This economic evaluation was based on a Markov model which estimated the costs and benefits associated with the two treatment options. The time horizon of the analysis was six months. The authors stated that the study perspective was that of the National Health Service.
The effectiveness data were derived from a systematic review of the literature, supplemented with estimates from a Delphi panel when information was not available. The literature review involved searches of EMBASE and MEDLINE to identify prospective clinical trials that evaluated either 1800mg per day or less of gabapentin or the lidocaine 5% medicated plaster for the treatment of patients with PHN. Trials, which were not published in English, and those with less than 50 patients were excluded. The Delphi panel comprised nine general practitioners (GPs) working in England who had experience treating PHN with gabapentin. These GPs were identified and selected by an independent agency. The main clinical outcome was the treatment response.
Monetary benefit and utility valuations:
The utility weights were derived from a published study, which used the Health Utilities Index (Mark 3). These utilities were adjusted by the Delphi panel, in some instances, to reflect the predominantly elderly population analysed.
Measure of benefit:
The primary measure of benefit was the quality-adjusted life-year (QALY).
The cost categories were those of medications and consultations with GPs and hospital based clinicians. The resource use data were obtained from the Delphi panel in conjunction with published studies and the cost data were taken from official price tariffs. The price year was 2006 and all costs were reported in UK pounds sterling (£). Given the short time horizon, discounting was not performed in the base-case analysis. However, a longer time horizon was explored in the sensitivity analysis and these costs were discounted at an annual rate of 3.5%.
Analysis of uncertainty:
A one-way sensitivity analysis was conducted on all the input parameters, other than the unit costs, to investigate their separate impact on the results. Probabilistic sensitivity analysis was conducted to assess how varying the uncertain parameters simultaneously affected the results. The details of this analysis were presented as cost-effectiveness acceptability curves. In addition, a number of scenario analyses were completed.