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801 Background: SBA is a rare, poorly understood gastrointestinal malignancy. Adenocarcinomas are often grouped with other small bowel cancer histologies in epidemiologic and outcomes reports, which limits the ability to detect SBA-specific trends. Recent studies in European populations show increasing SBA incidence, but there are limited published data in American cohorts. Identifying trends in SBA can improve understanding of the population most at risk for developing SBA. This study describes U.S. trends in SBA incidence and outcomes from 2000 to 2019. Methods: Using the 2022 SEER research-limited dataset, we identified SBA cases and measured the incidence change from 2000-2019. We built linear regression models to evaluate changes in annual incidence by groups, including sex, race, and age of diagnosis, separately. We then compared the overall incidence and trends between subgroups. We investigated overall survival (OS) through the SEER research case listings for SBA patients diagnosed during the study period. Results: An average of 0.67 cases/100,000 SBA cases were reported annually from 2000-2019, with a median diagnosis age of 69 years. SBA incidence has increased annually by 0.3% per year from 2000-2019 (p=0.05). From 2000-2019, men were at a higher risk for SBA compared to women (p=0.02). In men, SBA cases increased at a rate of 0.004 cases/100,000/year from 2000-2019 (p=0.01) and a nonsignificant decrease in women of 0.00012 cases/100,000/year. There were no statistically significant differences in incidence or the change in incidence of SBA by race. The age-adjusted incidence was significantly higher each year between 2000 and 2019 in the > 70 cohort compared to the <70 cohort (p=0.02). Cases of SBA increased at a rate of 0.02 cases/100,000/year in adults >70 years (p=0.02). There were no differences in incidence rates in patients <70 years. There was no significant difference in OS for patients diagnosed with SBA in 2000, 2005, 2010, 2015, and 2019 (p=0.21). Conclusions: The overall annual incidence of SBA is increasing in the U.S. population. The most significant rate increases are in men and adults older than 70. In the SEER population, trends in SBA contrast with the recent rise of colorectal cancer in the young adult population, highlighting the unique nature of SBA compared to other gastrointestinal malignancies. Additionally, survival outcomes in patients diagnosed with SBA have remained stable over the past 20 years, while other malignancies have shown improvement in the same period. The small cohort size and the lack of a universal U.S. cancer registry limited this evaluation. Improved reporting of SBA cases and further research to identify risk factors are urgently needed to reduce the growing impact of SBA.

AbstractBackgroundBlood‐based biomarkers show promise as a noninvasive, inexpensive method for measuring Alzheimer’s disease pathology throughout the lifecourse. However, the predictive and classification accuracy of these biomarkers at different stages of the lifecourse and among diverse, community‐dwelling populations requires further investigation.MethodBetween 2014 and 2015, 329 dementia‐free participants from the Atherosclerosis Risk in Communities Study underwent brain magnetic resonance imaging (MRI) and florbetapir positron emission tomography (PET). Amyloid positivity was defined as a global cortex standardized uptake value ratio greater than 1.2. Stored plasma samples collected in midlife (1993‐95, mean age 58.5 years) and late‐life (2011‐13, mean age 76.2 years) from a subsample of 259 participants were assayed in 2022 using Quanterix SiMoA. The assay quantified amyloid‐β (Aβ)42/40, phosphorylated tau at threonine 181 (p‐Tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Unadjusted and covariate‐adjusted logistic regression models estimated the association between plasma biomarkers from midlife and late‐life and amyloid positivity in late‐life. Unadjusted receiver operating characteristic curves documented the classification accuracy of the plasma biomarkers separately and collectively.ResultThe sample (Table 1) included 151 women (58.1%), 105 Black participants (40.4%), and 136 (52.3%) participants with amyloid positivity. In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, assays measured in midlife were not associated with amyloid positivity in late‐life (Table 2). However, late‐life measurements of Aβ42/40, p‐Tau181, and GFAP and change per decade from midlife to late‐life in p‐Tau181 and GFAP were associated with greater odds of amyloid positivity. The greatest classification accuracy (Figure 1) was achieved by using all assays measured in midlife and late‐life (AUC = 0.754), although the accuracy when using only late‐life measures was comparable (AUC = 0.737).ConclusionLate‐life plasma biomarkers of Alzheimer's disease neuropathology and astrogliosis were associated with late‐life amyloid positivity, but midlife plasma biomarkers obtained 16 to 20 years earlier did not exhibit a statistically significant association. Additional longitudinal research is needed to determine whether changes in plasma biomarkers measured before an individual is classified as amyloid positive can be used to identify individuals at risk of developing Alzheimer's disease.

AbstractBackgroundOlder adults with dual cognitive and mobility impairments have higher financial costs and poorer quality of life than adults with either impairment alone. Blood biomarkers of Alzheimer Disease (AD) pathology (Aβ42, Aβ40 and p‐tau181) and neurodegeneration (neurofilament light (NFL) and glial fibrillary acidic protein (GFAP)) may identify individuals at risk for both mobility and cognitive impairment and provide novel insights into mechanistic underpinnings.MethodBlood biomarkers (SiMoA Quanterix N4PE, p‐tau181 single‐plex) were available in a subsample of 1751 ARIC study participants at Visit 5 (V5, 2011‐13, mean age 76.2 years (5.3), 41% men, 28% Black); Aβ42 was reversed and adjusted for Aβ40 (‐Aβ42|40) for consistent directions of associations (higher=worse). Usual gait speed and cognitive status were assessed over 8 years at V5, V6 (2016‐17), and V7 (2017‐18). Participants were categorized by V5 impairment: mobility‐only (gait speed <0.8m/s, n=430), cognitive‐only (expert‐adjudicated dementia, n=38), dual (n=54), or neither (referent, n=1229). Multinomial regression models examined relative risk ratios (RRR) of V5 log‐transformed biomarkers with prevalent impairments and, among those with neither impairment at V5, incident impairments through V7. All models adjusted for V5 age, sex, self‐reported race (Black or White), renal function, and body mass index.ResultHigher levels of all biomarkers were associated with greater risk of prevalent impairment in mobility, cognitive, or dual domains (Figure A). Over 8‐years of follow‐up, incident impairments included 471 participants with only mobility impairments, 39 with only cognitive impairments, 55 with dual impairments, and 168 died without developing any impairment. All biomarkers were associated with incident dual impairment per IQR higher biomarker: p‐tau181 (RRR=2.54; 95% CI: 1.45, 4.44), ‐Aβ42|40 (RRR=1.66; 1.31, 2.09), NfL (RRR=2.69; 1.22, 5.91) and GFAP (RRR=2.13; 1.07, 4.25). P‐tau181, ‐Aβ42|40, and GFAP were also associated with incident cognitive‐only impairment, while P‐tau181, NFL and GFAP were associated with incident mobility‐only impairment. (Figure B).ConclusionBlood biomarkers of brain health may be useful tools for earlier identification of those at risk for cognitive, mobility, or dual declines, facilitating earlier targeted interventions. Potential differences in AD‐pathology versus neurodegeneration blood biomarker relationships with outcomes of mobility and cognition may help to identify more targeted interventions for both.

Importance Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure Plasma biomarkers of amyloid-β 42 to amyloid-β 40 (Aβ42:Aβ40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aβ42:Aβ40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 ( APOE ε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aβ42:Aβ40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers’ association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.

Abstract Objectives Urine drug testing (UDT) is a critical tool used in medical, forensic, and occupational settings, but interpreting results can be challenging. We performed a study to assess the ability of health care professionals to interpret UDT results accurately. Methods In total, 911 clinical and laboratory professionals in the United States and Canada responded to a survey with questions gauging expertise in UDT interpretation. Responses were analyzed to identify knowledge gaps. Results Toxicologists and laboratory PhD scientists performed well, with means of 4.82 and 4.63 questions answered correctly (out of 6 possible), respectively. Physicians specializing in pathology, emergency medicine, primary care, and internal medicine, however, displayed concerning knowledge gaps, as did laboratorians with nondoctoral degrees. Experience and training correlated with interpretation accuracy. Identification of simulated compliance as well as understanding opioid exposure, metabolism, and immunoassay cross-reactivity were among the most clinically significant knowledge gaps. More than 30% of survey respondents indicated that they would seek UDT information from the internet or peers rather than clinical or laboratory experts. Conclusions The study highlighted the need for targeted education and better collaboration between clinical and laboratory experts and other health care professionals to ensure that when physicians order UDT, they can accurately interpret results and reduce harm.

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P &amp;lt; .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.