Heterogeneity in the effect of type 2 diabetes on dementia incidence in a diverse cohort of Asian American and non-Latino White older adults.

Dementia incidence is lower among Asian Americans than Whites, despite higher prevalence of type 2 diabetes, a well-known dementia risk factor. Determinants of dementia, including type 2 diabetes, have rarely been studied in Asian Americans. We followed 4,846 Chinese, 4,129 Filipino, 2,784 Japanese, 820 South Asian, and 123,360 non-Latino White members of a California-based integrated healthcare delivery system from 2002-2020. We estimated dementia incidence rates by race/ethnicity and type 2 diabetes status, and fit Cox proportional hazards and Aalen additive hazards models for the effect of type 2 diabetes (assessed 5 years before baseline) on age of dementia diagnosis controlling for sex/gender, educational attainment, nativity, height, race/ethnicity, and a race/ethnicity*diabetes interaction. Type 2 diabetes was associated with higher dementia incidence in Whites (hazard ratio [HR] 1.46, 95% confidence interval [CI] 1.40-1.52). Compared with Whites, the estimated effect of diabetes was larger in South Asians (2.26 [1.48-3.44]), slightly smaller in Chinese (1.32 [1.08-1.62]) and Filipino (1.31 [1.08-1.60]), and similar in Japanese (1.44 [1.15-1.81]) individuals. Heterogeneity in this association across Asian subgroups may be related to type 2 diabetes severity. Understanding this heterogeneity may inform prevention strategies to prevent dementia for all racial and ethnic groups.

Estimating dementia incidence in insured older Asian Americans and Pacific Islanders in California: an application of inverse odds of selection weights.

Literature shows heterogeneous age-standardized dementia incidence rates across US Asian American, Native Hawaiian, and Pacific Islanders (AANHPI), but no estimates of population-representative dementia incidence exist due to lack of AANHPI longitudinal probability samples. We compared harmonized characteristics between AANHPI Kaiser Permanente Northern California members (KPNC cohort) and the target population of AANHPI 60+ with private or Medicare insurance using the California Health Interview Survey. We used stabilized inverse odds of selection weights (sIOSW) to estimate ethnicity-specific crude and age-standardized dementia incidence rates and cumulative risk by age 90 in the target population. Differences between the KPNC cohort and target population varied by ethnicity. sIOSW eliminated most differences in larger ethnic groups; some differences remained in smaller groups. Estimated crude dementia incidence rates using sIOSW (versus unweighted) were similar in Chinese, Filipinos, Pacific Islanders and Vietnamese, and higher in Japanese, Koreans, and South Asians. Unweighted and weighted age-standardized incidence rates differed for South Asians. Unweighted and weighted cumulative risk were similar for all groups. We estimated the first population-representative dementia incidence rates and cumulative risk in AANHPI ethnic groups. We encountered some estimation problems and weighted estimates were imprecise, highlighting challenges using weighting to extend inferences to target populations.

Neighborhood disadvantage and dementia incidence in a cohort of Asian American and non-Latino White older adults in Northern California.

INTRODUCTION: Some evidence suggests that neighborhood socioeconomic disadvantage is associated with dementia-related outcomes. However, prior research is predominantly among non-Latino Whites. METHODS: We evaluated the association between neighborhood disadvantage (Area Deprivation Index [ADI]) and dementia incidence in Asian American (n = 18,103) and non-Latino White (n = 149,385) members of a Northern California integrated health care delivery system aged 60 to 89 at baseline. Race/ethnicity-specific Cox proportional hazards models adjusted for individual-level age, sex, socioeconomic measures, and block group population density estimated hazard ratios (HRs) for dementia. RESULTS: Among non-Latino Whites, ADI was associated with dementia incidence (most vs. least disadvantaged ADI quintile HR = 1.09, 95% confidence interval [CI] = 1.02-1.15). Among Asian Americans, associations were close to null (e.g., most vs. least disadvantaged ADI quintile HR = 1.01, 95% CI = 0.85-1.21). DISCUSSION: ADI was associated with dementia incidence among non-Latino Whites but not Asian Americans. Understanding the potentially different mechanisms driving dementia incidence in these groups could inform dementia prevention efforts.

Estimating Vaccine Effectiveness by Linking Population-Based Health Registries: Some Sources of Bias.

The coronavirus disease 2019 (COVID-19) pandemic has underscored the importance of observational studies of real-world vaccine effectiveness (VE) to help answer urgent public health questions. One approach to rapidly answering questions about real-world VE relies on linking data from a population-based registry of vaccinations with a population-based registry of health outcomes. Here we consider some potential sources of bias in linked registry studies, including incomplete reporting to the registries, errors in linking individuals between registries, and errors in the assumed population size of the catchment area of the registries. We show that the direction of the bias resulting from one source of error by itself is predictable. However, if multiple sources of error are present, the direction of the bias can be either upward or downward. The biases can be so strong as to make harmful vaccines appear effective. We provide explicit formulas with which to quantify and adjust for multiple biases in estimates of VE which could be used in sensitivity analyses. While this work was motivated by COVID-19 vaccine questions, the results are generally applicable to studies that link population-based exposure registries with population-based case registries to estimate relative risks of exposures.

Regression with interval-censored covariates: Application to cross-sectional incidence estimation.

A method for generalized linear regression with interval-censored covariates is described, extending previous approaches. A scenario is considered in which an interval-censored covariate of interest is defined as a function of other variables. Instead of directly modeling the distribution of the interval-censored covariate of interest, the distributions of the variables which determine that covariate are modeled, and the distribution of the covariate of interest is inferred indirectly. This approach leads to an estimation procedure using the Expectation-Maximization (EM) algorithm. The performance of this approach is compared to two alternative approaches, one in which the censoring interval midpoints are used as estimates of the censored covariate values, and another in which the censored values are multiply imputed using uniform distributions over the censoring intervals. A simulation framework is constructed to assess these methods' accuracies across a range of scenarios. The proposed approach is found to have less bias than midpoint analysis and uniform imputation, at the cost of small increases in standard error.

Evaluation of multi-assay algorithms for cross-sectional HIV incidence estimation in settings with universal antiretroviral treatment.

BACKGROUND: Multi-assay algorithms (MAAs) are used to estimate population-level HIV incidence and identify individuals with recent infection. Many MAAs use low viral load (VL) as a biomarker for long-term infection. This could impact incidence estimates in settings with high rates of early HIV treatment initiation. We evaluated the performance of two MAAs that do not include VL. METHODS: Samples were collected from 219 seroconverters (infected < 1 year) and 4376 non-seroconverters (infected > 1 year) in the HPTN 071 (PopART) trial; 28.8% of seroconverter samples and 73.2% of non-seroconverter samples had VLs ≤ 400 copies/mL. Samples were tested with the Limiting Antigen Avidity assay (LAg) and JHU BioRad-Avidity assays. Antibody reactivity to two HIV peptides was measured using the MSD U-PLEX assay. Two MAAs were evaluated that do not include VL: a MAA that includes the LAg-Avidity assay and BioRad-Avidity assay (LAg + BR) and a MAA that includes the LAg-Avidity assay and two peptide biomarkers (LAg + PepPair). Performance of these MAAs was compared to a widely used MAA that includes LAg and VL (LAg + VL). RESULTS: The incidence estimate for LAg + VL (1.29%, 95% CI: 0.97-1.62) was close to the observed longitudinal incidence (1.34% 95% CI: 1.17-1.53). The incidence estimates for the other two MAAs were higher (LAg + BR: 2.56%, 95% CI 2.01-3.11; LAg + PepPair: 2.84%, 95% CI: 1.36-4.32). LAg + BR and LAg + PepPair also misclassified more individuals infected > 2 years as recently infected than LAg + VL (1.2% [42/3483 and 1.5% [51/3483], respectively, vs. 0.2% [6/3483]). LAg + BR classified more seroconverters as recently infected than LAg + VL or LAg + PepPair (80 vs. 58 and 50, respectively) and identified ~ 25% of virally suppressed seroconverters as recently infected. CONCLUSIONS: The LAg + VL MAA produced a cross-sectional incidence estimate that was closer to the longitudinal estimate than two MAAs that did not include VL. The LAg + BR MAA classified the greatest number of individual seroconverters as recently infected but had a higher false recent rate.

The role of nativity in heterogeneous dementia incidence in a large cohort of three Asian American groups and white older adults in California.

INTRODUCTION: Literature shows lower dementia incidence in Asian American groups versus whites, varying by Asian ethnicity. One hypothesized driver is nativity differences (eg, healthy immigrant effect). METHODS: We followed a cohort of 6243 Chinese, 4879 Filipino, 3256 Japanese, and 141,158 white Kaiser Permanente Northern California members for incident dementia (2002 to 2020), estimating age-adjusted dementia incidence rates by ethnicity and nativity, and hazard ratios (HR) for nativity on dementia incidence using ethnicity-stratified age- and sex-adjusted Cox proportional hazards models. RESULTS: Dementia incidence appeared higher in foreign- versus US-born Filipinos (HR, 95% confidence interval: 1.39, 1.02 to 1.89); differences were small in Japanese (1.07, 0.88 to 1.30) and Chinese (1.07, 0.92 to 1.24). No nativity differences were observed among whites (1.00, 0.95 to 1.04). DISCUSSION: Nativity does not explain lower dementia incidence in Asian Americans versus whites, but may contribute to heterogeneity across Asian ethnicities. Future research should explore differential impacts of social and cardiometabolic factors.

Fusion designs and estimators for treatment effects.

While randomized trials remain the best evidence for treatment effectiveness, lack of generalizability often remains an important concern. Additionally, when new treatments are compared against existing standards of care, the potentially small benefit of the new treatment may be difficult to detect in a trial without extremely large sample sizes and long follow-up times. Recent advances in "data fusion" provide a framework to combine results across studies that are applicable to a given population of interest and allow treatment comparisons that may not be feasible with traditional study designs. We propose a data fusion-based estimator that can be used to combine information from two studies: (1) a study comparing a new treatment to the standard of care in the local population of interest, and (2) a study comparing the standard of care to placebo in a separate, distal population. We provide conditions under which the parameter of interest can be identified from the two studies described and explore properties of the estimator through simulation. Finally, we apply the estimator to estimate the effect of triple- vs monotherapy for the treatment of HIV using data from two randomized trials. The proposed estimator can account for underlying population structures that induce differences in case mix, adherence, and outcome prevalence between the local and distal populations, and the estimator can also account for potentially informative loss to follow-up. Approaches like those detailed here are increasingly important to speed the approval and adoption of effective new therapies by leveraging multiple sources of information.

Associations of social capital resources and experiences of homophobia with HIV transmission risk behavior and HIV care continuum among men who have sex with men in Los Angeles.

For men who have sex with men (MSM) in the US, the positive and negative aspects of social capital - access to resources within their social networks and experiences of homophobia - may explain their disproportionate burden of HIV infection. We analyzed data from 379 HIV seronegative and seropositive MSM in Los Angeles, collected between May 2017 and February 2018. Dependent variables were HIV transmission risk behaviors and care continuum outcomes. We used multivariable logistic regression to estimate the association between social capital resources and experiences of homophobia with dependent variables, adjusting for sociodemographics and drug use. Most participants were under age 40 and 41% identified as Black/African American and 36% as Hispanic/Latino. Social capital resources associated with likelihood of new sexually transmitted infections (-5.5% per standard deviation (SD), 95%CI -10.3, 0.7%) and HIV testing (5% per SD, 95%CI 0.8, 9.2%). Experiences of homophobia associated with likelihood of methamphetamine use during sex (10% per SD, 95%CI 7, 14%), receiving (4.3% per SD, 95%CI 1.9, 6.7%) and giving (7.2% per SD, 95%CI 4.5, 9.9%) exchange sex, and missing appointments (7.2% per SD, 95%CI 0.8, 13.6%). Findings that social capital associated with HIV transmission risk behaviors and HIV testing suggest interventions to increase social capital resources would impact the HIV-prevention continuum.

Attributable risk of Alzheimer's dementia attributed to age-related neuropathologies.

OBJECTIVE: The degree to which Alzheimer's versus other neuropathologies contribute to the risk of Alzheimer's dementia is unknown. We examined the risk of Alzheimer's dementia attributable to pathologic AD and 8 other neuropathologies. METHODS: Participants (n = 1,161) came from 2 clinical-pathological studies of aging. Multivariable logistic regression models examined associations of 8 neuropathological indices with Alzheimer's dementia and quantified the percentage of cases attributable to each. Furthermore, because some dementia cases are not driven by common neuropathologies, we re-estimated the attributable risks after empirically adjusting for such cases. RESULTS: Of 1,161 persons, 512 (44.1%) had Alzheimer's dementia at time of death. With the exception of microinfarcts, all neuropathological indices were independently associated with greater odds of Alzheimer's dementia. Two hundred ten (41.0%) Alzheimer's dementia cases were attributable to pathological AD. Separately, 8.9% were attributable to macroscopic infarcts, 10.8% to Lewy bodies, 5.2% to hippocampal sclerosis, 11.7% to transactive response DNA-binding protein 43, 8.1% to cerebral amyloid angiopathy, 6.0% to atherosclerosis, and 5.2% to arteriolosclerosis. A total of 83.3% of cases were attributable to all 8 indices combined. However, after further adjustment for cases driven by other factors, a total of 67.5% of cases were attributable to all 8 neuropathologic indices combined. INTERPRETATION: Pathological AD accounts for a considerable percentage of Alzheimer's dementia cases, but multiple other neuropathologies also contribute. In total, just over two-thirds of Alzheimer's dementia cases are attributable to common age-related neuropathologies, suggesting that other disease and resilience factors are important. ANN NEUROL 2019;85:114-124.

Excess Patient Visits for Cough and Pulmonary Disease at a Large US Health System in the Months Prior to the COVID-19 Pandemic: Time-Series Analysis.

BACKGROUND: Accurately assessing the regional activity of diseases such as COVID-19 is important in guiding public health interventions. Leveraging electronic health records (EHRs) to monitor outpatient clinical encounters may lead to the identification of emerging outbreaks. OBJECTIVE: The aim of this study is to investigate whether excess visits where the word "cough" was present in the EHR reason for visit, and hospitalizations with acute respiratory failure were more frequent from December 2019 to February 2020 compared with the preceding 5 years. METHODS: A retrospective observational cohort was identified from a large US health system with 3 hospitals, over 180 clinics, and 2.5 million patient encounters annually. Data from patient encounters from July 1, 2014, to February 29, 2020, were included. Seasonal autoregressive integrated moving average (SARIMA) time-series models were used to evaluate if the observed winter 2019/2020 rates were higher than the forecast 95% prediction intervals. The estimated excess number of visits and hospitalizations in winter 2019/2020 were calculated compared to previous seasons. RESULTS: The percentage of patients presenting with an EHR reason for visit containing the word "cough" to clinics exceeded the 95% prediction interval the week of December 22, 2019, and was consistently above the 95% prediction interval all 10 weeks through the end of February 2020. Similar trends were noted for emergency department visits and hospitalizations starting December 22, 2019, where observed data exceeded the 95% prediction interval in 6 and 7 of the 10 weeks, respectively. The estimated excess over the 3-month 2019/2020 winter season, obtained by either subtracting the maximum or subtracting the average of the five previous seasons from the current season, was 1.6 or 2.0 excess visits for cough per 1000 outpatient visits, 11.0 or 19.2 excess visits for cough per 1000 emergency department visits, and 21.4 or 39.1 excess visits per 1000 hospitalizations with acute respiratory failure, respectively. The total numbers of excess cases above the 95% predicted forecast interval were 168 cases in the outpatient clinics, 56 cases for the emergency department, and 18 hospitalized with acute respiratory failure. CONCLUSIONS: A significantly higher number of patients with respiratory complaints and diseases starting in late December 2019 and continuing through February 2020 suggests community spread of SARS-CoV-2 prior to established clinical awareness and testing capabilities. This provides a case example of how health system analytics combined with EHR data can provide powerful and agile tools for identifying when future trends in patient populations are outside of the expected ranges.

Nationwide Cohort Study of Antiretroviral Therapy Timing: Treatment Dropout and Virological Failure in China, 2011-2015.

Background: People living with human immunodeficiency virus (PLWH) are still being diagnosed late, rendering the benefits of "early" antiretroviral therapy (ART) unattainable. Therefore, we aimed to evaluate the benefits of "immediate" ART. Methods: A nationwide cohort of PLWH in China who initiated ART January 1, 2011, to December 31, 2014 and had baseline CD4 results >200 cells/µL were censored at 12 months, dropout, or death, whichever came first. Treatment dropout and virological failure (viral load ≥400 copies/mL) were measured. Determinants were assessed by Cox and log-binomial regression. Results: The cohort included 123605 PLWH. The ≤30 days group had a significantly lower treatment dropout rate of 6.72%, compared to 8.91% for the 91-365 days group and to 12.64% for the >365 days group. The ≤30 days group also had a significantly lower virological failure rate of 5.45% (31-90 days: 7.39%; 91-365 days: 9.64%; >365 days: 12.67%). Greater risk of dropout (91-365 days: adjusted hazard ratio [aHR] = 1.33, 95% confidence interval [CI] = 1.25-1.42; >365 days: aHR = 1.55, CI = 1.47-1.54), and virological failure (31-90 days: adjusted risk ratio [aRR] = 1.35, CI = 1.26-1.45; 91-365 days: aRR = 1.66, CI = 1.55-1.78; >365 days: aRR = 1.85, CI = 1.74-1.97) were observed for those who delayed treatment. Conclusions: ART within 30 days of HIV diagnosis was associated with significantly reduced risk of treatment failure, highlighting the need to implement test-and-immediately-treat policies.

Multistate models and lifetime risk estimation: Application to Alzheimer's disease.

The lifetime risk of a clinical condition is the probability of onset of the condition during one's lifespan. Recent advances in Alzheimer's disease (AD) research have identified screening tests for biomarkers that can identify persons who are in the earliest stages of the AD process but who do not yet have any clinical signs or symptoms. A critical question asked by patients and clinicians is, what is the probability an individual will develop AD dementia during his or her lifetime? Here, we discuss estimation of lifetime risks using biomarkers for preclinical disease based on a discrete nonhomogeneous Markov multistate model for the disease process. We allow the transition probabilities to depend on chronological age. In addition, we allow the probabilities to depend on calendar time to account for possible calendar trends in death rates and to evaluate the impact on lifetime risks of future interventions designed to slow disease progression. We develop estimating equations for calculating the lifetime risks from the nonhomogeneous multistate Markov model. Estimates of lifetime risks for AD dementia based on biomarkers for preclinical disease are presented.

Cross-sectional HIV incidence estimation in an evolving epidemic.

The cross-sectional approach to HIV incidence estimation overcomes some of the challenges with longitudinal cohort studies and has been successfully applied in many settings around the world. However, the cross-sectional approach does rely on an initial training data set to develop and calibrate the statistical methods to be used in cross-sectional surveys. The problem addressed in this paper is that the initial training data set may, over time, not reflect the current target population of interest because of evolution of the epidemic. For example, the mismatch between the target population and the initial data set could occur because of increasing use of anti-retroviral therapy among HIV-infected persons throughout the world. We developed methods to adjust the initial training data set with the goal that the adjusted data sets better reflect the target population. These adjustment procedures could help avoid the time and expense of collecting a completely new training data set from the current target population. We report the results of a simulation study to evaluate the procedures. We applied the methods to a dataset of HIV subtype B infection. The adjustment procedures could be applicable in situations other than cross-sectional incidence estimation where complex statistical analyses are to be conducted using an initial data set but those results may not be directly transportable to a new target population of interest. The approach we have proposed could offer a practical and cost-effective way to apply cross-sectional incidence methods to new target populations as the epidemic evolves.

Design and sample size considerations for Alzheimer's disease prevention trials using multistate models.

BACKGROUND/AIMS: Clinical trials for Alzheimer's disease have been aimed primarily at persons who have cognitive symptoms at enrollment. However, researchers are now recognizing that the pathophysiological process of Alzheimer's disease begins years, if not decades, prior to the onset of clinical symptoms. Successful intervention may require intervening early in the disease process. Critical issues arise in designing clinical trials for primary and secondary prevention of Alzheimer's disease including determination of sample sizes and follow-up duration. We address a number of these issues through application of a unifying multistate model for the preclinical course of Alzheimer's disease. A multistate model allows us to specify at which points during the long disease process the intervention exerts its effects. METHODS: We used a nonhomogeneous Markov multistate model for the progression of Alzheimer's disease through preclinical disease states defined by biomarkers, mild cognitive impairment and Alzheimer's disease dementia. We used transition probabilities based on several published cohort studies. Sample size methods were developed that account for factors including the initial preclinical disease state of trial participants, the primary endpoint, age-dependent transition and mortality rates and specifications of which transition rates are the targets of the intervention. RESULTS: We find that Alzheimer's disease prevention trials with a clinical primary endpoint of mild cognitive impairment or Alzheimer's disease dementia will require sample sizes of the order many thousands of individuals with at least 5 years of follow-up, which is larger than most Alzheimer's disease therapeutic trials conducted to date. The reasons for the large trial sizes include the long and variable preclinical period that spans decades, high rates of attrition among elderly populations due to mortality and losses to follow-up and potential selection effects, whereby healthier subjects enroll in prevention trials. A web application is available to perform sample size calculations using the methods reported here. CONCLUSION: Sample sizes based on multistate models can account for the points in the disease process when interventions exert their effects and may lead to more accurate sample size determinations. We will need innovative strategies to help design Alzheimer's disease prevention trials with feasible sample size requirements and durations of follow-up.

Immediate Antiretroviral Therapy Decreases Mortality Among Patients With High CD4 Counts in China: A Nationwide, Retrospective Cohort Study.

Background: Clinical trials have demonstrated that immediate initiation of antiretroviral therapy (ART) reduces AIDS-related morbidity and mortality. We tested the hypothesis that initiating ART ≤30 days after human immunodeficiency virus (HIV) diagnosis would be associated with reduced mortality among people living with HIV (PLWH) with CD4 counts >500 cells/µL. Methods: PLWH enrolled in the Chinese National HIV Information System between January 2012 and June 2014 with CD4 counts >500 cells/µL were followed for 12 months. Cox proportional hazards model was used to determine hazard ratios (HRs) for PLWH who initiated ART after HIV diagnosis. ART initiation was treated as a time-dependent variable. Results: We enrolled 34581 PLWH with CD4 >500 cells/µL; 1838 (5.3%) initiated ART ≤30 days after diagnosis (immediate ART group), and 19 deaths were observed with a mortality rate of 1.04 per 100 person-years (PY). Fifty-eight deaths were documented among the 5640 PLWH in the delayed ART group with a mortality rate of 2.25 per 100 PY. There were 713 deaths among the 27103 PLWH in the no ART group with a mortality rate of 2.39 per 100 PY. After controlling for potential confounding factors, ART initiation at ≤30 days (adjusted HR, 0.37 [95% confidence interval, .23-.58]) was a statistically significant protective factor. Conclusions: We found that immediate ART is associated with a 63% reduction in overall mortality among PLWH with CD4 counts >500 cells/µL in China, supporting the recommendation to initiate ART immediately following HIV diagnosis.

Psychiatric Illness, Substance Use, and Viral Suppression Among HIV-Positive Men of Color Who Have Sex with Men in Los Angeles.

For individuals living with human immunodeficiency virus (HIV), viral suppression positively affects quality and length of life and reduces risks for HIV transmission. Men of color who have sex with men (MoCSM) who have been diagnosed with HIV have disproportionately low rates of viral suppression, with concomitant increases in incidence. We identified specific social, structural, and psychiatric factors associated with viral suppression among a sample of 155 HIV-positive MoCSM. Cigarette smoking and biological markers of recent drug use were significantly associated with detectable viral load. In contrast, individuals reporting a history of psychiatric illness during medical examination were more likely to be virally suppressed. Further analyses demonstrated that psychiatric illness may affect virologic outcomes through increased probability of being prescribed HIV medications. Alternatively, cigarette smoking and drug use appear to negatively affect subsequent HIV Care Continuum milestones such as medication adherence. Findings provide support for comprehensive intervention programs that emphasize prevention and treatment of cigarette, methamphetamine, and other drug use, and promote improved connection to psychiatric care. Continual achievement of this goal may be a crucial step to increase rates of viral suppression and slow HIV incidence in communities of MoCSM in Los Angeles and other urban areas.

Estimation of lifetime risks of Alzheimer's disease dementia using biomarkers for preclinical disease.

INTRODUCTION: Lifetime risks are the probabilities of progressing to Alzheimer's disease (AD) dementia during one's lifespan. Here, we report the first estimates of the lifetime and ten-year risks of AD dementia based on age, gender, and biomarker tests for preclinical disease. METHODS: We used a multistate model for the disease process together with US death rates. RESULTS: Lifetime risks of AD dementia vary considerably by age, gender, and the preclinical or clinical disease state of the individual. For example, the lifetime risks for a female with only amyloidosis are 8.4% for a 90-year old and 29.3% for a 65-year old. Persons younger than 85 years with mild cognitive impairment, amyloidosis, and neurodegeneration have lifetime risks of AD dementia greater than 50%. DISCUSSION: Most persons with preclinical AD will not develop AD dementia during their lifetimes. Lifetime risks help interpret the clinical significance of biomarker screening tests for AD.