Citations

Abstract BACKGROUND Some persons with late‐stage Alzheimer's disease and related dementias (ADRD) and seemingly very minimal cognitive abilities have transient episodes of unexpected, spontaneous, meaningful, and relevant communication or behavior. This phenomenon, referred to as lucidity, is not well understood, although it is frequently observed by family caregivers. METHODS An exploratory study using 24 qualitative interviews and 140 open‐ended response data documented family caregiver perspectives and experiences with lucid episodes during late‐stage ADRD. RESULTS Caregivers detailed their experiences witnessing a lucid episode and the resulting impacts. Caregivers revealed reasons they felt positive or upset about the lucid episode, discussed changes the lucid episode prompted, and shared the range of emotions they experienced. IMPLICATIONS Lucid episodes have a significant, enduring, and not always positive impact on caregivers. To better navigate and face sequelae associated with lucid episodes, caregivers should receive psychoeducation or consultation to help increase their understanding, set expectations, and cope with changes. Highlights Little is known about lucid episodes in late‐stage dementia and even less is known about how dementia family caregivers react to and are impacted by these episodes. Qualitative interviews can garner rich data on dementia family caregiving experiences with understudied phenomena such as lucidity. Lucid episodes have a varying but marked and long‐lasting impact on dementia family caregivers. The dementia care field must explore strategies for enhancing education and support to caregivers to build awareness and shape expectations of lucid episodes, a complex experience.

ABSTRACT Background Critically ill patients may be overexposed to valproate because altered protein binding leads to a disproportionate free valproate fraction. The Fraser equation was derived and internally validated to estimate critically ill patients' free valproate concentrations, but it requires external validation. Methods Adult intensive care unit (ICU) patients at two academic centers with concurrently measured free and total valproate concentrations were included. Free valproate concentrations were estimated using the Fraser equation which includes total valproate, albumin and BUN concentration, and whether the patient received propofol or aspirin. The primary outcome was Fraser equation performance, assessed using Bland–Altman methods. Comparative performance against estimates from the Doré equation (an alternative predictive equation), therapeutic concordance using a target free valproate range of 5–15 mg/L, and equation improvements were explored. Results Overall, 315 patients and 556 free‐total valproate concentration pairs were included. The mean (±SD) age was 58 (±17) years and 90 (29%) patients were on valproate prior to hospital admission. The Fraser equation estimated free valproate concentrations were correlated with measured concentrations ( r = 0.728) with a negative bias (mean bias −2.77 mg/L, 95% LOA –18.9, 13.4). The Fraser equation increasingly underestimated measured concentrations as measured concentrations increased. 71% of Fraser equation estimates were therapeutically concordant (e.g., estimate and measured both within reference range) compared to 61.9% of Doré estimates ( p = 0.001). Fraser equation modifications led to minor performance improvements but did not overcome worsening underestimation with higher measured free valproate concentrations. Conclusion The Fraser equation was moderately accurate and corresponded with an appropriate interpretation for 71% of free valproate concentrations. Worse underestimation with higher measured free valproate concentrations suggests direct measurement of free valproate concentrations is warranted. While the Fraser equation could complement therapeutic decision making at centers where direct free valproate measurements are unavailable or slow to return, its accuracy is currently insufficient to replace direct measurement.

Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.

Importance The introduction of immune checkpoint inhibitor (ICI) therapy has improved cancer outcomes but at the cost of adverse events, mainly related to the immune system. Cardiovascular (CV) toxic effects, and especially myocarditis, are of particular concern and are the subject of this position statement by the International Cardio-Oncology Society with representation of experts from oncology, hematology, and cardiology. Observations CV toxic effects of ICI therapies include inflammation-associated diseases, such as myocarditis, pericarditis, and vasculitis, as well as the aggravation of chronic inflammatory conditions, such as atherosclerosis with acute ischemic complications (myocardial infarction and stroke). Patients taking ICI therapies can also develop cardiac dysfunction, stress-induced cardiomyopathy (Takotsubo or apical ballooning syndrome), and heart failure without inflammatory cell infiltration of the myocardium. Atrial and ventricular arrhythmias can emerge in the setting of a systemic inflammatory milieu, myocarditis, or ischemia. Of all potential CV adverse effects, myocarditis remains of highest concern, although fatality rates have declined over time with a broadening spectrum of presentations ranging from troponin elevation of uncertain significance to smoldering, nonsevere, and severe or fulminant myocarditis. Conclusions and Relevance Concerns for myocarditis continue to dominate the spectrum of CV toxic effects in patients receiving ICI therapy. Recommendations for management vary according to severity. Multidisciplinary collaborations remain key for managing acute toxic effects and future cancer treatment decisions, including ICI rechallenge. Ischemic heart disease constitutes the main differential diagnosis in these patients, while pericarditis can be concomitantly present, and atrial and ventricular arrhythmias can also complicate the clinical picture. Several gaps in knowledge are identified and require further research.

Abstract Objective To evaluate 2-year cost to insured patients treated with Roux-en-Y gastric bypass (RYGB) or glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for type 2 diabetes (T2D) and obesity. Methods Using the 2017 to 2023 Merative™ claims database, we identified adult patients with severe obesity and T2D who were treated with a RYGB or GLP-1 RAs. Patients with RYGB had no treatment with GLP-1 RAs, and those who received GLP-1 RA therapy with tirzepatide or semaglutide for ≥ 2 years had no metabolic and bariatric surgery (MBS) procedures. The study cohorts were matched on demographics including obesity, associated medical problems, and baseline direct or out-of-pocket (OOP) costs to patients in the year prior to treatment initiation. Direct costs included those from outpatient services, inpatient admissions, and outpatient prescription filled that were paid directly by patients. We compared this cost up to two years after treatment initiation using paired t-tests. Results 1012 matched RYGB and GLP-1 RA patients were analyzed, including 35% male. At 1-year after treatment initiation, healthcare costs paid directly by patients were similar for the RYGB ($2,301) and GLP-1 RA ($2,179) (delta = $122, p = 0.15) cohorts. From one to two years after index treatment date, OOP costs were significantly lower in the RYGB treatment group ($1,277 vs. $2,104, p < 0.01). Two years after treatment initiation, RYGB patients spent $704 less in OOP costs than similar patients treated with GLP-1 RA medications (p < 0.01). Conclusions Direct OOP healthcare costs were lower for RYGB compared to GLP-1 RA use patients 2-years after treatment initiation.

Abstract Peanut allergy is a leading cause of food-induced allergy (prevalence of ∼1%). The diagnosis relies on evaluating clinical symptoms consistent with peanut exposure, supported by the detection of total peanut specific IgE (sIgE) and peanut component IgE antibodies (Ara h1, Ara h2, Ara h3, Ara h6, Ara h8, Ara h9 and Bet v2) through serum or skin testing. However, sensitization patterns across different ages and regions in the United States remain largely unknown. In this study, we investigated regional and demographic patterns of peanut component sensitization in a large U.S. population tested for suspected peanut allergy. Retrospective data were collected from 13,702 individuals tested at Mayo Clinic Laboratories. sIgEs were measured using the ImmunoCAP system (Thermo Fisher Scientific). Samples with detectable total peanut sIgE (≥0.1 kU/L) were reflexed to testing for seven peanut component IgEs. Statistical analyses including linear regression and correlation matrix analysis were conducted using R Studio. Regional differences were assessed using care provider zip code information. Among the study population, 92.0% (12,604 of 13,702) had detectable total peanut sIgE, with the Western U.S. region exhibiting the highest detectable rate (95.6%), and the Southeast the lowest (85.6%) (p &lt; 0.001). On average, 3.38 different component IgEs were detectable per person with a detectable total peanut sIgE; 7.1% (892) had no detectable component IgEs, possibly due to antibodies against other peanut components. Correlation analysis revealed strong associations between Ara h2 and Ara h6 (r = 0.94), with moderate correlations observed between Ara h2, Ara h3, and Ara h6 to Ara h1 (r ranging from 0.72 to 0.77). Age-stratified analysis indicated higher total peanut sIgE detectable rates in children and adolescents (95.2%, ≤18 years) compared to adults (76.5%, &gt;18 years). Interestingly, adults were more likely than children to have negative results for all component IgEs. Sensitization rates to different peanut components varied, with Ara h2 (77.5%) and Ara h6 (73.2%) being the most frequently detected, followed by Ara h1 (56%), and Ara h3 (47.3%). Lower detectable rates were observed for Ara h8, Ara h9, and Bet v2 (34.8%, 26.1% and 22.7%, respectively). Regional analysis showed consistently high detectable rates for Ara h2 and Ara h6 (&gt;70%) across most areas (p &lt; 0.001) with slightly lower rates in the Southwest (&lt;63%). Bet v2, despite its overall low prevalence (&lt;24%), had a relatively higher detectable rate in the Southwest (29%). This study provides valuable insights into potential demographic and geographic factors influencing peanut allergy sensitization. Our study demonstrates that peanut sensitization patterns vary by age and geographic location. Children and adolescents exhibit higher detectable rates for total peanut sIgE and component IgEs compared to adults, with Ara h2 and Ara h6 as the most frequently detected and highly correlated components.

Abstract Glioblastoma (GBM) progression and recurrence are often driven by therapy-resistant cellular states emerging within hypoxic tumor niches. While hypoxia is a hallmark of GBM, the spatial transcriptomic heterogeneity that underpins resistance in these regions remains poorly characterized. Here, we employ pimonidazole labeling in conjunction with high-resolution spatial and single cell transcriptomics across 29 primary, treatment-naive human GBM samples, syngeneic mouse models, and patient-derived glioma-initiating cells exposed to hypoxia to define the hypoxia-specific tumor microenvironment and its associated cellular programs. We reveal spatially organized sub-niches within hypoxic regions, each supporting diverse cellular programs yet coexisting tumor lineage states with minimal transitions between cell states. Phylogenetic reconstruction based on inferred copy number variations demonstrates consistent evolutionary trajectories from non-hypoxic to hypoxic tumor loci. Specific copy number alterations were enriched in hypoxic regions and associated with immune infiltration and poor prognosis in MGMT-methylated tumors. Cross-species analyses confirmed the conservation of hypoxia-associated gene programs and spatial architectures. Together, our study delineates the cellular, evolutionary, and spatial complexity of hypoxia in GBM, identifies hypoxia-induced genomic alterations that may promote tumor fitness, and offers insights into new therapeutic vulnerabilities within hypoxic niches.

Abstract Pediatric, adolescent and young adult patients (Ped/AYA; 0–39 years) with meningiomas are underrepresented in neuro-oncology research, despite meningiomas being the second most common primary brain tumor in this age group. While DNA methylation-based models have advanced classification and prognostication in adults, their utility in younger populations remains uncertain. To address this gap, we aimed to evaluate the performance of current DNA methylation-based classification and recurrence prediction models in Ped/AYA patients with meningiomas and identify age-associated molecular differences. As part of this study, we analyzed 1,568 meningioma samples with DNA methylation and clinical data, including subsets with whole-exome and RNA sequencing. Patients were grouped into Ped/AYA (≤39 years, n = 213) and adult (&gt;39 years, n = 1,355) cohorts. We assessed classifier performance, performed subgroup-specific model retraining, and compared molecular profiles across age groups. Our results showed that molecular classification differed significantly between age groups, with Ped/AYA tumors less frequently belonging to the most aggressive Proliferative Molecular Group. The DNA methylation-based recurrence model performed well in adults (AUC = 0.83) but poorly in the Ped/AYA cohort (AUC = 0.57). However, retraining the model on only younger patients improved performance (AUC = 0.75). In addition, Ped/AYA tumors exhibited significantly fewer chromosomal alterations, including lower frequencies of 1p, 6q, and 14q loss (p&lt;0.05). Taken together, these findings indicate that predominantly adult-trained methylation models underperform in younger meningioma patients due to both biological divergence and exclusion from training datasets. Our findings underscore the need for age-specific molecular tools to improve prognostication and support personalized care across the lifespan in neuro-oncology.