Association of Early Seizure Prophylaxis With Posttraumatic Seizures and Mortality: A Meta-analysis With Evidence Quality Assessment.

Purpose of the Review: To evaluate the quality of evidence about the association of primary seizure prophylaxis with antiseizure medication (ASM) within 7 days postinjury and the 18- or 24-month epilepsy/late seizure risk or all-cause mortality in adults with new-onset traumatic brain injury (TBI), in addition to early seizure risk. Results: Twenty-three studies met the inclusion criteria (7 randomized and 16 nonrandomized studies). We analyzed 9,202 patients, including 4,390 in the exposed group and 4,812 in the unexposed group (894 in placebo and 3,918 in no ASM groups). There was a moderate to serious bias risk based on our assessment. Within the limitations of existing studies, our data revealed a lower risk for early seizures in the ASM prophylaxis group compared with placebo or no ASM prophylaxis (risk ratio [RR] 0.43, 95% confidence interval [CI] 0.33-0.57, p < 0.00001, I 2 = 3%). We identified high-quality evidence in favor of acute, short-term primary ASM use to prevent early seizures. Early ASM prophylaxis was not associated with a substantial difference in the 18- or 24-month risk of epilepsy/late seizures (RR 1.01, 95% CI 0.61-1.68, p = 0.96, I 2 = 63%) or mortality (RR 1.16, 95% CI 0.89-1.51, p = 0.26, I 2 = 0%). There was no evidence of strong publication bias for each main outcome. The overall quality of evidence was low and moderate for post-TBI epilepsy risk and all-cause mortality, respectively. Summary: Our data suggest that the evidence showing no association between early ASM use and 18- or 24-month epilepsy risk in adults with new-onset TBI was of low quality. The analysis indicated a moderate quality for the evidence showing no effect on all-cause mortality. Therefore, higher-quality evidence is needed as a supplement for stronger recommendations.

Evaluating The Accuracy Of Medicare Risk Adjustment For Alzheimer's Disease And Related Dementias.

In 2020 Medicare reintroduced Alzheimer's disease and related dementias (ADRD) Hierarchical Condition Categories (HCCs) to risk-adjust Medicare Advantage and accountable care organization (ACO) payments. The potential for Medicare spending increases from this policy change are not well understood because the baseline accuracy of ADRD HCCs is uncertain. Using linked 2016-18 claims and electronic health record data from a large ACO, we evaluated the accuracy of claims-based ADRD HCCs against a reference standard of clinician-adjudicated disease. An estimated 7.5 percent of beneficiaries had clinician-adjudicated ADRD. Among those with ADRD HCCs, 34 percent did not have clinician-adjudicated disease. The false-negative and false-positive rates were 22.7 percent and 3.2 percent, respectively. Medicare spending for those with false-negative ADRD HCCs exceeded that of true positives by $14,619 per beneficiary. If, after the reintroduction of risk adjustment for ADRD, all false negatives were coded as having ADRD, expenditure benchmarks for beneficiaries with ADRD would increase by 9 percent. Monitoring ADRD coding could become challenging in the setting of concurrent incentives to decrease false-negative rates and increase false-positive rates.

Identifying Medicare Beneficiaries With Delirium.

BACKGROUND: Each year, thousands of older adults develop delirium, a serious, preventable condition. At present, there is no well-validated method to identify patients with delirium when using Medicare claims data or other large datasets. We developed and assessed the performance of classification algorithms based on longitudinal Medicare administrative data that included International Classification of Diseases, 10th Edition diagnostic codes. METHODS: Using a linked electronic health record (EHR)-Medicare claims dataset, 2 neurologists and 2 psychiatrists performed a standardized review of EHR records between 2016 and 2018 for a stratified random sample of 1002 patients among 40,690 eligible subjects. Reviewers adjudicated delirium status (reference standard) during this 3-year window using a structured protocol. We calculated the probability that each patient had delirium as a function of classification algorithms based on longitudinal Medicare claims data. We compared the performance of various algorithms against the reference standard, computing calibration-in-the-large, calibration slope, and the area-under-receiver-operating-curve using 10-fold cross-validation (CV). RESULTS: Beneficiaries had a mean age of 75 years, were predominately female (59%), and non-Hispanic Whites (93%); a review of the EHR indicated that 6% of patients had delirium during the 3 years. Although several classification algorithms performed well, a relatively simple model containing counts of delirium-related diagnoses combined with patient age, dementia status, and receipt of antipsychotic medications had the best overall performance [CV- calibration-in-the-large <0.001, CV-slope 0.94, and CV-area under the receiver operating characteristic curve (0.88 95% confidence interval: 0.84-0.91)]. CONCLUSIONS: A delirium classification model using Medicare administrative data and International Classification of Diseases, 10th Edition diagnosis codes can identify beneficiaries with delirium in large datasets.

Development and Evaluation of a Natural Language Processing Annotation Tool to Facilitate Phenotyping of Cognitive Status in Electronic Health Records: Diagnostic Study.

BACKGROUND: Electronic health records (EHRs) with large sample sizes and rich information offer great potential for dementia research, but current methods of phenotyping cognitive status are not scalable. OBJECTIVE: The aim of this study was to evaluate whether natural language processing (NLP)-powered semiautomated annotation can improve the speed and interrater reliability of chart reviews for phenotyping cognitive status. METHODS: In this diagnostic study, we developed and evaluated a semiautomated NLP-powered annotation tool (NAT) to facilitate phenotyping of cognitive status. Clinical experts adjudicated the cognitive status of 627 patients at Mass General Brigham (MGB) health care, using NAT or traditional chart reviews. Patient charts contained EHR data from two data sets: (1) records from January 1, 2017, to December 31, 2018, for 100 Medicare beneficiaries from the MGB Accountable Care Organization and (2) records from 2 years prior to COVID-19 diagnosis to the date of COVID-19 diagnosis for 527 MGB patients. All EHR data from the relevant period were extracted; diagnosis codes, medications, and laboratory test values were processed and summarized; clinical notes were processed through an NLP pipeline; and a web tool was developed to present an integrated view of all data. Cognitive status was rated as cognitively normal, cognitively impaired, or undetermined. Assessment time and interrater agreement of NAT compared to manual chart reviews for cognitive status phenotyping was evaluated. RESULTS: NAT adjudication provided higher interrater agreement (Cohen κ=0.89 vs κ=0.80) and significant speed up (time difference mean 1.4, SD 1.3 minutes; P<.001; ratio median 2.2, min-max 0.4-20) over manual chart reviews. There was moderate agreement with manual chart reviews (Cohen κ=0.67). In the cases that exhibited disagreement with manual chart reviews, NAT adjudication was able to produce assessments that had broader clinical consensus due to its integrated view of highlighted relevant information and semiautomated NLP features. CONCLUSIONS: NAT adjudication improves the speed and interrater reliability for phenotyping cognitive status compared to manual chart reviews. This study underscores the potential of an NLP-based clinically adjudicated method to build large-scale dementia research cohorts from EHRs.

Anticonvulsant Primary and Secondary Prophylaxis for Acute Ischemic Stroke Patients: A Decision Analysis.

Background and Purpose: We examined the impact of 3 anticonvulsant prophylaxis strategies on quality-adjusted life-years (QALYs) among patients with an incident acute ischemic stroke. Methods: We created a decision tree to evaluate 3 strategies: (1) long-term primary prophylaxis; (2) short-term secondary prophylaxis after an early seizure with lifetime prophylaxis if persistent or late seizures (LSs) developed; and (3) long-term secondary prophylaxis if either early, late, or persistent seizures developed. The outcome was quality-adjusted life expectancy (QALY). We created 4 base cases to simulate common clinical scenarios: (1) female patient aged 40 years with a 2% or 11% lifetime risk of an LS and a 33% lifetime risk of an adverse drug reaction (ADR); (2) male patient aged 65 years with a 6% or 29% LS risk and 60% ADR risk; (3) male patient aged 50 years with an 18% or 65% LS risk and 33% ADR risk; and (4) female patient aged 80 years with a 29% or 83% LS risk and 80% ADR risk. In sensitivity analyses, we altered the parameters and assumptions. Results: Across all 4 base cases, primary prophylaxis yielded the fewest QALYs when compared with secondary prophylaxis. For example, under scenario 1, strategies 2 and 3 resulted in 7.17 QALYs each, but strategy 1 yielded only 6.91 QALYs. Under scenario 4, strategies 2 and 3 yielded 2.85 QALYs compared with 1.40 QALYs for strategy 1. Under scenarios in which patients had higher ADR risks, strategy 2 led to the most QALYs. Conclusions: Short-term therapy with continued anticonvulsant prophylaxis only after postischemic stroke seizures arise dominates lifetime primary prophylaxis in all scenarios examined. Our findings reinforce the necessity of close follow-up and discontinuation of anticonvulsant seizure prophylaxis started during acute ischemic stroke hospitalization.

Identifying Medicare beneficiaries with dementia.

BACKGROUND/OBJECTIVES: No data exist regarding the validity of International Classification of Disease (ICD)-10 dementia diagnoses against a clinician-adjudicated reference standard within Medicare claims data. We examined the accuracy of claims-based diagnoses with respect to expert clinician adjudication using a novel database with individual-level linkages between electronic health record (EHR) and claims. DESIGN: In this retrospective observational study, two neurologists and two psychiatrists performed a standardized review of patients' medical records from January 2016 to December 2018 and adjudicated dementia status. We measured the accuracy of three claims-based definitions of dementia against the reference standard. SETTING: Mass-General-Brigham Healthcare (MGB), Massachusetts, USA. PARTICIPANTS: From an eligible population of 40,690 fee-for-service (FFS) Medicare beneficiaries, aged 65 years and older, within the MGB Accountable Care Organization (ACO), we generated a random sample of 1002 patients, stratified by the pretest likelihood of dementia using administrative surrogates. INTERVENTION: None. MEASUREMENTS: We evaluated the accuracy (area under receiver operating curve [AUROC]) and calibration (calibration-in-the-large [CITL] and calibration slope) of three ICD-10 claims-based definitions of dementia against clinician-adjudicated standards. We applied inverse probability weighting to reconstruct the eligible population and reported the mean and 95% confidence interval (95% CI) for all performance characteristics, using 10-fold cross-validation (CV). RESULTS: Beneficiaries had an average age of 75.3 years and were predominately female (59%) and non-Hispanic whites (93%). The adjudicated prevalence of dementia in the eligible population was 7%. The best-performing definition demonstrated excellent accuracy (CV-AUC 0.94; 95% CI 0.92-0.96) and was well-calibrated to the reference standard of clinician-adjudicated dementia (CV-CITL <0.001, CV-slope 0.97). CONCLUSION: This study is the first to validate ICD-10 diagnostic codes against a robust and replicable approach to dementia ascertainment, using a real-world clinical reference standard. The best performing definition includes diagnostic codes with strong face validity and outperforms an updated version of a previously validated ICD-9 definition of dementia.

Cognitive and social activities and long-term dementia risk: the prospective UK Million Women Study.

BACKGROUND: Although dementia is associated with non-participation in cognitive and social activities, this association might merely reflect the consequences of dementia, rather than any direct effect of non-participation on the subsequent incidence of dementia. Because of the slowness with which dementia can develop, unbiased assessment of any such direct effects must relate non-participation in such activities to dementia detection rates many years later. Prospective studies with long-term follow-up can help achieve this by analysing separately the first and second decade of follow-up. We report such analyses of a large, 20-year study. METHODS: The UK Million Women Study is a population-based prospective study of 1·3 million women invited for National Health Service (NHS) breast cancer screening in median year 1998 (IQR 1997-1999). In median year 2001 (IQR 2001-2003), women were asked about participation in adult education, groups for art, craft, or music, and voluntary work, and in median year 2006 (IQR 2006-2006), they were asked about reading. All participants were followed up through electronic linkage to NHS records of hospital admission with mention of dementia, the first mention of which was the main outcome. Comparing non-participation with participation in a particular activity, we used Cox regression to assess fully adjusted dementia risk ratios (RRs) during 0-4, 5-9, and 10 or more years, after information on that activity was obtained. FINDINGS: In 2001, 851 307 women with a mean age of 60 years (SD 5) provided information on participation in adult education, groups for art, craft, or music, and voluntary work. After 10 years, only 9591 (1%) had been lost to follow-up and 789 339 (93%) remained alive with no recorded dementia. Follow-up was for a mean of 16 years (SD 3), during which 31 187 (4%) had at least one hospital admission with mention of dementia, including 25 636 (3%) with a hospital admission with dementia mentioned for the first time 10 years or more after follow-up began. Non-participation in cognitive or social activities was associated with higher relative risks of dementia detection only during the first decade after participation was recorded. During the second decade, there was little association. This was true for non-participation in adult education (RR 1·04, 99% CI 0·98-1·09), in groups for art, craft, or music (RR 1·04, 0·99-1·09), in voluntary work (RR 0·96, 0·92-1·00), or in any of these three (RR 0·99, 0·95-1·03). In 2006, 655 118 women provided information on reading. For non-reading versus any reading, there were similar associations with dementia, again with strong attenuation over time since reading was recorded, but longer follow-up is needed to assess this reliably. INTERPRETATION: Life has to be lived forwards, but can be understood only backwards. Long before dementia is diagnosed, there is a progressive reduction in various mental and physical activities, but this is chiefly because its gradual onset causes inactivity and not because inactivity causes dementia. FUNDING: UK Medical Research Council, Cancer Research UK.

Patterns of anticonvulsant use and adverse drug events in older adults.

PURPOSE: To examine indications for, duration of use, and rate of adverse drug events (ADE) attributable to anticonvulsant initiation, as adjudicated by expert review of electronic health records (EHR) of older adults. METHODS: We identified a cohort of community dwelling Medicare beneficiaries with linked EHR (aged 65+, continuously enrolled with a large health system/until death between 2012 and 2014, n = 20 945) and drew a stratified EHR review sample (n = 1534). An expert reviewed all records to adjudicate anticonvulsant use, years of use, indication for use, and evidence of ADEs attributable to anticonvulsant initiation. After excluding patients with insufficient EHR data (n = 37; 2%), we reconstructed the cohort using inverse probability weights to resemble the original cohort of eligible beneficiaries (n = 20 380). Among incident users of a single anticonvulsant, we estimated the rate of ADEs and described the type and severity of ADEs. RESULTS: Overall, 12% (n = 2469) of eligible beneficiaries used at least one anticonvulsant in the 2012 to 2014 period (4% [n = 757] incident users, 8% [n = 1712] prevalent users). Incident users were most frequently prescribed gabapentin (n = 461/757, 61%), benzodiazepines (n = 122/757, 16%), and levetiracetam (n = 74/757, 10%); the most common indication was pain relief (n = 214; 28%) followed by epilepsy (n = 53; 7%). Among incident users, the overall ADE rate was 10/100 person-years (95% CI 4-20/100 person-years), of which 29% (n = 28/97) were life threatening (eg, somnolence). Most ADEs among incident monotherapy users were nervous system related (68%, n = 66/97). CONCLUSION: Many older adult community dwelling traditional Medicare beneficiaries had clinically significant ADEs likely attributable to the initiation of anticonvulsant therapy, which was begun for a range of indications.

Differences in Assessment of Everyday Preferences Between People With Cognitive Impairment and Their Care Partners: The Role of Neuropsychiatric Symptoms.

OBJECTIVE: As cognitive impairment progresses, people with dementia increasingly rely on surrogate decision-makers for everyday activities. Yet, little is known about concordance on everyday preferences between persons with cognitive impairment and their care partners. METHODS: The sample included 69 dyads of persons with cognitive impairment (Clinical Dementia Rating Scale ≥0.5) and their care partners. We used the Preferences for Everyday Living Inventory (PELI) to assess preferences for activities and lifestyle choices among persons with cognitive impairment. The PELI was concurrently but separately administered to care partners, who answered as surrogate decision-makers. Factor analysis was used to ascertain factor structure of the PELI; reliability measures were computed within the sample. Paired sample t-tests were used to estimate differences in scores of corresponding PELI items for each factor. Multiple regression models were used to relate predictors, including neuropsychiatric symptoms, to agreement levels. RESULTS: Four factors were identified from the PELI: autonomous choice, social engagement, personal growth, and keeping a routine. Significant participant-care partner discrepancy was found in "social engagement" preferences (e.g., regular contact with family, meeting new people, volunteering). Geriatric Depression Scale-15 score and care partner sex were significantly associated with participant-care partner discrepancies in "social engagement" preferences. CONCLUSION: This study yields new insights regarding the most important preferences for persons with cognitive impairment and clarifies a path to optimizing surrogate decision-making around everyday preferences by highlighting areas of apparent disagreement and identifying potential predictors of discrepancy.

Epilepsy Among Elderly Medicare Beneficiaries: A Validated Approach to Identify Prevalent and Incident Epilepsy.

BACKGROUND: Uncertain validity of epilepsy diagnoses within health insurance claims and other large datasets have hindered efforts to study and monitor care at the population level. OBJECTIVES: To develop and validate prediction models using longitudinal Medicare administrative data to identify patients with actual epilepsy among those with the diagnosis. RESEARCH DESIGN, SUBJECTS, MEASURES: We used linked electronic health records and Medicare administrative data including claims to predict epilepsy status. A neurologist reviewed electronic health record data to assess epilepsy status in a stratified random sample of Medicare beneficiaries aged 65+ years between January 2012 and December 2014. We then reconstructed the full sample using inverse probability sampling weights. We developed prediction models using longitudinal Medicare data, then in a separate sample evaluated the predictive performance of each model, for example, area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. RESULTS: Of 20,945 patients in the reconstructed sample, 2.1% had confirmed epilepsy. The best-performing prediction model to identify prevalent epilepsy required epilepsy diagnoses with multiple claims at least 60 days apart, and epilepsy-specific drug claims: AUROC=0.93 [95% confidence interval (CI), 0.90-0.96], and with an 80% diagnostic threshold, sensitivity=87.8% (95% CI, 80.4%-93.2%), specificity=98.4% (95% CI, 98.2%-98.5%). A similar model also performed well in predicting incident epilepsy (k=0.79; 95% CI, 0.66-0.92). CONCLUSIONS: Prediction models using longitudinal Medicare data perform well in predicting incident and prevalent epilepsy status accurately.

Medicare claims can identify post-stroke epilepsy.

OBJECTIVE: There have been no validated Medicare claims-based algorithms available to identify epilepsy by discrete etiology of stroke (e.g., post-stroke epilepsy, PSE) in community-dwelling elderly individuals, despite the increasing availability of large datasets. Our objective was to validate algorithms that detect which patients have true PSE. METHODS: We linked electronic health records (EHR) to Medicare claims from a Medicare Pioneer Accountable Care Organization (ACO) to identify PSE. A neurologist reviewed 01/2012-12/2014 EHR data from a stratified sample of Medicare patients aged 65+ years to adjudicate a reference-standard to develop an algorithm for identifying patients with PSE. Patient sampling strata included those with: A) epilepsy-related claims diagnosis (n = 534 [all]); B) no diagnosis but neurologist visit (n = 500 [randomly sampled from 4346]); C) all others (n = 500 [randomly sampled from 16,065]). We reconstructed the full sample using inverse probability sampling weights; then used half to derive algorithms and assess performance, and the remainder to confirm performance. We evaluated predictive performance across several measures, e.g., specificity, sensitivity, negative and positive predictive values (NPV, PPV). We selected our best performing algorithms based on the greatest specificity and sensitivity. RESULTS: Of 20,943 patients in the reconstructed sample, 13.6% of patients with epilepsy had reference-standard PSE diagnosis, which represents a 3-year overall prevalence of 0.28% or 28/10,000, and a prevalence within the subpopulation with stroke of 3%. The best algorithm included three conditions: (a) at least one cerebrovascular claim AND one epilepsy-specific anticonvulsant OR (b) at least one cerebrovascular claim AND one electroencephalography claim (specificity 100.0% [95% CI 99.9%-100.0%], NPV 98.8% [98.6%-99.0%], sensitivity 20.6% [95% CI 14.6%-27.9%], PPV 86.5% [95% CI 71.2%-95.5%]). CONCLUSION: Medicare claims can identify elderly Medicare beneficiaries with PSE with high accuracy. Future epidemiological surveillance of epilepsy could incorporate similar algorithms to accurately identify epilepsy by varying etiologies.

Mediators of First- Versus Second-generation Antipsychotic-related Mortality in Older Adults.

BACKGROUND: Observational studies of older adults showed higher mortality for first-generation antipsychotics than their second- generation counterparts, which led to US Food and Drug Administration warnings, but the actual mechanisms involved remain unclear. METHODS: A cohort of 9,060 initiators of first-generation antipsychotics and 17,137 of second-generation antipsychotics enrolled in New Jersey and Pennsylvania Medicare were followed for 180 days. Medical events were assessed using diagnostic and procedure codes on inpatient billing claims. For the individual and joint set of medical events (mediators), we estimated the total, direct, and indirect effects of antipsychotic type (first versus second generation) on mortality on the risk ratio scale and the proportion mediated on the risk difference scale, obtaining 95% confidence intervals through bootstrapping. We performed bias analyses for false-negative mediator misclassification in claims data, with sensitivity ranging from 0.25 to 0.75. RESULTS: There were 3,199 deaths (outcomes), 862 cardiovascular events, 675 infectious events, and 491 hip fractures (potential mediators). Mortality was higher for first- than second-generation antipsychotic initiators (adjusted risk ratio: 1.14; 95% confidence interval: 1.06, 1.22). In naïve analyses, that ignored potential misclassification, less than 4% of this difference was explained by any particular medical event. In bias analyses, the proportion mediated ranged from 6% to 16% for stroke, 3% to 9% for ventricular arrhythmia, 3% to 11% for myocardial infarction, 0% venous thromboembolism, 3% to 9% for pneumonia, 0% to 1% for other bacterial infection, and 1% to 3% for hip fracture. CONCLUSIONS: Acute cardiovascular events and pneumonia may explain part of the mortality difference between first- and second-generation antipsychotic initiators in this analysis.

Health-care use and cost in dementia caregivers: Longitudinal results from the Predictors Caregiver Study.

OBJECTIVE: To examine the effects of caregiver and patient characteristics on caregivers' medical care use and cost. METHODS: One hundred forty-seven caregiver/patient dyads were followed annually for 6 years in three academic Alzheimer's disease centers in the United States. Logistic, negative binomial, and generalized linear mixed models were used to examine overall effects of caregiver/patient characteristics on caregivers' hospitalizations, doctor visits, outpatient tests and procedures, and prescription and over-the-counter medications. RESULTS: Patients' comorbid conditions and dependence were associated with increased health-care use and costs of caregivers. Increases in caregiver depressive symptoms are associated with increases in multiple domains of caregivers' health-care use and costs. DISCUSSION: Findings suggest expanding our focus on dementia patients to include family caregivers to obtain a fuller picture of effects of caregiving. Primary care providers should integrate caregivers' needs in health-care planning and delivery. Clinical interventions that treat patients and caregivers as a whole will likely achieve the greatest beneficial effects.

The explanatory role of stroke as a mediator of the mortality risk difference between older adults who initiate first- versus second-generation antipsychotic drugs.

Antipsychotic drugs are used to treat dementia-related symptoms in older adults, and observational studies show higher risks of death and stroke associated with the use of first-generation antipsychotic drugs (FGAs) compared with second-generation antipsychotic drugs (SGAs). However, the extent to which stroke explains the differential mortality risk between FGA use and SGA use in older adults is unclear. We followed those who initiated use of antipsychotic drugs (9,777 FGA users and 21,164 SGA users) aged 65 years or older, and who were enrolled in Medicare and either the New Jersey or Pennsylvania pharmacy assistance program during 1994 to 2005, over 180 days for the outcomes of stroke and death. We estimated direct and indirect effects by comparing 180-day mortality risks associated with the use of FGAs versus SGAs as mediated by stroke on the risk ratio scale, as well as the proportion mediated on the risk difference scale. FGA use was associated with marginally higher risks of stroke (risk ratio =1.24, 95% confidence interval (CI): 1.01, 1.53) and death (risk ratio = 1.15, 95% CI: 1.08, 1.22) compared with SGA use, but stroke explained little (2.7%) of the observed difference in mortality risk. The indirect effect was null (risk ratio = 1.004, 95% CI: 1.000, 1.008), and the direct effect was equal to the total effect of antipsychotic drug type (FGA vs. SGA) on mortality risk (risk ratio = 1.15, 95% CI: 1.08, 1.22). These results suggest that the difference in mortality risk between users of FGAs and SGAs may develop mostly through pathways that do not involve stroke.

Genome scan of age-at-onset in the NIMH Alzheimer disease sample uncovers multiple loci, along with evidence of both genetic and sample heterogeneity.

Alzheimer's disease (AD) is a common neurodegenerative disorder of late life with a complex genetic basis. Although several genes are known to play a role in rare early onset AD, only the APOE gene is known to have a high contribution to risk of the common late-onset form of the disease (LOAD, onset >60 years). APOE genotypes vary in their AD risk as well as age-at-onset distributions, and it is likely that other loci will similarly affect AD age-at-onset. Here we present the first analysis of age-at-onset in the NIMH LOAD sample that allows for both a multilocus trait model and genetic heterogeneity among the contributing sites, while at the same time accommodating age censoring, effects of known genetic covariates, and full pedigree and marker information. The results provide evidence for genomic regions not previously implicated in this data set, including regions on chromosomes 7q, 15, and 19p. They also affirm evidence for loci on chromosomes 1q, 6p, 9q, 11, and, of course, the APOE locus on 19q, all of which have been reported previously in the same sample. The analyses failed to find evidence for linkage to chromosome 10 with inclusion of unaffected subjects and extended pedigrees. Several regions implicated in these analyses in the NIMH sample have been previously reported in genome scans of other AD samples. These results, therefore, provide independent confirmation of AD loci in family-based samples on chromosomes 1q, 7q, 19p, and suggest that further efforts towards identifying the underlying causal loci are warranted.

Assessment of Alzheimer's disease case-control associations using family-based methods.

The genetics of Alzheimer's disease (AD) is heterogeneous and remains only ill-defined. We have recently created a freely available and continuously updated online database (AlzGene; http://www.alzgene.org ) for which we collect all published genetic association studies in AD and perform systematic meta-analyses on all polymorphisms with sufficient genotype data. In this study, we tested 27 genes (ACE, BDNF, CH25H, CHRNB2, CST3, CTSD, DAPK1, GALP, hCG2039140, IL1B, LMNA, LOC439999, LOC651924, MAPT, MTHFR, MYH13, PCK1, PGBD1, PRNP, PSEN1, SORCS1, SORL1, TF, TFAM, TNK1, GWA_14q32.13, and GWA_7p15.2), all showing significant association with AD risk in the AlzGene meta-analyses, in a large collection of family-based samples comprised of 4,180 subjects from over 1,300 pedigrees. Overall, we observe significant association with risk for AD and polymorphisms in ACE, CHRNB2, TF, and an as yet uncharacterized locus on chromosome 7p15.2 [rs1859849]. For all four loci, the association was observed with the same alleles as in the AlzGene meta-analyses. The convergence of case-control and family-based findings suggests that these loci currently represent the most promising AD gene candidates. Further fine-mapping and functional analyses are warranted to elucidate the potential biochemical mechanisms and epidemiological relevance of these genes.

Patient dependence and longitudinal changes in costs of care in Alzheimer's disease.

BACKGROUND/AIMS: To examine the incremental effect of patients' dependence on others, on cost of medical and nonmedical care, and on informal caregiving hours over time. METHODS: Data are obtained from 172 patients from the Predictors Study, a large, multicenter cohort of patients with probable Alzheimer disease (AD) followed annually for 4 years in 3 University-based AD centers in the USA. Enrollment required a modified Mini-Mental State Examination score >or=30. We examined the effects of patient dependence (measured by the Dependence Scale, DS) and function (measured by the Blessed Dementia Rating Scale, BDRS) on medical care cost, nonmedical care cost, and informal caregiving time using random effects regression models. RESULTS: A one-point increase in DS score was associated with a 5.7% increase in medical cost, a 10.5% increase in nonmedical cost, and a 4.1% increase in caregiving time. A one-point increase in BDRS score was associated with a 7.6% increase in medical cost, a 3.9% increase in nonmedical cost and an 8.7% increase in caregiving time. CONCLUSIONS: Both functional impairment and patient dependence were associated with higher costs of care and caregiving time. Measures of functional impairment and patient dependence provide unique and incremental information on the overall impact of AD on patients and their caregivers.

The effects of patient function and dependence on costs of care in Alzheimer's disease.

OBJECTIVES: To estimate incremental effects of patients' dependence and function on costs of care during the early stages of Alzheimer's disease (AD) and to compare strengths of their relationships with different cost components. DESIGN: Multicenter, cross-sectional, observational study. SETTING: Three university hospitals in the United States. PARTICIPANTS: One hundred seventy-nine community-living patients with probable AD, with modified Mini-Mental State Examination scores of 30 or higher. MEASUREMENTS: Patients' dependence was measured using the Dependence Scale (DS). Functional capacity was measured using the Blessed Dementia Rating Scale (BDRS). Total cost was measured by summing direct medical costs and informal costs. Direct medical costs included costs of hospitalization, outpatient treatment and procedures, assistive devices, and medications. Informal costs were estimated from time spent helping with basic and instrumental activities of daily living for up to three caregivers per patient using national average hourly earnings as wage rate. RESULTS: DS and BDRS were associated with higher total cost; a 1-point increase in DS was associated with a $1,832 increase in total cost, and a 1-point increase in BDRS was associated with a $3,333 increase. Examining component costs separately identified potential differences between DS and BDRS. A 1-point increase in BDRS was associated with a $1,406 increase in direct medical cost. A 1-point increase in DS was associated with a $1,690 increase in informal cost. CONCLUSION: Patients' dependence and function related differently to direct medical and informal cost, suggesting that measures of function and dependence provided unique information for explaining variations in cost of care for patients with AD, highlighting the value in measuring both constructs.

Comparison of costs of care between patients with Alzheimer's disease and dementia with Lewy bodies.

BACKGROUND: The objective of this study was to compare total costs of care and its major components for community-living patients with Alzheimer's disease (AD) or dementia with Lewy bodies (DLB). This cross-sectional analysis of baseline data from the Predictors II Study took place in three university-based AD centers in the U.S. METHODS: Community-living patients clinically diagnosed with probable AD (n = 170) or DLB (n = 25) with a modified Mini-Mental State examination (mMMS) score > or =30, equivalent to a score of approximately > or =16 on the Folstein Mini-Mental State Examination (MMSE), participated in this study. Patient and informant reported on patients' use of direct medical care, direct nonmedical care, and informal care. Patients' clinical and demographic characteristics included global cognitive status (measured by MMSE), functional capacity (measured by Blessed Dementia Rating Scale), psychotic symptoms, behavioral problems, depressive symptoms, extrapyramidal signs, comorbidities, age, and sex. Costs were compared by using covariate matching methods. RESULTS: Unadjusted total costs and direct medical costs were not significantly different between AD and DLB patients. Compared with AD patients, unadjusted indirect costs were significantly higher and unadjusted direct nonmedical costs were significantly lower among DLB patients. After adjusting for age, sex, cognitive and functional status, differences in all cost components between DLB and AD patients were no longer statistically significant. CONCLUSIONS: Apparent cost differences were largely attributed to differences in patients' cognitive and functional status. However, the small sample size for DLB patients might have limited power to detect statistically significant differences in costs of care between these groups.

Home health and informal care utilization and costs over time in Alzheimer's disease.

OBJECTIVES: To (1) compare home health and informal (unpaid) services utilization among patients with Alzheimer's disease (AD), (2) examine longitudinal changes in services use, and (3) estimate possible interdependence of home health and informal care utilization. METHODS: The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers. Bivariate probit models estimated the effects of patient characteristics on home health and informal care utilization. RESULTS: A large majority of the patients (80.6%) received informal care with a smaller proportion (18.6%) receiving home health services. Home health services utilization increased from 9.9% at baseline to 34.5% in year 4. Among users, number of days that services were provided in three-month recall increased from 21.9 to 56 days over time. Home health services utilization was significantly associated with function, depressive symptoms, being female, and not living with a spouse. Informal care utilization was significantly associated with cognition, function, comorbidities, and living with a spouse or child. CONCLUSIONS: Home health and informal care utilization relate differently to patient characteristics. Utilization of home health care or informal care was not influenced by utilization of the other.