Background: Multiple sclerosis (MS) is a chronic autoimmune/neurodegenerative disease associated with progressing disability affecting mostly women. We aim to estimate transition probabilities describing MS-related disability progression from no disability to severe disability. Transition probabilities are a vital input for health economics models. In MS, this is particularly relevant for pharmaceutical agency reimbursement decisions for disease-modifying therapies (DMTs).
Methods: Data were obtained from Australian participants of the MSBase registry. We used a four-state continuous-time Markov model to describe how people with MS transition between disability milestones defined by the Expanded Disability Status Scale (scale 0-10): no disability (EDSS of 0.0), mild (EDSS of 1.0-3.5), moderate (EDSS of 4.0-6.0), and severe (EDSS of 6.5-9.5). Model covariates included sex, DMT usage, MS-phenotype, and disease duration, and analysis of covariate groups were also conducted. All data were recorded by the treating neurologist.
Results: A total of N = 6369 participants (mean age 42.5 years, 75.00% female) with 38,837 person-years of follow-up and 54,570 clinical reviews were identified for the study. Annual transition probabilities included: remaining in the no, mild, moderate, and severe states (54.24%, 82.02%, 69.86%, 77.83% respectively) and transitioning from no to mild (42.31%), mild to moderate (11.38%), and moderate to severe (9.41%). Secondary-progressive MS was associated with a 150.9% increase in the hazard of disability progression versus relapsing-remitting MS.
Conclusions: People with MS have an approximately 45% probability of transitioning from the no disability state after one year, with people with progressive MS transitioning from this health state at a much higher rate. These transition probabilities will be applied in a publicly available health economics simulation model for Australia and similar populations, intended to support reimbursement of a plethora of existing and upcoming interventions including medications to reduce progression of MS.
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http://dx.doi.org/10.1007/s40273-024-01417-4 | DOI Listing |
JMIR Cardio
January 2025
Faculty of Education, Health and Human Sciences, University of Greenwich, London, United Kingdom.
Background: Cardiovascular diseases (CVDs) are the leading cause of death globally. Demographic, behavioral, socioeconomic, health care, and psychosocial variables considered risk factors for CVD are routinely measured in population health surveys, providing opportunities to examine health transitions. Studying the drivers of health transitions in countries where multiple burdens of disease persist (eg, South Africa), compared with countries regarded as models of "epidemiologic transition" (eg, England), can provide knowledge on where best to intervene and direct resources to reduce the disease burden.
View Article and Find Full Text PDFISA Trans
January 2025
Centre de Recherche en Automatique de Nancy-Lorraine University, 2 avenue de la Forêt de Haye, BP, Vandoeuvre Lès Nancy 54516, France. Electronic address:
This paper explores a novel challenge regarding bidirectional Automated Guided Vehicles (AGVs): supervisory control amidst potential sensor faults. The proposed approach uses an event-based control architecture, guided by Supervisory Control Theory (SCT), to achieve non-blocking routing of AGVs. Unlike most routing approaches assuming full event observability, this paper investigates scenarios where events might become unobservable due to sensor faults or disturbances, which may affect the supervisor efficiency.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
January 2025
Department of Pharmacy, Uppsala University, Uppsala, Sweden.
Type 2 diabetes (T2D) is a progressive metabolic disorder that could be an underlying cause of long-term complications that increase mortality. The assessment of the probability of such events could be essential for mortality risk management. This work aimed to establish a framework for risk predictions of macrovascular complications (MVC) and diabetic kidney disease (DKD) in patients with T2D, using real-world data from the Swedish National Diabetes Registry (NDR), in the presence of mortality as a competing risk.
View Article and Find Full Text PDFBMC Public Health
January 2025
Changzhou Center for Disease Control and Prevention, No. 203 Taishan Road, Xinbei District, Changzhou City, Jiangsu Province, 213000, China.
Background: The benefits of improving coverage and timeliness of varicella vaccination need to be quantified in countries where varicella vaccine (VarV) has not yet been included in national immunization programs. This longitudinal study analyzed the vaccine effectiveness (VE) of the varicella vaccination program implemented in Changzhou City during the transitional period (2017-2022).
Methods: Using the Immunization Information System and National Notifiable Infectious Disease Surveillance System registry data, this retrospective case-cohort study assessed the VEs of varicella vaccination for Changzhou children born from 2016 to 2021.
PLoS One
January 2025
National Institute of Public Health, University of Southern Denmark, Copenhagen K, Denmark.
Latent transition analysis (LTA) is a useful statistical modelling approach for describe transitions between latent classes over time. LTA may be characterized in terms of prevalence at each time point and through transition probabilities over time. Investigating predictors of these transitions is often of key interest.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!