Probabilistic sensitivity analysis (PSA)
Probabilistic sensitivity analysis (PSA) was conducted by considering an appropriate probability distribution for Markov model parameters that included utility values, Weibull parameters, mortality rates and costs of resource use with health ‘states’. For example, a beta probability distribution was considered for Weibull scale (lambda) and shape (gamma) parameters and utilities for both infliximab and ciclosporin groups, while cost was varied using a Gamma distribution. The mean costs and QALYs are subject to sampling error. The effect of parameter uncertainty on cost-effectiveness results was addressed by employing a Monte Carlo (MC) simulation to generate 10,000 input configurations for model parameters and then the Markov model was run with each parameter set. Results from the PSA were presented via a CE plane and CEAC curves.Model-based cost-effectiveness results in the study were produced based on Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist [