A systematic review of cost-effectiveness modeling of pharmaceutical therapies in neuropathic pain: variation in practice, key challenges, and recommendations for the future.

OBJECTIVES: Complexities in the neuropathic-pain care pathway make the condition difficult to manage and difficult to capture in cost-effectiveness models. The aim of this study is to understand, through a systematic review of previous cost-effectiveness studies, some of the key strengths and limitations in data and modeling practices in neuropathic pain. Thus, the aim is to guide future research and practice to improve resource allocation decisions and encourage continued investment to find novel and effective treatments for patients with neuropathic pain.

METHODS: The search strategy was designed to identify peer-reviewed cost-effectiveness evaluations of non-surgical, pharmaceutical therapies for neuropathic pain published since January 2000, accessing five key databases. All identified publications were reviewed and screened according to pre-defined eligibility criteria. Data extraction was designed to reflect key data challenges and approaches to modeling in neuropathic pain and based on published guidelines.

RESULTS: The search strategy identified 20 cost-effectiveness analyses meeting the inclusion criteria, of which 14 had original model structures. Cost-effectiveness modeling in neuropathic pain is established and increasing across multiple jurisdictions; however, amongst these studies, there is substantial variation in modeling approach, and there are common limitations. Capturing the effect of treatments upon health outcomes, particularly health-related quality-of-life, is challenging, and the health effects of multiple lines of ineffective treatment, common for patients with neuropathic pain, have not been consistently or robustly modeled.

CONCLUSIONS: To improve future economic modeling in neuropathic pain, further research is suggested into the effect of multiple lines of treatment and treatment failure upon patient outcomes and subsequent treatment effectiveness; the impact of treatment-emergent adverse events upon patient outcomes; and consistent and appropriate pain measures to inform models. The authors further encourage transparent reporting of inputs used to inform cost-effectiveness models, with robust, comprehensive and clear uncertainty analysis and, where feasible, open-source modeling is encouraged.