RHEUMTOLOGY Rheumatology 2011;50:iv39 iv47 doi:10.1093/rheumatology/ker245 Modelling the cost-effectiveness of biologic treatments for psoriatic arthritis Laura Bojke 1, David Epstein 1, Dawn Craig 2, Mark Rodgers 2, Nerys Woolacott 2, Huiqin Yang 2 and Mark Sculpher 1 bstract Objectives. probabilistic model was developed to determine the cost-effectiveness of three biologics, etanercept, infliximab and adalimumab, compared with palliative care for the treatment of active and progressive Ps in patients who have an inadequate response to standard treatment (including DMRDs). Methods. previous model was revised to evaluate the impact of biologics on both skin and joint disease and to include new evidence from the clinical review and evidence synthesis. Initial response to biologics was determined using the Ps response criteria. The impact of biologics on the arthritis component of the disease is then modelled via a change in the HQ and the impact of the psoriasis component measured using the Psoriasis rea and Severity Index. Results. For Ps patients with mild to moderate skin disease, the incremental cost-effectiveness ratio (ICER) for etanercept vs palliative care is around 18 000, and the ICER for infliximab vs etanercept is around 44 000 per quality-adjusted life year (QLY). dalimumab is extendedly dominated. The probability that etanercept is cost effective is 0.436 at a threshold of 20 000 per QLY. Etanercept is also likely to be cost effective for patients with moderate to severe psoriasis or negligible skin involvement. Conclusions. Further investigation is required to reduce uncertainties around a number of model parameters, in particular the length of time over which biologics are assumed to be effective and the progression of HQ on and off treatment. Key words: Cost-effectiveness, Biologics, Psoriatic arthritis, Decision model. Introduction Ps is defined as a unique inflammatory arthritis affecting the joints and connective tissue and is associated with psoriasis of the skin or nails [1]. The prevalence of psoriasis in the general population has been estimated to be between 2 and 3% [1], and the prevalence of inflammatory arthritis in patients with psoriasis has been estimated to be up to 30% [2]. In the UK, DMRDs are often used to treat active and progressive Ps. For patients that have an inadequate response to DMRDs, biologic agents that target tumour necrosis factor (TNF) are available. The economic costs of Ps are likely to be substantial. In the US, the mean annual direct (health and social care) 1 Centre for Health Economics and 2 Centre for Reviews and Dissemination, University of York, Heslington, York, UK. Submitted 2 February 2011; revised version accepted 7 June 2011. Correspondence to: Laura Bojke, Centre for Health Economics, lcuin Block, University of York, Heslington, York YO10 5DD, UK. E-mail: laura.bojke@york.ac.uk cost per patient with Ps was $3638 according to data from Medstat MarketScan in 1999 2000 [3], but similar data are not yet available for the UK. Expenditures on biologic therapies have been increasing rapidly in recent years [4], although this might be at least partly offset by cost savings elsewhere [5]. The cost-effectiveness of the biologics etanercept and infliximab has been previously assessed by the National Institute for Health and Clinical Excellence (NICE) [6]. However, this did not include the impact of biologics on the psoriasis component of Ps. In addition, since this appraisal was published, another biologic, adalimumab, is also available for the treatment of Ps. To address these issues, a new decision model was constructed to determine the cost-effectiveness of the biologics etanercept, infliximab and adalimumab for the treatment of active and progressive Ps in patients who have an inadequate response to standard treatment (including DMRD therapy). The model was developed alongside a systematic review and synthesis of clinical evidence and a! The uthor 2011. Published by Oxford University Press on behalf of the British Society for Rheumatology. ll rights reserved. For Permissions, please email: journals.permissions@oup.com
Laura Bojke et al. systematic review of the cost-effectiveness literature, which was undertaken to inform a NICE appraisal. This article reports the methods and results of the de novo economic model, which updates a previous model [7] by incorporating the biologic adalimumab, incorporating the effect of biologics on the psoriasis aspect of the disease [measured using the Psoriasis rea Severity Index (PSI)], incorporating any additional trials and updating of model parameters, including withdrawal rates, elicited evidence on rebound after treatment withdrawal, costs of disease and natural history data. Methods Overview probabilistic cohort model tracks patients with Ps over a lifetime (40 years). Patients either receive a biologic treatment (etanercept, infliximab or adalimumab) or palliative care (no biologic therapy). The model is implemented in the R programming software. The structure and events in the model aimed to be consistent with licensed indications and current British Society of Rheumatologists (BSR) [8] and British ssociation of Dermatologists (BD) [9] guidelines for the use of biologics in Ps [7]. The model adopts the perspective of the UK National Health Service (NHS) and personal social services to quantify costs and health outcomes are measured as quality-adjusted life years (QLYs). The price year assumed for costs is 2008/2009 and the annual discount rate is 3.5% [10] for both costs and QLYs. Initial response to biologic treatment is determined using the Ps response criteria (PsRC). The impact of biologics on the functional status (arthritis) component of the disease is then modelled via a change in the HQ, which ranges from 0 to 3, with 3 being the most severe state. The impact of the psoriasis component of the disease is measured using the PSI. The mean age of the population is assumed to be 47 years, with at least 7 years since diagnosis of Ps, based on the average characteristics of participants in the randomized controlled trials (RCTs) [7]. Patients fulfil the BSR criteria in terms of previous therapies [7]. In the base case, the HQ at the start of the model is 1.05, based on the average in the RCTs [7]. We assume patients in the base case have mild to moderate psoriasis with a PSI score of 7.5 (Ian Bruce, rthritis Research UK Epidemiology Unit, School of Translational Medicine, personal communication, 20 November 2009). Subgroups are also presented by varying the baseline HQ and PSI scores to reflect more or less psoriasis involvement. Model structure The model structure is shown in Fig. 1. The base case model assumes that those with a PsRC response at 3 months will continue on biologic treatment. The response time is consistent with the trials and the accepted FIG. 1Model structure. Figure reproduced with permission from Rodgers M, Epstein D, Bojke L et al. Etanercept, infliximab and adalimumab for the treatment of psoriatic arthritis: a systematic review and economic evaluation. Health Technol ssess 2011;15:1 329. Cycle 1 Months 1 3 Cycle 2 Months 3 6 Biologic j No PsRC PsRC PSI 75 No PSI 75 PSI 75 C C PSI 75 only: withdrawn from biologic j Response of neither: withdrawn from biologic j Response of both: continue on biologic j No PSI 75 B p.w. p.w. B Response of PsRC only: continue on biologic j No treatment N N iv40
Cost-effectiveness of biologic treatments initiation period according to BSR guidelines [11]. Those who do not respond according to PsRC will discontinue biologic treatment and switch to palliative care (with associated natural history progression see Fig. 2). For those initially receiving palliative care and those failing to respond according to PsRC, the arthritis component steadily deteriorates over time. The psoriasis component of the disease is assumed to remain constant. Following a PsRC response, or no response to biologics according to PsRC, the impact of treatment on the two aspects of Ps are modelled: the arthritis and the psoriasis components. Change in HQ score is assumed to be relative to baseline HQ. For PsRC responders, there will be an HQ gain that corresponds to a drop in HQ score. There is very little data to inform whether patients maintained on biologic therapy will maintain the initial improvement in HQ over the long term. Previous models have assumed that the initial gain is maintained while the patient continues with biologic therapy, and this is the base case in the current model (Fig. 2). Opinions were elicited from rheumatologists to inform this assumption [12] (see Rodgers et al. [7] for further details). For PsRC non-responders, a slight HQ gain is estimated in the initial (3-month) treatment assessment period, after which they will no longer receive biologics and will switch to palliative care and the associated natural history progression of HQ. The psoriasis component of the disease is modelled via the PSI. patient who achieves a PSI of 75 has gained at least a 75% improvement in psoriasis compared with baseline PSI. Patients who do not achieve a PSI 75 response will nevertheless have some proportionate gain in PSI while they continue taking a biologic, though this will be <75% improvement (see Rodgers et al. [7] for further detail). QLYs associated with each treatment strategy are calculated by mapping the calculated HQ and PSI scores onto utilities (see below) and are then transformed into QLYs over a lifetime. The base case model assumes a constant rate of withdrawal from biologics after 12 weeks (for those with an initial PsRC response). Withdrawal might occur for lack of continuing efficacy (secondary non-response), adverse events or other reasons. In this model, patients are assumed to return to palliative care after withdrawal from biologic therapy. There is little evidence about patient outcomes (known as rebound) after withdrawal from biologic therapy. Other models have assumed either that patients return to their baseline HQ (rebound equal to initial gain) or that patients rebound to the HQ score that would have been expected had they never taken biologic therapy (rebound equal to natural history). In the base case, it is assumed that rebound is equal to initial gain in terms of HQ and PSI scores (Fig. 2). This assumption was informed by elicitation from experts (see Rodgers et al. [7]). Patients with Ps have been found to have lower life expectancy than the general population [13]. However, there is no evidence that biologics affect mortality. The decision model assumes no difference in mortality rates between treatments, or between biologic treatments and no treatment. ll-cause mortality was estimated from UK life tables. Gompertz function was fitted to these data (Table 1). FIG. 2Illustration of the progression of arthritis according to HQ scores. Figure reproduced with permission from Rodgers M, Epstein D, Bojke L et al. Etanercept, infliximab and adalimumab for the treatment of psoriatic arthritis: a systematic review and economic evaluation. Health Technol ssess 2011;15:1 329. 3 2.5 HQ natural history 2 HQ if withdrawn at Year 5 I 1.5 1 0.5 HQ established on drug (zero progression) 0 0 10 20 30 40 50 Year iv41
Laura Bojke et al. TBLE 1 Model data Description Mean SE Distribution Source Change in cost for 1 U change in HQ 103 67 Normal Kobelt et al. [54] Three-month cost for mild-to-moderate 198 9 Normal Ref costs [56] psoriasis if uncontrolled by biologics Three-month cost for psoriasis in remission 16 1 Normal Hartman et al. [58] Change in HQ while on treatment per 3-month 0 0.02 Normal Expert elicitation period Change in HQ while not on treatment per 0.018 0.007 Gamma NOR data 3-month period Log withdrawal rate from biologics per year 1.823 0.2044 Normal Registers Probability of PsRC response on placebo 0.249 0.0384 Beta Evidence Change in HQ given a PsRC response on 0.2436 0.04746 Normal synthesis placebo Probability of PSI 75 response on placebo 0.044 0.009 Beta Etan Inflix dal Cost of drugs (first 3 months) 2495 5523 2495 Normal BSR guidelines Cost of drugs for Months 4 6 2443 2965 2443 Normal and BNF Cost of drugs, subsequent 3 months 2385 2965 2385 Normal Probability of PsRC response on biologic 0.713 0.795 0.587 Beta Evidence Change in HQ in first 3 months given no 0.190 0.194 0.130 Normal synthesis PsRC response on biologic Change in HQ in first 3 months given 0.630 0.657 0.477 Normal PsRC response on biologic Probability of PSI 75 response on biologic 0.1768 0.7687 0.4772 Beta Estimating QLYs The effectiveness parameters of the model were obtained from published literature, manufacturers parameter estimates, evidence synthesis and a structured elicitation of expert opinion. Clinical effectiveness Bayesian mixed treatment comparison [14] was used to generate the following parameters for the decision model (for each biologic and for palliative care): the probability of PsRC response at 12 weeks, probability of achieving PSI 50, 75 and 90 response at 12 weeks and the associated HQ for PsRC responder/non responder (see Rodgers et al. [7] for further detail). Data were used from six RCTs comparing one of the three biologics to placebo ([15 21], IMPCT [randomized period] [22 33], IMPCT 2 [randomized] [34 41], DEPT [42 50], Genovese 2007 [51]). The analysis was undertaken using WinBUGS version 1.4.2 [52]. The probabilities of PsRC and PSI 75 responses may not be independent, and the model incorporates an estimate of this correlation based on data provided to the authors by one of the manufacturers (bbott Laboratories) [42]. Impact of withdrawals from biologics For patients who respond to biologics according to PsRC, there is an ongoing risk of withdrawal from biologic therapy at some point in the future (post 12-week assessment period). The rate of withdrawal is estimated from a meta-analysis of registry data from several countries [7] and is assumed to be constant after the first 12 weeks. s these data were not randomized, the choice of therapy may be subject to selection bias, and therefore these data were not considered reliable enough to estimate whether withdrawal rates differed between biologics. Natural history HQ progression while on palliative care (natural history) was estimated from patients described in the Norfolk rthritis Register (NOR) who, as far as was possible to determine, matched the licensing indications for a biologic drug, but were not using one [7]. HQ was estimated to increase (worsen) over time, with a 12-week HQ increase of 0.018. Utilities HQ and PSI scores are mapped onto utilities from data provided by one of the manufacturers (Wyeth), who carried out linear regressions of the EQ-5D utility (EuroQol Group) vs HQ and PSI in participants in key RCTs. n interaction term (HQ*PSI) was also included in the regression, but was dropped from the final analysis because the coefficient was small and insignificant [7]. The base case utility function was: Expected utility ¼ 0:897 0:298 HQ 0:004 PSI ðseþ ð0:006þ ð0:006þ ð0:0003þ Table 1 shows a summary of parameter values for the model, including their sources. For further details, see Rodgers et al. [7]. iv42
Cost-effectiveness of biologic treatments Estimating costs Drug acquisition costs and costs of administration and monitoring were obtained from BSR recommendations and pharmaceutical list prices [53]. The health service costs of treating arthritis were measured from a UK-based study that estimated the effect of HQ on costs in patients with R [54, 55]. The NHS costs used for treating mild to moderate psoriasis in patients who do not use biologics or who do not respond to biologics were obtained from NHS unit costs of phototherapy [56] and a UK RCT [57]. nalytical methods ny uncertain parameters in the model were represented by probability distributions. For probabilities (e.g. PsRC response), a beta distribution was assigned. For continuous measures such as the rate of change of HQ without biologic therapy, a gamma distribution was assigned. This ensured that all values were strictly positive. ll other uncertain parameters were assigned normal distributions, with the mean and S.E. shown in Table 1. Probabilistic sensitivity analysis was carried out using Monte Carlo simulation. The results of the model are presented by first reporting mean lifetime costs and QLYs for the four strategies and then by comparing their cost-effectiveness, estimating incremental cost-effectiveness ratios (ICERs) using standard decision rules [59]. lthough NICE does not specify a particular cost-effectiveness threshold, a strategy is more likely to be considered cost effective if the ICER is < 20 000 per QLY, and less likely to be considered cost-effective if the ICER is > 30 000 per QLY [10]. The decision uncertainty is shown as the probability that each intervention is the most cost effective for a given cost-effectiveness threshold. Results Base case results The expected lifetime costs without biologics (palliative care only) are around 42 000 in the base case for a patient with Ps and mild to moderate psoriasis (Table 2). Total costs for all of the biologics are higher than this. The lifetime discounted acquisition, administration and monitoring cost of infliximab is around 52 000, of etanercept is about 33 000 and of adalimumab is about 27 000. These prescribing costs are much greater than any offset health care cost savings arising from improvements in arthritis and psoriasis. Expected QLYs are low in this model. The total lifetime discounted health associated with palliative care is 5.24 QLYs (Table 2). This is because utility declines fairly rapidly in patients with uncontrolled arthritis, and is predicted to be <0 in later years. In the base case, utility gains as a result of improvement in arthritis are predicted to be much greater than utility gains as a result of improvement in the psoriasis component of Ps. This situation arises because of the relative importance of improvements in arthritis and psoriasis on health related quality of life (HRQoL) estimated by the utility function. For example, a 75% improvement in PSI implies a reduction in PSI from 7.5 to 1.9, a 5.6-point reduction, resulting in a change in HRQoL (measured by EQ-5D) of 5.6 0.004 = 0.02. Etanercept is expected to reduce HQ by 0.63 points (Table 1), which would improve HRQoL by 0.63 0.298 = 0.188, showing that expected gains from biologic therapy in arthritis have a much greater impact on HRQoL than psoriasis. The base case analysis (Table 2) suggests that infliximab is the most effective treatment (in terms of expected QLYs), followed by etanercept, then adalimumab. Infliximab is also the most costly treatment, followed by etanercept, then adalimumab. The results (Table 2) show that for patients with Ps and mild to moderate skin disease, etanercept is likely to be the most cost-effective option, with an ICER vs palliative care of around 16 000 per QLY. Etanercept also has the highest probability of being cost effective at a threshold between 20 000 and 30 000 per QLY. The ICER of infliximab vs etanercept is around 54 000 per QLY, which is unlikely to be acceptable at conventional thresholds for the cost per QLY. In the base case, adalimumab is extendedly dominated. Therefore it would not be cost effective, on average, to recommend adalimumab because a greater QLY gain can be achieved from etanercept within the threshold of 20 000 per QLY. Subgroup analysis Subgroup analysis was conducted to explore the impact of differing severities of psoriasis on cost-effectiveness. For patients with Ps and moderate to severe skin disease, the ICER of adalimumab vs palliative care is around 15 000 per QLY. The ICER of etanercept vs adalimumab is TBLE 2 Base case results Strategy QLYs Costs ( ) ICER ( ) P(c/e)_20k P(c/e)_30k Palliative care 5.241 42 205 0.414 0.282 dalimumab 6.642 66 408 Extendedly 0.044 0.020 dominated Etanercept 7.115 72 178 15 986 a 0.524 0.566 Infliximab 7.430 89 107 53 750 b 0.018 0.132 a Compared with the next best strategy (excluding extendedly dominated option) palliative care. b Compared with the next best strategy (excluding extendedly dominated option) etanercept. iv43
Laura Bojke et al. around 16 000 per QLY and the ICER for infliximab vs etanercept is around 36 000 per QLY. For this subgroup, etanercept has the greatest probability (0.432) of being cost effective at a 20 000 threshold. For patients with Ps with negligible skin involvement, the ICER of etanercept vs palliative care is slightly higher, at around 17 000 per QLY, and the ICER of infliximab vs etanercept is around 76 000 per QLY. dalimumab is extendedly dominated in this group. Sensitivity analysis In addition to the probabilistic analysis, a series of oneway sensitivity analyses were conducted. This showed that results were sensitive to the length of treatment effect for biologics (10 years rather than 40 years), assumptions about the prescription cost, alternative costs of treating patients who do not achieve a response to biologics for the psoriasis component of Ps and assumptions about the progression of HQ on and off treatment. The ICER of adalimumab falls below 20 000 per QLY and is no longer extendedly dominated by other strategies if:. ll responders to PsRC have the same change in HQ at 12 weeks, regardless of biologic therapy used.. Etanercept and adalimumab are considered equally effective for PsRC response, HQ change and PSI response.. patient who does not respond for psoriasis, or does not use biologic therapy, undergoes annual inpatient psoriasis treatment rather than annual ultraviolet B treatment.. lternative costs per PSI point (including phototherapy) are used. The ICER of etanercept increases above 20,000 per QLY or is dominated by other strategies if:. For patients who do not achieve a PSI 75 response, a more intensive (inpatient based) treatment is offered.. HQ rebounds after withdrawal from biologics to natural history rather than to initial gain.. Biologic treatment becomes ineffective (relative to no treatment) after 10 years.. lternative estimates of the cost of treating psoriasis with phototherapy are used. The ICER of infliximab falls below 30 000 per QLY if:. For patients who do not achieve a PSI 75 response, a more intensive (inpatient based) treatment is offered.. Infliximab requires three vials rather than four vials per administration.. lternative estimates of the cost of treating psoriasis with phototherapy are used.. HQ improves while on a biologic drug. Palliative care is cost effective at a threshold of 30 000 per QLY if rebound of HQ is to natural history rather than initial gain. In the scenario where treatment only remains effective for up to 10 years, the ICER for etanercept vs palliative care is 31 000 per QLY, and therefore is likely to be on the boundary of what would be considered cost effective. If treatment remains effective for up to 20 years, the ICER of etanercept vs palliative care is 19 000 per QLY and the ICER for infliximab vs etanercept is 60 000 per QLY. Discussion The model presented here is an extension of a previous model to allow for the inclusion of the biologic adalimumab, in addition to etanercept and infliximab, and to incorporate the impact of treatment on the psoriasis component of the disease through the PSI. The results of this model show that under base case assumptions, etanercept would be considered the most cost-effective strategy for patients with Ps and minimal, mild to moderate or moderate to severe skin involvement. However, there remains a large amount of decision uncertainty in choosing etanercept as the optimal treatment, as the probability of etanercept being cost effective at a threshold of 20 000 was 0.526 and at a threshold of 30 000 was 0.566. lthough this analysis more accurately reflects the disease process and the impact of treatment than previous models in this area, the complexity of the disease process and the scarcity of data mean that there are a number of limitations and outstanding uncertainties in the current analysis. First, despite there being a number of randomized trials comparing biologics with palliative care, there are no head to-head comparisons of all three biologics. Therefore, in order to determine the relative effectiveness of all three, a Bayesian indirect comparison analyses is used. The estimates obtained from the indirect comparison, despite being valid measures of the relative efficacy of these biologics, may be considered more uncertain than estimates provided from head-to-head RCTs. In addition, the patients in most trials are not precisely representative of the population recommended for biologics under current guidelines. It is therefore unclear whether the beneficial effects realized in the clinical trials are similar in those seen in routine clinical practice. Second, there is some uncertainty regarding the progression of HQ scores on and off biologic treatment, and the length of time over which biologics are assumed to be effective. Expert elicitation was used in this model to generate estimates of the progression of HQ for patients continuing on biologics and the progression of HQ following withdrawal from treatment (rebound) [7]. lthough the results of the elicitation should be interpreted with some caution, due to the small number of respondents, the experts unanimously thought that rebound would be less than the amount of initial gain [7], an assumption made in many previous models. This is a surprising result that has not previously been examined in the literature and which requires further consideration. Third, the relationship between utility and severity of arthritis and psoriasis is estimated here from a single data source, which may be a limitation. In addition, the resulting utilities may be sensitive to the functional form chosen for the mapping exercise. The suitability of the iv44
Cost-effectiveness of biologic treatments functional form chosen in this analysis was subject to some scrutiny, but would benefit from further exploratory analysis. Fourth, the possibility of other alternative rules about continuing therapy beyond 12 weeks has not been discussed here. There is, however, a distinct possibility that decisions to continue treatment beyond 12 weeks may be made on indicators other than a particular PsRC threshold. This is particularly the case for those patients with significant psoriasis involvement. This issue was explored somewhat in Rodgers et al. [7]; however, further consideration of alternative thresholds for PsRC and PSI would be useful, as would the possibility of allowing treatment continuation decisions beyond the current 12-week cutoff. Fifth, the analysis conducted here does not include any costs likely to fall on patients. These might include the costs of over-the-counter medications, lost income as a result of time away from work and caregiver costs. Currently NICE does not include these costs in its assessment of cost-effectiveness [10] and, instead, focuses on costs falling on the NHS and personal social services. In rheumatological disease, however, these costs are likely to be significant, with one recent study estimating these costs at between 52 and 72% of total costs [60]. It is also unknown if these costs differ markedly between treatments. Finally, the biologics market is constantly changing, even since this analysis a new comparator, golimumab, has been licensed for use in Ps patients in the UK. The evidence base for golimumab is scarce and it is likely that further uncertainty would be introduced if this comparator was included in the model. Current estimates of its costeffectiveness, however, do not suggest that it would be a cost-effective comparator compared with etanercept [61]. Rheumatology key message. Etanercept appears to be the most cost-effective treatment for active and progressive Ps. cknowlegements Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology ssessment programme (project number 08/43/01) and will be published in full in Health Technology ssessment, Vol. 15, No. 10. The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the Health Technology ssessment (HT) programme, NIHR, NHS or the Department of Health. Supplement: This paper forms part of the supplement Biologic therapies in inflammatory joint diseases: models, evidence and decision making. This supplement was supported by unrestrictive funding from rthritis Research UK. Disclosure statement: The authors have declared no conflicts of interest. References 1 Gladman DD, ntoni C, Mease P, Clegg D, Nash P. 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