Cargando…

Parkinson’s disease with early motor complications: predicting EQ-5D- 3L utilities from PDQ-39 data in the EARLYSTIM trial

BACKGROUND: A utility value is a health-related quality of life metric (HRQoL) metric used in a cost-effectiveness analysis. While utilities as outcomes in the treatment of advanced Parkinson’s disease (PD) with deep brain stimulation (DBS) are available, they do not currently exist for PD with earl...

Descripción completa

Detalles Bibliográficos
Autores principales: Zahra, Mehdi, Durand-Zaleski, Isabelle, Górecki, Michal, Walleser Autiero, Silke, Barnett, Gillian, Schüpbach, W. M. Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7053067/
https://www.ncbi.nlm.nih.gov/pubmed/32122369
http://dx.doi.org/10.1186/s12955-020-01299-y
Descripción
Sumario:BACKGROUND: A utility value is a health-related quality of life metric (HRQoL) metric used in a cost-effectiveness analysis. While utilities as outcomes in the treatment of advanced Parkinson’s disease (PD) with deep brain stimulation (DBS) are available, they do not currently exist for PD with early motor complications. The objectives of this study were to predict utilities from observed disease-specific HRQoL data using two mapping algorithms, and investigate their performance in terms of longitudinal changes within and between treatment groups, and distribution by PD severity. METHODS: This is a post hoc analysis of data from the EARLYSTIM trial of DBS compared with best medical therapy (BMT) in PD patients with early motor complications We used two published algorithms comprising ordinal and multinomial regression models to map EQ-5D-3L utilities from observed PD-specific 39 item Questionnaire (PDQ-39) scores in EARLYSTIM. Utilities were calculated using the predicted functioning levels of EQ-5D-3L dimensions and the established EQ-5D-3L UK tariffs. Statistical analyses (analysis of variance, two-tailed Student’s t-test) were used to test the change from baseline within groups and difference in change from baseline between groups in utilities. Boxplots were developed to investigate the distribution of predicted utilities by PD severity, measured using the Hoehn and Yahr scale. RESULTS: The change from baseline in predicted mean utilities was statistically significant at all visits up to 24 months for the DBS group (p < 0.001) with both algorithms, and statistically significant at 12 months only (p = 0.04) for the BMT group with one algorithm. With both algorithms, the between-groups difference in change from baseline in predicted mean utilities favored DBS at all follow-up visits (p < 0.001). Based on the Hoehn and Yahr scale, predicted utilities deteriorated with increasing disease severity. CONCLUSIONS: Among PD patients with early motor complications, utilities predicted by both mapping algorithms using PDQ-39 data demonstrated a statistically and clinically meaningful improvement with DBS compared with BMT. It was not possible to conclude if one algorithm was more responsive than other. In the absence of utilities collected directly from patients, mapping is an acceptable option permitting economic evaluations to be undertaken.