University Medical Centre Nijmegen, Department of Rheumatology, Nijmegen and 1Maastricht University, Department of Health Organisation, Policy and Economics, Maastricht, The Netherlands
Correspondence to:
P. M. J. Welsing. E-mail: P.Welsing{at}reuma.umcn.nl
SIR, Kobelt et al. [1] describe a modelling study into the cost-effectiveness of infliximab plus methotrexate treatment compared with methotrexate treatment alone over 10 yr in patients with advanced disease.
They use the results of the ATTRACT trial and a Markov model with health states defined by the Health Assessment Questionnaire (HAQ) to simulate the 10-yr follow-up of the patients in the clinical trial. Transition probabilities and costs and utility values for the health states are calculated using data from the Lund and ERAS cohorts. The results indicate that (1 to 2 yr) treatment with infliximab results in cost-effectiveness ratios well within the usual range for treatment to be recommended for use [1].
Unfortunately we believe that the study has some implicit assumptions that might result in too optimistic results.
Our first concern relates to the comparison. The comparison of infliximab plus methotrexate treatment with methotrexate alone is made in patients who are not adequately controlled on DMARDs including methotrexate. For the results of a cost-effectiveness analysis to be relevant for clinical practice the comparator for the investigational treatment should be the standard treatment, i.e. the treatment that is used in practice for these patients and should not be strictly limited by the availability of direct evidence from clinical trials [24]. A treatment with methotrexate in patients who have been shown not to be adequately controlled using methotrexate can hardly be regarded as standard treatment. In clinical practice rheumatologists will search for alternative treatments (i.e. increase in dosage, another DMARD, combinations of DMARDs and corticosteroids) when treatment does not have the desired effect. The comparator treatment in a cost-effectiveness study should reflect this.
Our second concern relates to the merging of data from all active treatment arms from the ATTRACT trial for estimating the effectiveness of infliximab and the use of only the treatment arm with the lowest dose, 3 mg/kg, for estimating the costs. Although no statistically significant difference between the active treatment arms in the ATTRACT trial could be demonstrated, there might be a clinically relevant difference. In this regard, absence of evidence is not equal to evidence of absence. Both the costs as well as the effects should preferably be based on the same population. Also the transition probabilities and the cost and utility values of the health states in a Markov model should be as context specific as possible.
The final concern relates to the assumption regarding the duration of the infliximab treatment and the assumptions made on the influence of stopping this treatment on the disease course in the basic model. It is not plausible that patients stop infliximab treatment after 1 yr, especially when the treatment has a beneficial effect. In this analysis it is also assumed that after stopping the infliximab treatment no relapse occurs, but rather over a period of 9 yr equilibrium is formed in both treatment arms with a comparable distribution over the health states (as far as this can be concluded from the mean values in Figs 5 and 6). This also seems an unrealistic assumption, since, as the authors state, the HAQ is influenced by disease activity and by joint damage, and probably only the influence of the progression of joint damage on the HAQ might (partly) remain, and the disease activity might flare up after stopping treatment.
To incorporate such an effect loss the authors present an alternative model. However, in this alternative model the ICERs only marginally increased and using all costs the cost-effectiveness ratios were even more favourable (cost saving)this result is counterintuitive. Apparently, in the alternative model, not only an effect loss was modelled but also the way of calculating the model was changed explaining the counterintuitive result. When it is intended to investigate the influence of an effect loss on the results of the study, one should not also change the calculation method. A figure of the mean HAQ scores using this approach (like Figs 4 and 5) would be helpful.
Making assumptions in modelling studies is unavoidable [3, 5]. However, for the results of (cost-effectiveness) modelling studies to be credible, assumptions should be made realistic or even conservative towards the experimental treatment and should be investigated transparently using univariate and multivariate sensitivity analyses to study robustness of the findings. This is an important approach to reduce the likelihood of bias in this kind of analysis [6].
The authors have declared no conflicts of interest.
References