Consensus Decision Models for Biologics in Rheumatoid and Psoriatic Arthritis: Recommendations of a Multidisciplinary Working Party

Jason Madan, Tony Ades, Pelham Barton, Laura Bojke, Ernest Choy, Philip Helliwell, Paresh Jobanputra, Ken Stein, Andrew Stevens, Jonathan Tosh, Suzanne Verstappen, Allan Wailoo

Biologic therapies are efficacious but costly. A number of health economic models have been developed to determine the most cost-effective way of using them in the treatment pathway. These models have produced conflicting results, driven by differences in assumptions, model structure, and data, which undermine the credibility of funding decisions based on modeling studies. A Consensus Working Party met to discuss recommendations and approaches for future models of biologic therapies. Our working party consisted of clinical specialists, modelers, and policy makers. Two 1-day meetings were held for members to arrive at consensus positions on model structure, assumptions, and appropriate data sources. These views were guided by clinical aspects of rheumatoid and psoriatic arthritis and the principles of evidence-based medicine. Where opinions differed, we sought to identify a research agenda that would generate the evidence needed to reach consensus. We gained consensus in four areas of model development: initial response to treatment; long-term disease progression; lifetime costs and benefits; and model structure. Consensus was also achieved on some key parameters such as choices of outcome measures, methods for extrapolation beyond trial data, and treatment switching. A research agenda to support further consensus was also identified. Consensus guidance that fully reflects current evidence and clinical understanding was gained successfully. In addition, research needs have been identified. Such guidance can be updated as evidence develops and policy questions change and need not be prescriptive as long as deviations from consensus are clearly explained and justified. Arthritis Research UK and the UK Medical Research Council Network of Hubs for Trials Methodology Research.