Cost-effectiveness of adding Sativex® spray to spasticity care in Belgium: using bootstrapping instead of Monte Carlo simulation for probabilistic sensitivity analyses.
Bootstrapping
Cannabinoids
Cost–utility analysis
Multiple sclerosis
Probabilistic sensitivity analysis
Journal
The European journal of health economics : HEPAC : health economics in prevention and care
ISSN: 1618-7601
Titre abrégé: Eur J Health Econ
Pays: Germany
ID NLM: 101134867
Informations de publication
Date de publication:
Jul 2021
Jul 2021
Historique:
received:
19
03
2020
accepted:
12
03
2021
pubmed:
22
4
2021
medline:
2
9
2021
entrez:
21
4
2021
Statut:
ppublish
Résumé
Uncertainty in model-based cost-utility analyses is commonly assessed in a probabilistic sensitivity analysis. Model parameters are implemented as distributions and values are sampled from these distributions in a Monte Carlo simulation. Bootstrapping is an alternative method that requires fewer assumptions and incorporates correlations between model parameters. A Markov model-based cost-utility analysis comparing oromucosal spray containing delta-9-tetrahidrocannabinol + cannabidiol (Sativex®, nabiximols) plus standard care versus standard spasticity care alone in the management of multiple sclerosis spasticity was performed over a 5-year time horizon from the Belgian healthcare payer perspective. The probabilistic sensitivity analysis was implemented using a bootstrap approach to ensure that the correlations present in the source clinical trial data were incorporated in the uncertainty estimates. Adding Sativex® spray to standard care was found to dominate standard spasticity care alone, with cost savings of €6,068 and a quality-adjusted life year gain of 0.145 per patient over the 5-year analysis. The probability of dominance increased from 29% in the first year to 94% in the fifth year, with the probability of QALY gains in excess of 99% for all years considered. Adding Sativex® spray to spasticity care was found to dominate standard spasticity care alone in the Belgian healthcare setting. This study showed the use of bootstrapping techniques in a Markov model probabilistic sensitivity analysis instead of Monte Carlo simulations. Bootstrapping avoided the need to make distributional assumptions and allowed the incorporation of correlating structures present in the original clinical trial data in the uncertainty assessment.
Sections du résumé
BACKGROUND
BACKGROUND
Uncertainty in model-based cost-utility analyses is commonly assessed in a probabilistic sensitivity analysis. Model parameters are implemented as distributions and values are sampled from these distributions in a Monte Carlo simulation. Bootstrapping is an alternative method that requires fewer assumptions and incorporates correlations between model parameters.
METHODS
METHODS
A Markov model-based cost-utility analysis comparing oromucosal spray containing delta-9-tetrahidrocannabinol + cannabidiol (Sativex®, nabiximols) plus standard care versus standard spasticity care alone in the management of multiple sclerosis spasticity was performed over a 5-year time horizon from the Belgian healthcare payer perspective. The probabilistic sensitivity analysis was implemented using a bootstrap approach to ensure that the correlations present in the source clinical trial data were incorporated in the uncertainty estimates.
RESULTS
RESULTS
Adding Sativex® spray to standard care was found to dominate standard spasticity care alone, with cost savings of €6,068 and a quality-adjusted life year gain of 0.145 per patient over the 5-year analysis. The probability of dominance increased from 29% in the first year to 94% in the fifth year, with the probability of QALY gains in excess of 99% for all years considered.
CONCLUSIONS
CONCLUSIONS
Adding Sativex® spray to spasticity care was found to dominate standard spasticity care alone in the Belgian healthcare setting. This study showed the use of bootstrapping techniques in a Markov model probabilistic sensitivity analysis instead of Monte Carlo simulations. Bootstrapping avoided the need to make distributional assumptions and allowed the incorporation of correlating structures present in the original clinical trial data in the uncertainty assessment.
Identifiants
pubmed: 33880663
doi: 10.1007/s10198-021-01285-1
pii: 10.1007/s10198-021-01285-1
pmc: PMC8214588
doi:
Substances chimiques
Drug Combinations
0
Cannabidiol
19GBJ60SN5
Dronabinol
7J8897W37S
nabiximols
K4H93P747O
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
711-721Références
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