Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants.

INTRODUCTION: We estimated the ages when associations between Alzheimer's disease (AD) genes and brain volumes begin among middle-aged and older adults. METHODS: Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume. RESULTS: AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices. DISCUSSION: APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Considerations for Use of Blood-Based Biomarkers in Epidemiologic Dementia Research.

Dementia represents a growing public health burden with large social, racial, and ethnic disparities. The etiology of dementia is poorly understood, and the lack of robust biomarkers in diverse, population-representative samples is a barrier to moving dementia research forward. Existing biomarkers and other measures of pathology-derived from neuropathology, neuroimaging, and cerebrospinal fluid samples-are commonly collected from predominantly White and highly educated samples drawn from academic medical centers in urban settings. Blood-based biomarkers are noninvasive and less expensive, offering promise to expand our understanding of the pathophysiology of dementia, including in participants from historically excluded groups. Although largely not yet approved by the Food and Drug Administration or used in clinical settings, blood-based biomarkers are increasingly included in epidemiologic studies on dementia. Blood-based biomarkers in epidemiologic research may allow the field to more accurately understand the multifactorial etiology and sequence of events that characterize dementia-related pathophysiological changes. As blood-based dementia biomarkers continue to be developed and incorporated into research and practice, we outline considerations for using them in dementia epidemiology, and illustrate key concepts with Alzheimer's Disease Neuroimaging Initiative (2003-present) data. We focus on measurement, including both validity and reliability, and on the use of dementia blood-based biomarkers to promote equity in dementia research and cognitive aging. This article is part of a Special Collection on Mental Health.

Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk.

INTRODUCTION: Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS: In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS: Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION: Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. HIGHLIGHTS: We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

Estimated effects of amyloid reduction on cognitive change: A Bayesian update across a range of priors.

INTRODUCTION: The results of the CLARITY-AD, GRADUATE I and II, and TRAILBLAZER-ALZ 2 trials have rekindled discussion on the impact of amyloid-targeting drugs. We use a Bayesian approach to quantify how rational observers would have updated their prior beliefs based on new trial results. METHODS: We used publicly available data from the CLARITY-AD, GRADUATE I and II, and TRAILBLAZER-ALZ 2 trials to estimate the effect of reducing amyloid on the clinical dementia rating scale, sum of boxes (CDR-SB) score. A range of prior positions were then updated according to Bayes' theorem using these estimates. RESULTS: After updating with new trial data, a wide range of starting positions resulted in credible intervals that did not include no effect of amyloid reduction on CDR-SB score. DISCUSSION: For a range of starting beliefs and assuming the veracity of the underlying data, rational observers would conclude there is a small benefit of amyloid reductions on cognition. This benefit must be weighed against opportunity cost and side-effect risk. HIGHLIGHTS: The results of recent trials of amyloid-targeting drugs have rekindled discussion on the impact of amyloid reductions achieved with amyloid-targeting drugs on cognition. Prior to the announcement of trial results, beliefs about the effects of altering amyloid levels varied. For a range of starting beliefs, one would conclude there is a small benefit of amyloid reductions due to amyloid-targeting drugs on cognition. The perceived value of individual drugs must balance the magnitude of this benefit against opportunity cost and risk of side effects.

Metformin Cessation and Dementia Incidence.

Importance: Prior studies suggested that metformin may be associated with reduced dementia incidence, but associations may be confounded by disease severity and prescribing trends. Cessation of metformin therapy in people with diabetes typically occurs due to signs of kidney dysfunction but sometimes is due to less serious adverse effects associated with metformin. Objective: To investigate the association of terminating metformin treatment for reasons unrelated to kidney dysfunction with dementia incidence. Design, Setting, and Participants: This cohort study was conducted at Kaiser Permanente Northern California, a large integrated health care delivery system, among a cohort of metformin users born prior to 1955 without history of diagnosed kidney disease at metformin initiation. Dementia follow-up began with the implementation of electronic health records in 1996 and continued to 2020. Data were analyzed from November 2021 through September 2023. Exposures: A total of 12 220 early terminators, individuals who stopped metformin with normal estimated glomerular filtration rate (eGFR), were compared with routine metformin users, who had not yet terminated metformin treatment or had terminated (with or without restarting) after their first abnormal eGFR measurement. Early terminators were matched with routine users of the same age and gender who had diabetes for the same duration. Main outcomes and measures: The outcome of interest was all-cause incident dementia. Follow-up for early terminators and their matched routine users was started at age of termination for the early terminator. Survival models adjusted for sociodemographic characteristics and comorbidities at the time of metformin termination (or matched age). Mediation models with HbA1c level and insulin usage 1 and 5 years after termination tested whether changes in blood glucose or insulin usage explained associations between early termination of metformin and dementia incidence. Results: The final analytic sample consisted of 12 220 early terminators (5640 women [46.2%]; mean [SD] age at start of first metformin prescription, 59.4 [9.0] years) and 29 126 routine users (13 582 women [46.6%]; mean [SD] age at start of first metformin prescription, 61.1 [8.9] years). Early terminators had 1.21 times the hazard of dementia diagnosis compared with routine users (hazard ratio, 1.21; 95% CI, 1.12 to 1.30). In mediation analysis, contributions to this association by changes in HbA1c level or insulin use ranged from no contribution (0.00 years; 95% CI, -0.02 to 0.02 years) for insulin use at 5 years after termination to 0.07 years (95% CI, 0.02 to 0.13 years) for HbA1c level at 1 year after termination, suggesting that the association was largely independent of changes in HbA1c level and insulin usage. Conclusions and Relevance: In this study, terminating metformin treatment was associated with increased dementia incidence. This finding may have important implications for clinical treatment of adults with diabetes and provides additional evidence that metformin is associated with reduced dementia risk.

Association between cancer and dementia risk in the UK Biobank: evidence of diagnostic bias.

Epidemiological studies have identified an inverse association between cancer and dementia. Underlying methodological biases have been postulated, yet no studies have systematically investigated the potential for each source of bias within a single dataset. We used the UK Biobank to compare estimates for the cancer-dementia association using different analytical specifications designed to sequentially address multiple sources of bias, including competing risk of death, selective survival, confounding bias, and diagnostic bias. We included 140,959 UK Biobank participants aged ≥ 55 without dementia before enrollment and with linked primary care data. We used cancer registry data to identify cancer cases prevalent before UK Biobank enrollment and incident cancer diagnosed after enrollment. We used Cox models to evaluate associations of prevalent and incident cancer with all-cause dementia, Alzheimer's disease (AD), and vascular dementia. We used time-varying models to evaluate diagnostic bias. Over a median follow-up of 12.3 years, 3,310 dementia cases were diagnosed. All-site incident cancer was positively associated with all-cause dementia incidence (hazard ratio [HR] = 1.14, 95% CI: 1.02-1.29), but prevalent cancer was not (HR = 1.04, 95% CI: 0.92-1.17). Results were similar for vascular dementia. AD was not associated with prevalent or incident cancer. Dementia diagnosis was substantially elevated in the first year after cancer diagnosis (HR = 1.83, 95% CI: 1.42-2.36), after which the association attenuated to null, suggesting diagnostic bias. Following a cancer diagnosis, health care utilization or cognitive consequences of diagnosis or treatment may increase chance of receiving a dementia diagnosis, creating potential diagnostic bias in electronic health records-based studies.

Key questions for the evaluation of anti-amyloid immunotherapies for Alzheimer's disease.

The clinical benefit associated with anti-amyloid immunotherapies, a new class of drugs for the treatment of Alzheimer's disease, is predicated on their ability to modify disease course by lowering brain amyloid levels. At the time of writing, two amyloid-lowering antibodies, aducanumab and lecanemab, have obtained United States Food and Drug Administration accelerated approval, with further agents of this class in the Alzheimer's disease treatment pipeline. Based on limited published clinical trial data to date, regulators, payors and physicians will need to assess their efficacy, clinical effectiveness and safety, as well as cost and accessibility. We propose that attention to three important questions related to treatment efficacy, clinical effectiveness and safety should guide evidence-based consideration of this important class of drugs. These are: (1) Were trial statistical analyses appropriate and did they convincingly support claims of efficacy? (2) Do reported treatment effects outweigh safety concerns and are they generalizable to a representative clinical population of people with Alzheimer's disease? and (3) Do the data convincingly demonstrate disease course modification, suggesting that increasing clinical benefits beyond the duration of the trials are likely? We suggest specific approaches to interpreting trial results for these drugs and highlight important areas of uncertainty where additional data and a cautious interpretation of existing results is warranted. Safe, effective and accessible treatments for Alzheimer's disease are eagerly awaited by millions of patients and their caregivers worldwide. While amyloid-targeting immunotherapies may be promising disease-modifying Alzheimer's disease treatments, rigorous and unbiased assessment of clinical trial data is critical to regulatory decision-making and subsequently determining their provision and utility in routine clinical practice. Our recommendations provide a framework for evidence-based appraisal of these drugs by regulators, payors, physicians and patients.

Pragmatic approaches to handling practice effects in longitudinal cognitive aging research.

INTRODUCTION: The challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID-19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory. METHODS: In three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data. RESULTS: APM-based correction for PEs based on balanced, pre-pandemic data, and with current age as the timescale produced the smallest discrepancy between within-person and between-person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used. DISCUSSION: Constraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change. HIGHLIGHTS: The magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age-related cognitive trajectories. Estimated age-related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

Estimated Effects of Amyloid Reduction on Cognitive Change: A Bayesian Update across a Range of Priors.

Introduction: Results of the CLARITY-AD and GRADUATE I and II trials rekindled discussion on the impact of amyloid-targeting drugs. We use a Bayesian approach to quantify how a rational observer would have updated their prior beliefs based on new trial results. Methods: We used publicly available data from the CLARITY-AD and GRADUATE I & II trials to estimate the effect of reducing amyloid on CDR-SB score. A range of prior positions were then updated according to Bayes Theorem using these estimates. Results: After updating with new trial data, a wide range of starting positions resulted in credible intervals that did not include no effect of amyloid reduction on CDR-SB. Discussion: For a range of starting beliefs and assuming veracity of underlying data, rational observers would conclude there is a small benefit of amyloid-reductions on cognition. This benefit must be weighed against opportunity cost and side effect risk.

Education, incident cancer, and rate of memory decline in a national sample of US adults in mid-to-later-life.

INTRODUCTION: Middle-aged and older adults who develop cancer experience memory loss following diagnosis, but memory decline in the years before and after cancer diagnosis is slower compared to their cancer-free counterparts. Educational attainment strongly predicts memory function during aging, but it is unclear whether education protects against memory loss related to cancer incidence or modifies long-term memory trajectories in middle-aged and older cancer survivors. MATERIALS AND METHODS: Data were from 14,449 adults (3,248 with incident cancer, excluding non-melanoma skin cancer) aged 50+ in the population-based US Health and Retirement Study from 1998 to 2016. Memory was assessed every two years as a composite of immediate and delayed word recall tests and proxy assessments for impaired individuals. Memory scores all time points were standardized at to the baseline distribution. Using multivariate-adjusted linear mixed-effects models, we estimated rates of memory decline in the years before cancer diagnosis, shortly after diagnosis, and in the years after diagnosis. We compared rates of memory decline between incident cancer cases and age-matched cancer-free adults, overall and according to level of education (<12 years, "low"; 12 to <16 years, "intermediate"; ≥16 years, "high"). RESULTS: Incident cancer diagnoses were followed by short-term declines in memory averaging 0.06 standard deviation (SD) units (95% confidence interval [CI]: -0.084, -0.036). Those with low education experienced the strongest magnitude of short-term decline in memory after diagnosis (-0.10 SD units, 95% CI: -0.15, -0.05), but this estimate was not statistically significantly different from the short-term decline in memory experienced by those with high education (-0.04 SD units, 95% CI: -0.08, 0.01; p-value for education as an effect modifier = 0.15). In the years prior to and following an incident cancer diagnosis, higher educational attainment was associated with better memory, but it did not modify the difference in rate of long-term memory decline between cancer survivors and those who remained cancer-free. DISCUSSION: Education was associated with better memory function over time among both cancer survivors and cancer-free adults aged 50 and over. Low education may be associated with a stronger short-term decline in memory after a cancer diagnosis.

Discordance in chromosomal and self-reported sex in the UK Biobank: Implications for transgender- and intersex-inclusive data collection.

There is growing need to distinguish between sex and gender. While sex is assigned at birth, gender is socially constructed and may not correspond to one's assigned sex. However, in most research studies, sex or gender is assessed in isolation or the terms are used interchangeably, which has implications for research accuracy and inclusivity. We used data from the UK Biobank to quantify the prevalence of disagreement between chromosomal and self-reported sex and identify potential reasons for discordance. Among approximately 200 individuals with sex discordance, 71% of discordances were potentially explained by the presence of intersex traits or transgender identity. The findings indicate that when describing sex- and/or gender-specific differences in health, researchers may be limited in their ability to draw conclusions regarding specific sex and/or gender health information.

Associations Between Handgrip Strength and Dementia Risk, Cognition, and Neuroimaging Outcomes in the UK Biobank Cohort Study.

Importance: The associations between muscle strength and cognitive outcomes have sparked interest in interventions that increase muscle strength for prevention of dementia, but the associations between muscle strength and cognitive aging are unclear, particularly among middle-aged adults. Objective: To evaluate the association between handgrip strength (HGS) and dementia, reduced cognition, and poorer neuroimaging outcomes in a UK population of middle-aged adults. Design, Setting, and Participants: This cohort study evaluated UK Biobank participants aged 39 to 73 years enrolled from 2006 to 2010 with measured HGS and prospectively followed up for dementia diagnosis. Data were analyzed from October 2021 to April 2022. Exposures: HGS assessed in both hands via dynamometer. Main Outcomes and Measures: Outcomes included cognitive test scores (fluid intelligence and prospective memory), brain magnetic resonance imaging measures (total brain volume, white matter hyperintensity, and hippocampal volume), and incident dementia (all-cause, vascular, and Alzheimer disease [AD] from primary care, hospital, or death records) over a median (IQR) of 11.7 (11.0-12.4) years of follow-up. Mixed-effects linear and logistic regressions and Cox proportional-hazard models were used to estimate associations, stratified by gender and adjusted for covariates. Estimates are presented per 5-kg decrement in HGS. To evaluate reverse causation, we assessed whether a polygenic risk score for AD is associated with HGS. Results: A subsample of 190 406 adult participants in the UK Biobank (mean [SD] age, 56.5 [8.1] years; 102 735 women [54%]) were evaluated. A 5-kg decrement in HGS was associated with lower fluid intelligence scores in men (ß, -0.007; 95% CI, -0.010 to -0.003) and women (ß, -0.04; 95% CI, -0.05 to -0.04. A 5-kg decrement in HGS was associated with worse odds of correctly responding to a prospective memory task for men (odds ratio, 0.91; 95% CI, 0.90 to 0.92) and women (odds ratio, 0.88; 95% CI, 0.87 to 0.90). A 5-kg decrement in HGS was associated with greater white matter hyperintensity volume in men (ß, 92.22; 95% CI, 31.09 to 153.35) and women (ß, 83.56; 95% CI, 13.54 to 153.58). A 5-kg decrement in HGS was associated with incident dementia for men (hazard ratio, 1.20; 95% CI, 1.12 to 1.28) and women (hazard ratio, 1.12; 95% CI, 1.00 to 1.26). The AD genetic risk score was not significantly associated with HGS. Conclusions and Relevance: These findings suggest that HGS is associated with measures of neurocognitive brain health among men and women and they add to a growing body of research indicating that interventions designed to increase muscle strength, particularly among middle-aged adults, may hold promise for the maintenance of neurocognitive brain health.

Association of Genetic Variants Linked to Late-Onset Alzheimer Disease With Cognitive Test Performance by Midlife.

Importance: Identifying the youngest age when Alzheimer disease (AD) influences cognition and the earliest affected cognitive domains will improve understanding of the natural history of AD and approaches to early diagnosis. Objective: To evaluate the age at which cognitive differences between individuals with higher compared with lower genetic risk of AD are first apparent and which cognitive assessments show the earliest difference. Design, Setting, and Participants: This cross-sectional study used data from UK Biobank participants of European genetic ancestry, aged 40 years or older, who contributed genotypic and cognitive test data from January 1, 2006, to December 31, 2015. Data analysis was performed from March 10, 2020, to January 4, 2022. Exposure: The AD genetic risk score (GRS), which is a weighted sum of 23 single-nucleotide variations. Main Outcomes and Measures: Seven cognitive tests were administered via touchscreen at in-person visits or online. Cognitive domains assessed included fluid intelligence, episodic memory, processing speed, executive functioning, and prospective memory. Multiple cognitive measures were derived from some tests, yielding 32 separate measures. Interactions between age and AD-GRS for each of the 32 cognitive measures were tested with linear regression using a Bonferroni-corrected P value threshold. For cognitive measures with significant evidence of age by AD-GRS interaction, the youngest age of interaction was assessed with new regression models, with nonlinear specification of age terms. Models with youngest age of interaction from 40 to 70 years, in 1-year increments, were compared, and the best-fitting model for each cognitive measure was chosen. Results across cognitive measures were compared to determine which cognitive indicators showed earliest AD-related change. Results: A total of 405 050 participants (mean [SD] age, 57.1 [7.9] years; 54.1% female) were included. Sample sizes differed across cognitive tests (from 12 455 to 404 682 participants). The AD-GRS significantly modified the association with age on 13 measures derived from the pairs matching (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.5%-11.5%), symbol digit substitution (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.0%-5.8%), and numeric memory tests (difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 8.8%) (P = 1.56 × 10-3). Best-fitting models suggested that cognitive scores of individuals with a high vs low AD-GRS began to diverge by 56 years of age for all 13 measures and by 47 years of age for 9 measures. Conclusions and Relevance: In this cross-sectional study, by early midlife, subtle differences in memory and attention were detectable among individuals with higher genetic risk of AD.

Dynamical Modeling as a Tool for Inferring Causation.

Dynamical models, commonly used in infectious disease epidemiology, are formal mathematical representations of time-changing systems or processes. For many chronic disease epidemiologists, the link between dynamical models and predominant causal inference paradigms is unclear. In this commentary, we explain the use of dynamical models for representing causal systems and the relevance of dynamical models for causal inference. In certain simple settings, dynamical modeling and conventional statistical methods (e.g., regression-based methods) are equivalent, but dynamical modeling has advantages over conventional statistical methods for many causal inference problems. Dynamical models can be used to transparently encode complex biological knowledge, interference and spillover, effect modification, and variables that influence each other in continuous time. As our knowledge of biological and social systems and access to computational resources increases, there will be growing utility for a variety of mathematical modeling tools in epidemiology.

The Role of Dementia Diagnostic Delay in the Inverse Cancer-Dementia Association.

BACKGROUND: Cancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history. METHODS: We used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to U.S. population and cohort data. We varied the average lapse between dementia onset and diagnosis, including nondifferential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis. RESULTS: Nondifferential dementia diagnosis delay introduced minimal bias (IRRs = 0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR = 0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias. CONCLUSIONS: Delays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.

Proof of Concept Example for Use of Simulation to Allow Data Pooling Despite Privacy Restrictions.

BACKGROUND: Integrating results from multiple samples is often desirable, but privacy restrictions may preclude full data pooling, and most datasets do not include fully harmonized variable sets. We propose a simulation-based method leveraging partial information across datasets to guide creation of synthetic data based on explicit assumptions about the underlying causal structure that permits pooled analyses that adjust for all desired confounders in the context of privacy restrictions. METHODS: This proof-of-concept project uses data from the Health and Retirement Study (HRS) and Atherosclerosis Risk in Communities (ARIC) study. We specified an estimand of interest and a directed acyclic graph (DAG) summarizing the presumed causal structure for the effect of glycated hemoglobin (HbA1c) on cognitive change. We derived publicly reportable statistics to describe the joint distribution of each variable in our DAG. These summary estimates were used as data-generating rules to create synthetic datasets. After pooling, we imputed missing covariates in the synthetic datasets and used the synthetic data to estimate the pooled effect of HbA1c on cognitive change, adjusting for all desired covariates. RESULTS: Distributions of covariates and model coefficients and associated standard errors for our model estimating the effect of HbA1c on cognitive change were similar across cohort-specific original and preimputation synthetic data. The estimate from the pooled synthetic incorporates control for confounders measured in either original dataset. DISCUSSION: Our approach has advantages over meta-analysis or individual-level pooling/data harmonization when privacy concerns preclude data sharing and key confounders are not uniformly measured across datasets.

Amyloid-PET imaging offers small improvements in predictions of future cognitive trajectories.

BACKGROUND: Amyloid ß (Aß) is thought to initiate a cascade of pathology culminating in Alzheimer's disease-related cognitive decline. Aß accumulation in brain tissues may begin one to two decades prior to clinical diagnosis of Alzheimer's disease. Prior studies have demonstrated that Aß detected in vivo with positron emission tomography with amyloid ligands (amyloid-PET) predicts contemporaneously measured cognition and future cognitive trajectories. Prior studies have not evaluated the added value of Aß measures in predicting future cognition when repeated past cognitive measures are available. We evaluated the extent to which amyloid-PET improves prediction of future cognitive changes over and above predictions based only on sociodemographics and past cognitive measures. METHODS: We used data from participants in the University of California Davis Alzheimer's Disease Research cohort who were cognitively normal at baseline, participated in amyloid-PET imaging, and completed at least three cognitive assessments prior to amyloid-PET imaging (N = 132 for memory andN = 135 for executive function). We used sociodemographic and cognitive measures taken prior to amyloid-PET imaging to predict cognitive trajectory after amyloid-PET imaging and assessed whether measures of amyloid burden improved predictions of subsequent cognitive change. Improvements in prediction were characterized as percent reduction in the mean squared error (MSE) in predicted cognition post amyloid-PET and increase in percent variance explained. RESULTS: The base model using only sociodemographics and past cognitive performance explained the majority of variance in both predicted memory measures (55.6%) and executive function measures (74.5%) following amyloid-PET. Adding amyloid positivity to the model reduced the MSE for memory by 0.2%, 95% CI: (0%, 2.6%), p = 0.48 and for executive function by 3.4%, 95% CI: (0.6%, 10.2%), p = 0.002. This corresponded to an increase in the percent variance explained of 0.1%, 95% CI: (0%, 1.2%) for memory and 0.9%, 95% CI: (0.1%, 2.8%) for executive function. Similar results were obtained using a continuous measure of amyloid burden. CONCLUSION: In this cohort, the addition of amyloid burden slightly improved predictions of executive function compared to models based only on past cognitive assessments and sociodemographics. When repeated cognitive assessments are available, the additional utility of amyloid-PET in predicting future cognitive impairment may be limited.

A Randomized Study to Assess the Effect of Including the Graduate Record Examinations Results on Reviewer Scores for Underrepresented Minorities.

Whether requiring Graduate Record Examinations (GRE) results for doctoral applicants affects the diversity of admitted cohorts remains uncertain. This study randomized applications to 2 population-health doctoral programs at the University of California San Francisco to assess whether masking reviewers to applicant GRE results differentially affects reviewers' scores for underrepresented minority (URM) applicants from 2018-2020. Applications with GRE results and those without were randomly assigned to reviewers to designate scores for each copy (1-10, 1 being best). URM was defined as self-identification as African American/Black, Filipino, Hmong, Vietnamese, Hispanic/Latinx, Native American/Alaska Native, or Native Hawaiian/Other Pacific Islander. We used linear mixed models with random effects for the applicant and fixed effects for each reviewer to evaluate the effect of masking the GRE results on the overall application score and whether this effect differed by URM status. Reviewer scores did not significantly differ for unmasked versus masked applications among non-URM applicants (ß = 0.15; 95% CI: -0.03, 0.33) or URM applicants (ß = 0.02, 95% CI: -0.49, 0.54). We did not find evidence that removing GREs differentially affected URM compared with non-URM students (ß for interaction = -0.13, 95% CI: -0.55, 0.29). Within these doctoral programs, results indicate that GRE scores neither harm nor help URM applicants.