Modelling approaches - The case of schizophrenia: the case of schizophreniaHeeg, B. M. S., Damen, J., Buskens, E., Caleo, S., de Charro, F. & van Hout, B. A., 2008, In : Pharmacoeconomics. 26, 8, p. 633-648 16 p.
Research output: Contribution to journal › Editorial › Academic › peer-review
Schizophrenia is a chronic disease characterized by periods of relative stability interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter- and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between covariates and variability (first-order uncertainty).
We note that, depending on the research question, the optimal modelling approach should be selected based on the expected differences between the comparators, the number of co-variates, the number of patient subgroups, the interactions between co-variates, and simulation time. Finally, it is argued that in case micro-simulation is required for the cost-effectiveness analysis of schizophrenia treatments, a discrete event simulation model is best suited to accurately capture all of the relevant interdependencies in this chronic, highly heterogeneous disease with limited long-term follow-up data.
|Number of pages||16|
|Publication status||Published - 2008|
- LONG-ACTING RISPERIDONE, DISCRETE-EVENT SIMULATION, QUALITY-OF-LIFE, TREATMENT-RESISTANT SCHIZOPHRENIA, COST-EFFECTIVENESS, ECONOMIC-EVALUATION, CONVENTIONAL ANTIPSYCHOTICS, SCHIZOAFFECTIVE DISORDERS, ATYPICAL ANTIPSYCHOTICS, MARKOV MODEL