with infliximab is partly offset by reductions in the cost of the disease and patients’ quality of life is increased, leading to a cost per QALY gained in the vicinity of £30,000 to £40,000 in the short term, but potentially below £10,000 in the long term.

KEY WORDS: Cost of illness, Cost-effectiveness, Cost–utility, Ankylosing spondylitis, Infliximab, Modelling


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Prevalence estimates for ankylosing spondylitis (AS) vary across studies and countries, from 0.6 to 1.9% [1–3]. The disease is diagnosed in young adults (although it is often thought to have an onset in late adolescence) and leads to severe functional disability and loss of work capacity [4–8]. Similarly, patients’ quality of life (QoL) is reduced as a consequence of both the loss of physical function and the pain linked to disease activity [9, 10].

In the past, few treatment options were available for AS [11, 12]. Disease-modifying anti-rheumatic drugs (DMARDs) such as sulphasalazine or methotrexate have been shown to have limited effectiveness, reducing treatment options essentially to NSAIDs, physiotherapy and joint replacements. Thus, the cost of AS is currently driven by the cost of the disease and its consequences on work capacity, while treatment costs are rather low. Total direct costs have been estimated to between {euro}1800 and {euro}2800 in three European countries (Belgium, the Netherlands, France) [13] and $1750 per annum in the United States [5].

Recently, anti-tumour necrosis factor-{alpha} (anti-TNF-{alpha}) therapy has been shown to be very efficacious in the treatment of AS [14–17] and the first agent, infliximab, has been approved in Europe. The average cost of infliximab treatment, including an out-patient visit for drug infusion, is estimated at around £12,500 per year (infusions of 5 mg/kg every 6 weeks). Thus, with the introduction of infliximab, direct costs of AS will increase substantially, and the additional cost will have to be weighed against the health gains obtained with treatment.

A number of European countries will demand that the cost-effectiveness of infliximab in the treatment of AS be demonstrated, prior to recommending its unrestricted use. The question of when treatment should be started and who should be treated, at what dose and for how long will be raised and related to cost-effectiveness estimates.

However, in order to perform such an economic analysis, data on the development of the disease, both symptoms and progression, its effect on resource consumption, work capacity and patients’ QoL are required, in addition to clinical data on the effect of treatment [18]. Clinical data are generally short compared with the duration of the disease, but the effect of treatment will be felt beyond clinical trials. By combining epidemiological, economic and clinical data in decision analytic models, it is possible to extrapolate the time frame, generalize the results and investigate different treatment scenarios.

The aims of this study were to investigate the cost of AS in the United Kingdom, focusing on the influence of disease severity on cost and QoL, and to construct a disease model to estimate the cost-effectiveness of infliximab in patients with active unremitting disease. The logic of the model is illustrated in Fig. 1.



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FIG. 1. Structure of the analysis based on the assumption that costs increase while quality of life (utility) decreases with worsening disease. Costs and utilities are collected in large cross-sectional studies and related to measures of disease severity (BASDAI/BASFI). The progression of the disease is estimated using the same measures of disease severity, from epidemiological cohorts or longitudinal surveys. Treatment intervention, based on clinical trial data, reduces the severity of the disease, and will hence reduce disease costs and increase quality of life. Treatment costs might or might not be offset by the reduction in disease costs. If they are, treatment will be cost-saving; if they are not, there will be an incremental cost that has to be related to the health benefit, i.e. the gain in quality of life over a given time period.

 

    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
It has been shown in a number of chronic progressive diseases, including rheumatoid arthritis [19–21], that costs increase as the disease progresses while QoL decreases. We assumed that this would also be the case in AS, with costs and QoL correlated with disease activity and physical function. Thus, a treatment such as infliximab, that has been shown to reduce disease activity and thereby improve functional capacity, would be expected to reduce health-care consumption, maintain the ability to work longer and improve patients’ well-being in the long term. If this effect is to be estimated in a decision analytic model, the key clinical measures relating to disease activity and function must be included in all data sets, and costs as well as QoL must be related to these variables. Also, to increase comparability to treatments in other diseases, QoL should be measured as utility (i.e. preference scores for given health states).

We used three datasets in this study that all included measurement of disease activity and functional ability using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Bath Ankylosing Spondylitis Functional Index (BASFI) respectively [22, 23]: A double-blind, placebo-controlled 12-week clinical trial with a 1-yr open extension [14, 17], a cohort study of 700 patients followed in clinical practice at the Bath Royal National Hospital for Rheumatic Diseases [24] and a cross-sectional survey mailed to 3000 patients with AS in the United Kingdom [25–27].

Ethical approval for the study was given by Bath Royal National Hospital and informed patient consent was obtained from patients when they completed and returned the questionnaires.

Data
Clinical data
The clinical trial randomized 70 patients with confirmed AS (bilateral sacroiliitis ≥grade 2) with active disease (BASDAI of ≥4) to 5 mg/kg infliximab every 6 weeks, with a loading infusion after 2 weeks, or placebo. At the end of the 12-week double-blind phase, all patients were offered infliximab treatment [14]. The economic analysis includes the open extension to 54 weeks for the intervention group, while for the purpose of comparison patients from the placebo group are assumed to receive standard treatment after 12 weeks.

BASDAI and BASFI measurements were available at baseline, weeks 2 and 6 and every 6 weeks thereafter, and all measurements were used in the economic evaluation. Table 1 shows the demographics of the study population and summarizes the results.


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TABLE 1. Clinical data [14, 17]

 
Survey and cohort data
The survey included 2300 patients who had participated in a population survey carried out between 1992 and 1994 at the University of Bath [28], and the cohort of 700 patients regularly followed for up to 9 yr at the Bath Royal Hospital for Rheumatic Diseases [24]. A special questionnaire to elicit patients’ current disease state (BASDAI, BASFI), health-care and private resource consumption related to AS, informal care needs, work capacity and utility (EQ-5D) [29, 30] was mailed in November 2002. The overall answer rate was 57% and 1413 questionnaires were included in the analysis.

For 1100 of the 1413 patients, BASDAI and BASFI data from the earlier survey in 1992–1994 were available and we used these two data points to estimate disease progression as the absolute annual change in functional disability (BASFI). These estimates were verified using the measurements for patients in the cohort study with more than 3 yr of follow-up (n = 493).

Cost data
Unit costs for the individual resources were taken from public sources available mostly on the internet, National Schedule of Reference Costs [31], Unit Costs of Health and Social Care (PSSRU) [32], Health Service Data Base of CIPFA [33], Filey-Therapist, British National Formulary (BNF) [34] and National Labour Statistics [35]. Costs earlier than 2002 were adjusted to 2002 using the Consumer Price Index.

The cost of hospitalization was based on per diem costs of the specific ward, except when patients had a surgical intervention where the cost of an admission (DRG) was used. Costs for out-patient visits and community care were directly available from the above sources. Prescription medicines in the higher price range (e.g. proton pump inhibitors, cyclo-oxygenase-2 (COX-2) inhibitors, DMARDs, etc.) were costed individually, at the standard recommended daily dose in the BNF, and multiplied with the number of days. Generic prescription drugs or low-priced products were grouped and assigned the cost of the most commonly mentioned product. The cost of over-the-counter (OTC) medication and other items (e.g. investments, etc.) was based on patients’ estimates. Indirect costs included short-term sick leave, reductions in working time due to AS and early retirement. The loss of production was estimated using the human capital approach, applying an hourly wage of £13.22 for men (40.9 h/week) and £10.73 for women (37.5 h/week), and 47 working weeks per year. Although other approaches to the valuing of the loss of production are being discussed, this method has been recommended by the National Institute of Clinical Excellence (NICE) for the UK [36]. Informal care was considered a direct cost and its cost estimated using the concept of opportunity cost calculated as the average disposable after-tax income estimated at 40%. Other methods to value informal care exist, and the most frequently used is the concept of replacement cost where care given by family and friends would have to be provided by health-care professionals. However, this method leads to substantially higher costs.

Burden of illness analysis
The survey collected resource consumption for the preceding 3 months for most items, with the exception of medication which was assessed for the previous month. For each type of resource, the proportion of users in the sample and the mean utilization per patient and year was calculated, and the average total annualized cost per patient estimated. Loss of work capacity was expected to be the largest part of the costs, and the proportion of patients working at different levels of disease activity or functional disability was therefore calculated. Utility scores were calculated as mean values for all patients as well as by disease severity.

Cost-effectiveness models
Structure
Deteriorating physical function and high disease activity were expected to be the major drivers of resource utilization. However, the progression of functional disability is slow with disease activity fluctuating over time [37] and it is thus difficult to estimate the impact of a short clinical trial on the future development of the disease without natural history data covering more than a decade. We therefore limited the main cost-effectiveness model to 2 yr, but present a second hypothetical model based on epidemiological data to illustrate potential long-term treatment and compliance with treatment.

The main model, illustrated in Fig. 2, is non-parametric and uses patient-level data rather than means, as costs and utilities are skewed. The disease development of each patient in the clinical trial is followed on an individual basis during the intervention and in the extrapolation beyond the trial. To estimate costs and utilities, each patient is matched with all patients in the survey with the same characteristics (age, gender, disease duration, BASDAI and BASFI), and assigned these patients’ costs and utilities. At each measurement of BASDAI and/or BASFI performed in the trial or estimated in the model, a new match is performed and costs and utilities adjusted accordingly.



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FIG. 2. Structure of the main model. For the first 12 weeks, BASDAI/BASFI scores from the double-blind clinical trial are used [14]. After 12 weeks, patients in the placebo group revert to their baseline over a period of 6 weeks and then remain stable. Patients in the treatment group continue treatment for 42 weeks and the BASDAI/BASFI scores from the open trial extension are used [17]. After 54 weeks, patients are assumed to withdraw from treatment and revert to their baseline over a mean period of 12 weeks and then remain stable. The model runs for 2 yr, in order to allow for different assumptions regarding the loss of treatment effect.

 
The first year is entirely based on the clinical trial and the data are extrapolated to a second year to incorporate assumptions regarding treatment withdrawal. All individual BASDAI and BASFI measurements from both the intervention and placebo groups are used for the first 12 weeks. However, as the baseline scores of the two groups differed, the scores of patients in the placebo group were adjusted to provide an identical baseline for all patients. After 12 weeks, individual patient data from the 54-week open extension trial were used for patients on treatment, while patients in the placebo group were assumed to revert to their baseline over a period of 6 (12) weeks and then remain stable. In the absence of treatment data beyond 1 yr at the time of this analysis, patients in the treatment group are also assumed to withdraw from treatment and revert to their baseline over an average period of 12 weeks. This assumption is based on clinical observation in a limited number of patients. Patients withdrawing from treatment during the trial revert to their baseline scores and are incorporated into the no-treatment group.

In the illustrative long-term model, the first 12 weeks are identical to the main model. At the end of the double-blind period of the trial, patients enter a Markov model with three states for ‘on treatment’, ‘off treatment’ (i.e. conventional care) and ‘dead’. The model runs in annual cycles until fewer then 5% of patients remain on treatment (30 yr). At the start of the Markov model, patients are assigned the mean 12-week BASDAI/BASFI scores of the treatment and placebo groups (3.3/3.3 and 5.7/5.4 respectively) and the mean age of the trial population (40 yr), and their disease then progresses according to the mean absolute annual change in BASFI estimated from the survey and cohort data. In the base case, patients treated with infliximab and patients with conventional care progress at the same rate, which represents the most conservative estimate for infliximab. Therefore, a scenario is also presented with no progression for patients on treatment. Ten per cent of patients withdraw from treatment every year, estimated from treatment discontinuations observed during 2 yr in the open trial extension, where discontinuation after 1 yr was 22% and after 2 yr 30% (data on file, J. Braun et al.). Dropouts revert to the mean BASFI/BASDAI scores of the no-treatment group over a period of 12 weeks.

Individual costs
Costs were not normally distributed, and a two-step regression model was used to relate individual cost components to individual patients. First, the probability that a patient used a given resource was estimated using a logit model, followed by the estimate of the expected cost of the resource (quantity x unit cost) and multiplication of the two terms. Both calculations were controlled for age, gender, disease duration, BASFI and BASDAI.

The cost of infliximab treatment was based on the actual quantities of drug used during the trial and the open extension, and a mean cost for infusions of 5 mg/kg every 6 weeks was used in the long-term model. Sensitivity analysis for infusions every 8 weeks is presented. The cost per infusion was calculated from the list price of infliximab (£451.20/100 mg vial) and the cost of an out-patient visit to the hospital was added. The cost of adverse events was estimated by assessing the treatment requirements for each event observed in the first year of the clinical trial. Total costs of all adverse events were then calculated and assigned to the treatment group as a mean cost per patient (£73.50) to all patients who started infliximab treatment, regardless of whether they experienced an adverse event or not. This was necessary to avoid adverse event costs for patients withdrawing from treatment being incorporated into the placebo group, which would bias the result in favour of treatment. In the main analyses, costs are presented from a societal perspective and are discounted with 6%, as requested for economic analysis in the UK at the time of the analysis [36]. However, a sensitivity analysis using a discount rate of 3% for both costs and utilities, as is used in most countries, is also presented.

Utilities
Utilities were not normally distributed, making it difficult to use a linear regression model. However, there was a clear correlation of BASDAI and BASFI with utilities. Utility scores were therefore grouped into a 5 x 5 matrix based on BASDAI and BASFI as shown in Fig. 3 and individual patient's scores calculated by linear interpolation within this matrix. Utilities are discounted with 1.5% (3%).



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FIG. 3. Utility matrix. Patients are grouped into 25 disease states according to their BASDAI/BASFI scores. The utilities of individual patients are calculated by linear interpolation between the values in this matrix.

 

    Results
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Burden of illness
The majority of the 1413 patients answering the survey were male (74%), with a mean age of 57 yr (S.D. 11.2) and mean disease duration of 30.2 yr (S.D. 11.7). Slightly over half of respondents aged less than 65 yr were working (51%) and more than half had experienced flares in the preceding 3 months (55%). The mean utility derived from the EQ-5D health state system was 0.67 (S.D. 0.21), and assessment of the current health state on the Visual Analogue Scale (VAS) was 54.3 (S.D. 28.1).

The mean BASDAI score was 4.2 (S.D. 2.3) and the mean BASFI score 4.4 (S.D. 2.8), but the sample comprised patients at all levels of disease severity measured by either BASDAI or BASFI, as shown in Table 2. Utility decreased in a similar fashion with increasing severity on both measures. Similarly, work capacity was lower for patients with more severe disease, but disease activity appeared to have an earlier impact than functional disability. Age and disease duration appeared to be related to function, but not to disease activity.


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TABLE 2. Utility and work capacity by severity of the disease (n = 1413)

 
Table 3 shows the cost estimates. Mean annual cost per patient was estimated at £6165. This is lower than the levels found by other authors, but other studies have shown that costs in the UK tend to be at the low end [21, 38, 39]. Indirect costs represented the majority of costs, driven by early retirement due to AS (23.1% of the sample). Direct costs were dominated by hospital costs (which included 22 hip or knee replacements within the 3-month period), while drugs represented only 2.5% of total cost. Most patients used medication, predominantly anti-inflammatory drugs [non-steroidal anti-inflammatory drugs (NSAIDs) 44.1%, COX-2 inhibitors 15.3%, steroids 3.6%] and gastro-protectants (21.2%). Only 13.5% of patients used DMARDs, while 33.3% used OTC preparations.


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TABLE 3. Resource consumption and mean annual cost per patient (n = 1413), 2002

 
Costs were highly correlated with both measures of disease severity, but functional capacity was found to be a much stronger predictor of high costs, as shown in Figs 4 and 5.



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FIG. 4. Influence of disease severity on costs. Mean annual total cost per patient by levels of disease activity and functional disability. BASDAI exerts a stronger influence on costs already at low levels, while BASFI drives the cost increase as the disease worsens.

 


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FIG. 5. Influence of disease severity on costs. This figure shows the mean annual cost for different types of resources for three hypothetical patient groups with mild, moderate and severe disease, defined as BASDAI/BASFI 2/2, 4/4, 8/8 respectively.

 
Cost-effectiveness
In the main model, 35 patients start on treatment, at their individual BASDAI and BASFI scores. As in the clinical trial, two patients withdraw from treatment during the double-blind phase and nine during the open extension period. After 54 weeks, all patients are assumed to withdraw from treatment. Patients who stop treatment are assumed to return to their baseline scores over a mean period of 12 weeks and remain at that level thereafter. Patients in the placebo group return to their baseline values within 6 (12) weeks after the end of the double-blind phase and remain at that level for the remainder of the model to form a hypothetical comparator group.

Results are shown in Table 4. In the base case, total 2-yr costs in the treatment arm are estimated at £17,240 (excluding the cost of infliximab) compared with £25,126 in the placebo group. Cost offsets amount to £4731 and £3155 for direct and indirect costs respectively. Treatment costs amount to £14,100, leading to an incremental cost of £6214 (discounted by 6%). When the calculation is limited to 54 weeks, thus excluding any potential carry-over benefit of the treatment, the total incremental cost amounts to £7341. The total gain in quality-adjusted life-years (QALYs) over 2 yr was estimated at 0.175 (discounted by 1.5%), equivalent to more than 2 months at full health. When a discount rate of 3% is used for both costs and effects, the incremental cost is £6624 for a QALY gain of 0.174.


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TABLE 4. Cost-effectiveness results, 2002

 
Progression of functional disability measured with BASFI in the sample of 1110 patients was estimated at 0.07 points. Patients with BASFI scores below 4.0 at baseline progressed slightly faster (0.1 points), while patients with scores above 7.0 appeared to be stable. These estimates were similar to the progression of 0.08 points seen in the follow-up cohort at the Bath hospital. When only patients with active disease (BASDAI ≥4.0) are included in the calculations, the annual progression is estimated at 0.054 and 0.059 in the two samples respectively.

The long-term cost-effectiveness model uses an annual progression of 0.07 on BASFI and sensitivity analysis is presented for 0.05. When simulations are run for 30 yr, the total incremental cost with treatment is estimated at £25,200, for a QALY gain of 2.62, leading to a cost per QALY gained of £9600. Under the assumption that patients’ BASFI would remain stable while on treatment, the cost per QALY gained with treatment is reduced to £2800. When the annual drop-out rate is increased from 10% to 15%, the cost per QALY gained is £700.


    Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
On the basis of data from a large cross-sectional survey in the United Kingdom and the first randomized controlled trial with infliximab in AS [14, 17] we estimated the costs, the outcome and the cost-effectiveness of this therapy in patients with unremitting disease using two outcome models.

Economic evaluation in AS, as in all chronic progressive diseases, presents a number of challenges. The disease affects a number of body functions and systems and different symptoms are present permanently or intermittently, while at the same time the disease progresses to increased functional disability. Cost-effectiveness analysis must thus take into account both short-term disease activity and long-term disease progression. Often these are correlated, such as BASDAI and BASFI in our sample (r2 = 0.7), but it is not always fully elucidated how disease activity affects progression. We have tried to take all disease variables into account, but several issues require discussion.

In our study, costs and quality of life (utility) were correlated with both disease activity and functional impairment. However, while utility decreases at a similar rate when correlated with BASDAI and BASFI (Table 3), the effect on costs comes at different points in time (Fig. 4). Disease activity affects costs considerably, even at low levels of BASDAI, but the increase with increasing levels of BASDAI is moderate. Contrary to this, costs at the lower end of the BASFI are limited, but the increase with increasing functional disability is exponential, and over time, costs are thus clearly driven by BASFI. These results may, however, also indicate that the two scales are not linear, and that there may be a substantial influence of physiotherapy on this domain.

It is thus necessary to take into account both measures for calculating costs and utilities for different levels of disease severity. We have estimated costs for individual patients in the models as a function of both BASDAI and BASFI, as well as age, gender and disease duration. As costs were highly skewed, as is generally the case, we used a two-step regression model, controlling for these parameters at each step. In the cost-effectiveness model, each patient from the clinical trial was then assigned the costs and utilities relative to the individual disease status and personal characteristics, based on all similar patients in the survey. This is to our knowledge a novel way of assigning costs to patients in clinical trials, and it has several advantages. Firstly, particularly when dealing with small numbers of patients such as in the clinical trial used in this analysis, it allows one to assign costs that match a patient's characteristics, but that are calculated from much larger samples, and thus avoid the effect of outliers. Second, the method takes into account that only a fraction of patients use a given resource at any given point in time, thus avoiding the problem of mean values based on highly skewed data. Third, it allows one to vary the costs according to small changes in disease parameters, and to adapt the calculations to different patient populations.

Although the calculations could be based on a very large sample of patients, it did not appear possible to estimate utilities using regression analysis incorporating both BASDAI and BASFI. When patients were grouped into a matrix according to BASDAI and BASFI points, some cells had a very limited population, particularly in the higher scores. We therefore preferred to use two-point steps to calculate a utility matrix and interpolate between these values according to the scores of the individual patients, thus again eliminating the impact of highly skewed data and outliers.

Our analysis combines data from a clinical trial, an epidemiological cohort and an observational survey, and the mean disease scores and patient characteristics in these data sets differ substantially. Patients in the cross-sectional survey were considerably older and had the disease for longer than patients in the clinical study, but had lower BASDAI and BASFI scores. The same was true for patients in the epidemiological cohort, although the difference was much smaller. However, for the estimates of cost and utility this is of no concern, as patients represented the full span of the two disease indexes and a wide range of ages (28–89 yr) and disease duration (1–65 yr). Thus, patients from the clinical trial could easily be matched with groups of similar patients from the survey. However, we did not control the calculation of annual disease progression for age, and it is conceivable that the type of patients enrolled in the clinical trial would develop functional disability at a faster rate than the survey cohort. In such a case, our analysis would have underestimated the benefit of treatment, as it is also more likely that functional ability can be improved in earlier disease when damage is more limited.

The cost-effectiveness models are based on a limited clinical trial, and results will therefore not necessarily apply to a wide patient population. However, the trial included the types of patients who would qualify for treatment with infliximab, and it is thus reasonable to assume that the treatment effect will be similar in clinical practice. At the time of our analysis, detailed data were available only for the first year of treatment. Our main analysis is therefore based on 1 yr of treatment only, with patients stopping treatment at the end of the clinical trial and returning to their baseline values within a few weeks. It is, however, clearly unrealistic to assume that patients who respond to treatment will discontinue after 1 yr, but on the other hand it is also not realistic that patients who do not have an adequate treatment response would remain on treatment for 1 yr in clinical practice. Thus, analyses beyond the clinical trial are speculative in terms of which patients will continue, what the treatment effect will be, at what rate patients will discontinue over time and what adverse reactions may occur. Nevertheless, we present some hypothetical analyses incorporating treatment continuation to 2 yr and beyond. Preliminary data from the second and third year continuation of the clinical trial suggest that our estimates are close to what was observed (data submitted).

To estimate the long-term effect, we have used a model based on the progression of functional disability. Functional capacity (BASFI) is the strongest driver of costs over time, as disease activity (BASDAI) fluctuates, due likely to flares. However, for given levels of BASFI, costs and utilities have been calculated conditional upon BASDAI, age and disease duration, thus taking disease activity into account. The annual worsening of functional capacity, calculated from two measurement points 8 yr apart for 1110 patients, was found to be +0.07 BASFI. This is similar to the results found by Taylor et al. [37]. Patients at higher BASFI levels had an overall slower progression, as had patients at higher BASDAI, indicating the correlation between the two measures. Not surprisingly, patients in the hospital cohort progressed slightly faster (0.08 BASFI), as they most likely represent a more severe patient population. The model uses a progression of +0.07, with a sensitivity analysis for +0.05. This is likely to be a conservative estimate that might underestimate the benefit of treatment, as it is patients with more active disease and potentially faster progression that qualify for infliximab treatment. On the other hand, a conservative estimate might compensate for the possibility that patients were enrolled into the clinical trial while in a flare, thus with a temporarily high disease activity only. However, data from the hospital cohort indicate that patients’ disease activity, without treatment, seems to fluctuate only slightly around a given, more constant level [27, 37]. In our base case analysis we also made the very conservative assumption that patients’ functional disability will progress at the same rate whether on treatment or not. Thus we have only included an initial treatment benefit, such as shown in the clinical trial, without incorporating any benefit beyond the trial, even when on treatment. This is consistent with our view that treatment effects should not be based on assumptions. It is, however, likely that this does not represent reality and underestimates treatment benefits, as the second and third year extensions of the clinical trial has shown that patients’ BASFI and BASDAI levels remain essentially stable while on treatment.

A major issue in economic evaluation is to account for adverse reactions. Often it is not clear whether events are related to the treatment or not, particularly during open studies, and frequently no data are available as to the clinical management of such events. The issue is particularly difficult when using very limited samples of patients with severe and sometimes long-standing disease, and the results of the analysis could be heavily influenced by co-morbidity in the sample. In the clinical trial used in our analysis, most adverse events occurred during the first year, and with the exception of one patient with tuberculosis, the majority were mild and transient. Infusion-site reactions occurred in two patients, lung granulomatosis, skin lupus, liver enzyme elevation, leucopenia and herpes in one patient each. Three cases of arthritis and one case of pancreatitis were considered to be unrelated and excluded from the calculations. These data are corroborated by results from the ASSERT study where 277 patients were treated with infliximab over 6 months and where almost no adverse events were observed. This differs from the incidence of adverse events in rheumatoid arthritis (RA) patients treated with infliximab. However, it has to be borne in mind that RA patients treated with anti-TNF drugs are overall older, with longer-standing disease and higher co-morbidity than the AS patients included in the clinical trial. In order to assign adverse event costs only to the infliximab group in our model, a mean cost based on standard clinical management for all events that occurred was assigned to all patients who started treatment.

Finally, our analysis assumes that patients’ costs and utilities will change as their BASDAI/BASFI scores change. This is likely to happen for direct costs not related to infliximab treatment as well as sick leave, as has been shown in a recent study in RA patients with severe and long-standing disease treated with anti-TNF drugs [40]. Also, a highly significant reduction in short-term work absence has been shown in the AS patients included in our analysis, from a mean of 11.1 to 0.6 and 2.9 days in the first and second year, respectively [41]. The same effect was seen on hospitalization, with 10% of the sample requiring hospitalization in years one and two compared with 41% in the year prior to the study [41]. The effect on costs is, however, less obvious for long-term sick leave, as it may take some more time for patients to return to work. In this case, the cost-effectiveness ratio will lie somewhere between £73,300 (direct costs considered only) and £35,400 (all costs). However, patients in the trial were relatively young and a majority was male, making a return to work more likely than what was observed, for example, in older patients with long-standing RA [40].

Although these analyses are based on a single small clinical trial, cost and utility estimates incorporate a much larger sample of patients, thus increasing the stability of the results. Nevertheless, the results can only be considered representative for the type of patients with unremitting disease included in the clinical trial, and more data for larger groups of patients are required to confirm the findings. A cost-effectiveness ratio will not per se provide information on whether a treatment is cost-effective or not. One approach often used to imply acceptability of a treatment is to compare the cost-effectiveness ratio with ratios obtained with other treatments, in other diseases. In the United Kingdom, recent recommendations by NICE for treatments to be used within the National Health Service appear to reveal a threshold of about £30,000 per QALY. This level would indicate that treatment of AS with infliximab is cost-effective from the societal perspective.


    Acknowledgments
 
This study was supported with an unrestricted grant from the Schering Plough Corporation, but they did not influence findings or interpretation.

J. Braun has worked as a consultant for Centreor, Schering Plough, Amgen, Wyeth and Abbott. The other authors have declared no conflicts of interest.


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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Submitted 18 January 2004; revised version accepted 13 May 2004.