IMPORTANCE Few health systems have adopted effective dementia care management programs. The Care Ecosystem is a model for delivering care from centralized hubs across broad geographic areas to caregivers and persons with dementia (PWDs) independently of their health system affiliations. OBJECTIVE To determine whether the Care Ecosystem is effective in improving outcomes important to PWDs, their caregivers, and payers beyond those achieved with usual care. DESIGN, SETTING, AND PARTICIPANTS A single-blind, randomized clinical trial with a pragmatic design was conducted among PWDs and their caregivers. Each PWD-caregiver dyad was enrolled for 12 months between March 20, 2015, and February 28, 2017. Data were collected until March 5, 2018. Study interventions and assessments were administered over the telephone and internet by clinical and research teams in San Francisco, California, and Omaha, Nebraska. Of 2585 referred or volunteer PWD-caregiver dyads in California, Iowa, or Nebraska, 780 met eligibility criteria and were enrolled. A total of 512 PWD-caregiver dyads were randomized to receive care through the Care Ecosystem and 268 dyads to receive usual care. All eligible PWDs had a dementia diagnosis; were enrolled or eligible for enrollment in Medicare or Medicaid; and spoke English, Spanish, or Cantonese. Analyses were intention-to-treat. INTERVENTION Telephone-based collaborative dementia care was delivered by a trained care team navigator, who provided education, support and care coordination with a team of dementia specialists (advanced practice nurse, social worker, and pharmacist). MAIN OUTCOMES AND MEASURES Primary outcome measure: Quality of Life in Alzheimer's Disease based on caregiver's rating of 13 aspects of PWD's well-being (including physical health, energy level, mood, living situation, memory, relationships, and finances) on a 4-point scale (poor to excellent). Secondary outcomes: frequencies of PWDs' use of emergency department, hospitalization, and ambulance services; caregiver depression (score on 9-Item Patient Health Questionnaire; higher scores indicate more severe depression); and caregiver burden (score on 12-Item Zarit Burden Interview; higher scores indicate more severe caregiver burden). RESULTS The 780 PWDs (56.3% female; mean [SD] age, 78.1 [9.9] years) and 780 caregivers (70.9% female; mean [SD] age, 64.7 [12.0] years) lived in California (n = 452), Nebraska (n = 284), or Iowa (n = 44). Of 780 dyads, 655 were still active at 12 months, and 571 completed the 12-month survey. Compared with usual care, the Care Ecosystem improved PWD quality of life (B, 0.53; 95% CI, 0.25-1.30; P = .04), reduced emergency department visits (B, −0.14; 95% CI, −0.29 to −0.01; P = .04), and decreased caregiver depression (B, −1.14; 95% CI, −2.15 to −0.13; P = .03) and caregiver burden (B, −1.90; 95% CI, −3.89 to −0.08; P = .046). CONCLUSIONS AND RELEVANCE Effective care management for dementia can be delivered from centralized hubs to supplement usual care and mitigate the growing societal and economic b...

Accurately predicting the underlying neuropathological diagnosis in patients with behavioural variant frontotemporal dementia (bvFTD) poses a daunting challenge for clinicians but will be critical for the success of disease-modifying therapies. We sought to improve pathological prediction by exploring clinicopathological correlations in a large bvFTD cohort. Among 438 patients in whom bvFTD was either the top or an alternative possible clinical diagnosis, 117 had available autopsy data, including 98 with a primary pathological diagnosis of frontotemporal lobar degeneration (FTLD), 15 with Alzheimer's disease, and four with amyotrophic lateral sclerosis who lacked neurodegenerative disease-related pathology outside of the motor system. Patients with FTLD were distributed between FTLD-tau (34 patients: 10 corticobasal degeneration, nine progressive supranuclear palsy, eight Pick's disease, three frontotemporal dementia with parkinsonism associated with chromosome 17, three unclassifiable tauopathy, and one argyrophilic grain disease); FTLD-TDP (55 patients: nine type A including one with motor neuron disease, 27 type B including 21 with motor neuron disease, eight type C with right temporal lobe presentations, and 11 unclassifiable including eight with motor neuron disease), FTLD-FUS (eight patients), and one patient with FTLD-ubiquitin proteasome system positive inclusions (FTLD-UPS) that stained negatively for tau, TDP-43, and FUS. Alzheimer's disease was uncommon (6%) among patients whose only top diagnosis during follow-up was bvFTD. Seventy-nine per cent of FTLD-tau, 86% of FTLD-TDP, and 88% of FTLD-FUS met at least 'possible' bvFTD diagnostic criteria at first presentation. The frequency of the six core bvFTD diagnostic features was similar in FTLD-tau and FTLD-TDP, suggesting that these features alone cannot be used to separate patients by major molecular class. Voxel-based morphometry revealed that nearly all pathological subgroups and even individual patients share atrophy in anterior cingulate, frontoinsula, striatum, and amygdala, indicating that degeneration of these regions is intimately linked to the behavioural syndrome produced by these diverse aetiologies. In addition to these unifying features, symptom profiles also differed among pathological subtypes, suggesting distinct anatomical vulnerabilities and informing a clinician's prediction of pathological diagnosis. Data-driven classification into one of the 10 most common pathological diagnoses was most accurate (up to 60.2%) when using a combination of known predictive factors (genetic mutations, motor features, or striking atrophy patterns) and the results of a discriminant function analysis that incorporated clinical, neuroimaging, and neuropsychological data.

Objective:To compare the diagnostic performance of PET with the amyloid ligand Pittsburgh compound B (PiB-PET) to fluorodeoxyglucose (FDG-PET) in discriminating between Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD). Methods:Patients meeting clinical criteria for AD (n ϭ 62) and FTLD (n ϭ 45) underwent PiB and FDG-PET. PiB scans were classified as positive or negative by 2 visual raters blinded to clinical diagnosis, and using a quantitative threshold derived from controls (n ϭ 25). FDG scans were visually rated as consistent with AD or FTLD, and quantitatively classified based on the region of lowest metabolism relative to controls.Results: PiB visual reads had a higher sensitivity for AD (89.5% average between raters) than FDG visual reads (77.5%) with similar specificity (PiB 83%, FDG 84%). When scans were classified quantitatively, PiB had higher sensitivity (89% vs 73%) while FDG had higher specificity (83% vs 98%). On receiver operating characteristic analysis, areas under the curve for PiB (0.888) and FDG (0.910) were similar. Interrater agreement was higher for PiB ( ϭ 0.96) than FDG ( ϭ 0.72), as was agreement between visual and quantitative classification (PiB ϭ 0.88-0.92; FDG ϭ 0.64-0.68). In patients with known histopathology, overall classification accuracy (2 visual and 1 quantitative classification per patient) was 97% for PiB (n ϭ 12 patients) and 87% for FDG (n ϭ 10). Conclusions:PiB and FDG showed similar accuracy in discriminating AD and FTLD. PiB was more sensitive when interpreted qualitatively or quantitatively. FDG was more specific, but only when scans were classified quantitatively. PiB slightly outperformed FDG in patients with known histopathology. Neurology Differentiating Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD) has implications for prognosis and symptomatic treatment, 1,2 and is critical for the efforts to develop disease-specific therapies. Making an accurate diagnosis during life can be challenging given overlapping clinical features.3,4 MRI or fluorodeoxyglucose PET (FDG-PET) can improve diagnostic accuracy by demonstrating distinct topographic patterns of atrophy or hypometabolism (temporoparietal predominant in AD; frontal and anterior temporal involvement in FTLD), 5,6 but anatomic overlap between the diseases is increasingly apparent. 5,7 Consequently, many patients with pathologically confirmed FTLD are diagnosed with AD during

A recently identified variant within the fat mass and obesity-associated ( FTO ) gene is carried by 46% of Western Europeans and is associated with an ~1.2 kg higher weight, on average, in adults and an ~1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ~8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.