Rheumatoid Arthritis: Nixon RM

Nixon RM, Bansback N, Stevens JW, Brennan A, Madan J. · MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Cambridge, UK. · Pharm Stat. · Pubmed #18942777 No free full text.

Abstract: A model is presented to generate a distribution for the probability of an ACR response at six months for a new treatment for rheumatoid arthritis given evidence from a one- or three-month clinical trial. The model is based on published evidence from 11 randomized controlled trials on existing treatments. A hierarchical logistic regression model is used to find the relationship between the proportion of patients achieving ACR20 and ACR50 at one and three months and the proportion at six months. The model is assessed by Bayesian predictive P-values that demonstrate that the model fits the data well. The model can be used to predict the number of patients with an ACR response for proposed six-month clinical trials given data from clinical trials of one or three months duration.

Wailoo AJ, Bansback N, Brennan A, Michaud K, Nixon RM, Wolfe F. · Health Economics and Decision Science, ScHARR, University of Sheffield, Sheffield, UK. · Arthritis Rheum. · Pubmed #18383356 links to  free full text

Abstract: OBJECTIVE: Since the introduction of the Medicare Prescription Drug Improvement and Modernization Act and its associated demonstration project, coverage of selected biologic drugs has been expanded for Medicare beneficiaries. For rheumatoid arthritis, coverage was extended to etanercept, adalimumab, and anakinra in addition to the previously covered infliximab. We undertook to develop a model to compare the costs and quality-adjusted life years (QALYs) generated by each of the 4 biologic agents. METHODS: Data were drawn from meta-analysis of randomized controlled trials and from a large longitudinal outcomes databank. Uncertainty was addressed using probabilistic and one-way sensitivity analyses. A lifetime horizon and Medicare viewpoint were adopted. RESULTS: In the base case analysis, anakinra was the least effective and least costly strategy. Etanercept, adalimumab, and infliximab were similar in terms of effectiveness, but infliximab was more costly. If decision makers are willing to pay a maximum of $50,000/QALY, the probability that infliximab is cost-effective is <1%. Findings were robust to a range of sensitivity analyses. Only if the dose of infliximab remains constant over time is this likely to be a cost-effective strategy. CONCLUSION: Infliximab is unlikely to be cost-effective in the Medicare population compared with either etanercept or adalimumab. Anakinra is substantially less costly but is also less effective than the 3 tumor necrosis factor alpha inhibitors.

Nixon RM, Bansback N, Brennan A. · MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, U.K. · Stat Med. · Pubmed #16900557 No free full text.

Abstract: Mixed treatment comparison (MTC) is a generalization of meta-analysis. Instead of the same treatment for a disease being tested in a number of studies, a number of different interventions are considered. Meta-regression is also a generalization of meta-analysis where an attempt is made to explain the heterogeneity between the treatment effects in the studies by regressing on study-level covariables. Our focus is where there are several different treatments considered in a number of randomized controlled trials in a specific disease, the same treatment can be applied in several arms within a study, and where differences in efficacy can be explained by differences in the study settings. We develop methods for simultaneously comparing several treatments and adjusting for study-level covariables by combining ideas from MTC and meta-regression.We use a case study from rheumatoid arthritis. We identified relevant trials of biologic verses standard therapy or placebo and extracted the doses, comparators and patient baseline characteristics. Efficacy is measured using the log odds ratio of achieving six-month ACR50 responder status. A random-effects meta-regression model is fitted which adjusts the log odds ratio for study-level prognostic factors. A different random-effect distribution on the log odds ratios is allowed for each different treatment. The odds ratio is found as a function of the prognostic factors for each treatment. The apparent differences in the randomized trials between tumour necrosis factor alpha (TNF- alpha) antagonists are explained by differences in prognostic factors and the analysis suggests that these drugs as a class are not different from each other.