Egle, Marco

Abstract INTRODUCTION Understanding comorbidities’ combined impacts on dementia risk may offer a more comprehensive understanding of individuals’ risk. Using machine‐learning, we grouped individuals with similar midlife risk profiles into clusters and explored associations with dementia risk. METHODS Participants without dementia at baseline (1987–1989) from the prospective Atherosclerosis Risk in Communities (ARIC) study were included (ages 45–64 years; N = 15,250). Using unsupervised hierarchical cluster analysis, nine clusters were created and defined based on 14 midlife morbidities. The associations with incident dementia ( N = 3272 cases, median follow‐up 25 years) and deaths ( N = 9099) were evaluated using time‐to‐event regression models. RESULTS Compared with the healthiest cluster (Cluster 1), Clusters 2 (smoking) (hazard ratio [HR](95% confidence interval [CI]) = 1.62 (1.08, 2.43)), 5 (obesity, diabetes, hypertension, and hypertriglyceridemia) (HR(95%CI) = 1.91 (1.35,2.70)), and 7/8 (atrial fibrillation/heart failure) (HR(95%CI) = 2.69 (1.59,4.57)) were associated with dementia. Accounting for competing risk of death in the Fine‐Gray subdistribution model negated the cluster‐dementia association. DISCUSSION Midlife morbidity clusters are important for dementia and mortality risk.

Background White matter hyperintensities (WMH) and their progression are associated with risk of dementia and stroke, so are an important target for clinical trials. The cost of broad magnetic resonance imaging (MRI) screening to identify eligible individuals, however, limits the feasibility of designing clinical trials targeting WMH. A low‐cost retinal or clinical screening measure before MRI could reduce recruitment costs versus an MRI‐only screening design in a hypothetical clinical trial. Methods and Results Data from the Atherosclerosis Risk in Communities study with valid retinal and WMH measurements ( N =1311) were used. To identify a population at greater likelihood of significant WMH on MRI and thus reduce the number of screening MRIs required, we evaluated 3 theoretical prescreening measures: (1) retinal, (2) clinical, (3) combined clinical‐retinal. Given a target sample for clinical trials ( N =646), we calculated screening sample sizes based on the proportion within the population having an elevated score for each prescreening measure (separately) multiplied by the proportion of significant WMH among those with that prescreening feature. Recruitment costs were calculated using estimated retinal and MRI cost estimates. Compared with the estimated cost of MRI‐only screening (>$4.24 million, requiring MRI on 6526 participants), prescreening for a high clinical score resulted in total cost of $2.47 million, with an initial screening group of 52 778 participants, with MRI in 3801. A high clinical‐retinal score cutoff resulted in costs of $2.9 million while requiring 13 572 participants, with 3801 completing MRI. Conclusions A 2‐stage design with low‐cost prescreening measures is a promising approach, resulting in reduced theoretical recruitment costs compared with an MRI‐only design.

Background: White matter hyperintensities (WMH) are associated with risk of dementia and stroke, so are an important therapeutic target for clinical trials. The cost of broad MRI screening to identify those individuals with significant WMH, however, limits the feasibility of designing clinical trials which target WMH presence and which test treatments that slow progression. Hypothesis: A low-cost retinal or clinical screening measure prior to an MRI screening stage reduces the cost of recruiting persons with significant WMH burden in a hypothetical clinical trial vs an MRI-only screening design. Method: Data were from participants in the Atherosclerosis Risk in Communities-Neurocognitive study with clinical, retinal and WMH measurements ( N = 1311) at ages 53-70 years. Significant WMH burden was defined as a Cardiovascular Health Study score >2. Three low-cost pre-screening measures were assessed: (1) retinal: a score incorporating multiple markers of abnormal retinal vasculature, (2) clinical: a score incorporating hypertension, diabetes, and age, (3) combined retinal-clinical: a score incorporating retinal and clinical factors. Given a prior published target sample for a WMH clinical trial (N= 646), we calculated a theoretical screening sample size based on the proportion of each pre-screening measure in the population multiplied by the proportion of significant WMH burden among those with a prevalent pre-screening feature. Total recruitment cost was calculated using standard retinal ($32.50) and MRI ($650) cost estimates. Results: Compared to the estimated cost of MRI-only screening (>$4.24M, requiring MRI screening 6,526 participants), pre-screening for a high clinical score reduced total cost to $2.47M, but increased the initial screening group to 52,778 participants, of whom 3,801 would be screened by MRI). A high retinal-clinical score cutoff reduced costs to $2.9M while only requiring 13,572 screened participants (of these only 3,801 would require MRI). Conclusion: A 2-stage recruitment design with a low-cost pre-screening retinal and clinical measure is a promising approach, resulting in a reduction of theoretical recruitment costs for recruiting persons with significant WMH burden compared to an MRI-only design.