This article, published in Pharmacoeconomics, systematically reviews the literature in order to identify model-based studies evaluating the cost-effectiveness of treatments for depression and examine the appropriateness of different modelling technique for simulating the natural course of depression.
The review yielded 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven.
Based on these findings the authors conclude that since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be the most appropriate modelling techniques. However, because the studies had diverse methodological aspects it appeared a challenge to compare them.
Kolovos S, Bosmans JE, Riper H et al. Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review. PharmacoEconomics Open 2017; 1 (3): 149-165. https://doi.org/10.1007/s41669-017-0014-7