Glucosamine Sulphate in the Treatment of Knee Osteoarthritis: Cost-effectiveness Comparison with Paracetamol

S. Scholtissen; O. Bruyère; A. Neuprez; J. L. Severens; G. Herrero-Beaumont; L. Rovati; M. Hiligsmann; J. Y. Reginster

Disclosures

Int J Clin Pract. 2010;64(6):756-762. 

In This Article

Materials and Methods

The GUIDE study

The Glucosamine Unum In Die (once-a-day) Efficacy trial (GUIDE;[8]) was conducted according to a prospective, randomised, PBO- and reference-controlled, double-blind, double-dummy, parallel-group design, in 13 rheumatology referral centres in Spain and Portugal. Three hundred eighteen patients diagnosed as having primary symptomatic knee OA were enrolled in this study.

Paracetamol, the currently preferred medication for symptomatic treatment of OA, was used as a side comparator. Patients were randomly assigned to receive oral GS 1500 mg once daily, paracetamol 3 g/day, or PBO. The rescue medication consisted of the conventional non-steroidal anti-inflammatory drug ibuprofen (IB), in 400-mg tablets. For each subject in the three groups, the number of IB tablets was recorded.

The primary efficacy outcome measure was the change in the Lequesne index after 6 months. Secondary parameters included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC).[12] These outcome measures were assessed using an intent-to-treat analysis. Clinic visits were carried out after 15 days of treatment and then at monthly intervals from the time of randomisation until the end of the 6-month treatment course.

Effects

The effectiveness of GS was assessed in the GUIDE study in terms of specific quality of life using the WOMAC. The WOMAC is a disease-specific instrument allowing for the computation of an overall total measure of Health Related Quality of Life using a weighted sum of the responses to each of the individual items.

To calculate the number of QALY for each subject, WOMAC scores were first translated into Health Utilities Index (HUI3)[13] scores using the formula of Grootendorst et al.[14] Grootendorst has developed and estimated a prediction model using linear regression to map the WOMAC along with basic demographic and OA disease severity data into HUI utility scores. The HUI is a commonly used generic preference-based instrument to measure utility. Subsequently, the utility estimates were used to calculate the 6-months QALY using the area-under-the-curve method.[15]

Costs

As the GUIDE study was not a full economic evaluation,[16] costs were not studied. To evaluate the costs retrospectively, we used the mean Spanish market price (i.e. in the country where the study was predominantly performed) of each treatment adjusted for the compliance of each individual patient. In healthcare, the most commonly used definition of compliance is 'patient's behaviours (in terms of taking medication, following diets, or executing life style changes) coincide with healthcare providers' recommendations for health and medical advice'.[17] Compliance was calculated as the medication possession ratio (MPR), which is the number of tablets dispensed, divided by the number of days between refills. The mean Spanish day costs for GS, paracetamol and PBO were 0.21, 0.28 and 0 €, respectively. Concerning the side medication IB, the unit price was 0.06 €.[18] Other health care costs and non-health care costs were assumed to be comparable between treatment groups.

Statistical Analyses

Descriptive analyses were first performed using the mean and SD for each of the three groups of subjects. To compare demographic and clinical characteristics of the GS group with the paracetamol and PBO groups, univariate analyses were performed using ANOVA test for continuous variables and χ2 for binary variables. When differences were revealed, the Scheffé test was used to identify between which groups of subjects the difference occurred.

Statistical analyses were performed using Statistica, version 8.0 (Statsoft Inc., Tulsa, OK, USA). All significant test results involved probabilities with alpha set at 0.05. Analyses were performed according to the intention-to-treat principle.

Cost-effectiveness Analysis

A cost-effectiveness analysis enumerates the additional resources consumed for an improvement in the effects (e.g. survival or QALY) associated with one health intervention compared with another. The result can be summarised as an incremental cost-effectiveness ratio (ICER) – a measure of the additional cost per unit of health gain. The underlying calculation for the ICER comparing GS vs. paracetamol or PBO in patients with knee OA was:

where costs were measured in Euros and effects were measured in QALY.

The incremental cost and incremental effect was represented visually using the incremental cost-effectiveness plane.[19] The horizontal axis divides the plane according to incremental cost (positive above, negative below) and the vertical axis divides the plane according to incremental effect (positive to the right and negative to the left). This divides the incremental cost-effectiveness plane into four quadrants. Each quadrant has a different implication for the decision. If the ICER fell in the southeast quadrant (more effective, less costly), the experimental intervention is always considered cost-effective and called dominant over the alternative. Interventions falling in the northwest (less effective, more costly) are never considered cost-effective, thus inferior. Finally, if the ICER fell in the northeast or the southwest quadrant, trade-offs between costs and effects would need to be considered. These two quadrants represent the situation where the experimental treatment or intervention may be cost-effective compared with the control, depending upon the value at which the ICER is considered good value for money. For economic analyses, the north-east quadrant and the south-west quadrant are considered to be of equal value.

To get insight into the uncertainty around the ICERs, a bootstrap simulation was conducted.[20] A bootstrap simulation is a non-parametric method in which a sample of equal size of the original sample is selected, many times at random with replacement. This yields information concerning the distribution of the ICER point estimate.

Within the cost-effectiveness framework, the probability that a new treatment is cost-effective varies depending on what society is prepared to pay per gain in effectiveness, the so-called ceiling ratio (λ). This is shown in a cost-effectiveness acceptability curve (CEAC).[21] We performed this procedure for the two group comparison (GS vs. paracetamol and GS vs. PBO) and for the three group comparison.

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