Potential Impact of Slowing Disease Progression in Early Symptomatic Alzheimer's Disease on Patient Quality of Life, Caregiver Time, and Total Societal Costs: Estimates Based on Findings from GERAS-US Study.

Background: Impact of Alzheimer's disease (AD) progression on patient health-related quality of life (HRQoL), caregiver time, and societal costs is not well characterized in early AD. Objective: To assess the association of change in cognition with HRQoL, caregiver time, and societal costs over 36 months, and estimate the impact of slowing disease progression on these outcomes. Methods: This post-hoc analysis included patients with amyloid-positive mild cognitive impairment (MCI) and mild AD dementia (MILD AD) from the 36-month GERAS-US study. Disease progression was assessed using the Mini-Mental State Examination score. Change in outcomes associated with slowing AD progression was estimated using coefficients from generalized linear models. Results: At baseline, 300 patients had MCI and 317 had MILD AD. Observed natural progression over 36 months was associated with: 5.1 point decline in the Bath Assessment of Subjective Quality of Life in Dementia (BASQID) score (for HRQoL), increase in 1,050 hours of total caregiver time, and $8,504 total societal costs for MCI; 6.6 point decline in the BASQID score, increase in 1,929 hours of total caregiver time, and $12,795 total societal costs for MILD AD per person. Slowing AD progression by 30% could result in per person savings in HRQoL decline, total caregiver time, and total societal costs: for MCI: 1.5 points, 315 hours, and $2,638; for MILD AD: 2.0 points, 579 hours, and $3,974. Conclusions: Slowing AD progression over 36 months could slow decline in HRQoL and save caregiver time and societal cost in patients with MCI and MILD AD.

Incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease in patients with multiple sclerosis initiating disease-modifying therapies: Retrospective cohort study using a frequentist model averaging statistical framework.

Researchers are increasingly using insights derived from large-scale, electronic healthcare data to inform drug development and provide human validation of novel treatment pathways and aid in drug repurposing/repositioning. The objective of this study was to determine whether treatment of patients with multiple sclerosis with dimethyl fumarate, an activator of the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, results in a change in incidence of type 2 diabetes and its complications. This retrospective cohort study used administrative claims data to derive four cohorts of adults with multiple sclerosis initiating dimethyl fumarate, teriflunomide, glatiramer acetate or fingolimod between January 2013 and December 2018. A causal inference frequentist model averaging framework based on machine learning was used to compare the time to first occurrence of a composite endpoint of type 2 diabetes, cardiovascular disease or chronic kidney disease, as well as each individual outcome, across the four treatment cohorts. There was a statistically significantly lower risk of incidence for dimethyl fumarate versus teriflunomide for the composite endpoint (restricted hazard ratio [95% confidence interval] 0.70 [0.55, 0.90]) and type 2 diabetes (0.65 [0.49, 0.98]), myocardial infarction (0.59 [0.35, 0.97]) and chronic kidney disease (0.52 [0.28, 0.86]). No differences for other individual outcomes or for dimethyl fumarate versus the other two cohorts were observed. This study effectively demonstrated the use of an innovative statistical methodology to test a clinical hypothesis using real-world data to perform early target validation for drug discovery. Although there was a trend among patients treated with dimethyl fumarate towards a decreased incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease relative to other disease-modifying therapies-which was statistically significant for the comparison with teriflunomide-this study did not definitively support the hypothesis that Nrf2 activation provided additional metabolic disease benefit in patients with multiple sclerosis.