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PURPOSE There is growing scientific interest in incorporating patient-reported outcomes (PROs) in early phase dose-finding oncology trials (DFOTs) to assess tolerability, inform dose selection, and guide later stage trial design. However, research indicates that PRO objectives in DFOTs are often unclear. The Incorporating Patient-Reported Outcomes in Dose-Finding Trials-Research Objectives Recommendations (OPTIMISE-ROR) project was established to support trialists to effectively incorporate PROs into DFOTs. METHODS Using the Enhancing Quality and Transparency of Health Research (EQUATOR) Network's methodological framework, guideline development included the following: (1) a methodological review of published DFOTs incorporating PROs; (2) candidate item generation, refined through expert consultation; (3) a two-round international multistakeholder Delphi survey (N = 109 in Round 1 [October 2024]; N = 96 in Round 2 [December 2024]); and (4) an independently chaired virtual consensus meeting (N = 31; January 2025) where multidisciplinary, international experts reviewed and voted to finalize items for inclusion. RESULTS Consensus was reached on six recommendations emphasizing three core PRO tolerability concepts: overall side effect impact, symptomatic adverse events, and overall health-related quality of life. The integration of PROs to inform final dose recommendations in dose escalation and optimization trials should be considered, regardless of trial design. The recommendations highlight the importance of PRO data analysis over time and across dose levels, defining PRO research objectives as descriptive or statistically powered, and assessing PRO-related end points to guide end point selection for subsequent studies. CONCLUSION This foundational guidance outlines key PRO research objectives in DFOTs. By facilitating the systematic integration of PROs, this guidance supports the utilization of patient-centered evidence for the tolerability and efficacy assessment of therapies to inform dose escalation, optimization, and regulatory evaluation—ultimately contributing to the development of safer, more effective therapies.

Background In pediatric patients presenting after blunt trauma, the incidence of clinically significant cervical spine injury (CSI) is approximately 1%. Although multidetector CT (MDCT) is widely accepted for cervical spine clearance in adults, its utility in children remains uncertain. The purpose of this study is to evaluate the sensitivity of MDCT in identifying clinically significant CSI in pediatric patients, stratified by age groups: adolescents (12 years to 17 years) and children (0 years to 11 years). Methods We designed a national, multicenter, prospective observational study to assess the diagnostic performance of MDCT in detecting clinically significant CSI in pediatric trauma patients. Data are being collected from participating centers on imaging findings, clinical outcomes, and the presence of confirmed CSIs after blunt trauma. The analysis plan includes stratification by age group and calculation of sensitivity, specificity, and predictive values of MDCT for CSI. Results This abstract outlines the background, methodology, and analytical framework of the study. Data collection and analysis are ongoing. This study represents the largest known cohort of pediatric patients undergoing cervical spine imaging after blunt trauma and is the first prospective study of its kind focused exclusively on this population. Conclusions This study will provide critical data to inform guidelines for pediatric cervical spine clearance after blunt trauma. By evaluating the sensitivity of MDCT in detecting clinically significant CSI, the findings aim to support evidence-based imaging strategies and improve the safety and efficiency of pediatric trauma care.

Abstract Background Mitochondrial dysfunction in Alzheimer's Disease (AD) is characterized by impaired energy production, oxidative stress, and disrupted calcium homeostasis, which collectively contribute to neuronal damage, synaptic dysfunction, and the progression of AD pathology. A significant knowledge gap in studying mitochondrial dysfunction in Alzheimer's Disease (AD) lies in understanding the precise molecular mechanisms linking mitochondrial metabolic alterations to neuronal damage, particularly how sex‐specific and cell‐type‐specific mitochondrial processes contribute to the progression of AD pathology. Method This study integrates multiple datasets, post‐mortem brain RNAseq from ROSMAP, Mayo Clinic brain bank and Mount Sinai Brain Bank cohort data available via AD Knowledge Portal hosted by Sage Bionetworks), Human Protein Atlas (HPA), MitoCarta3, genome‐scale human metabolic reconstruction, mitochondriome analysis, and brain & blood metabolomics data (data generated by the Alzheimer's Disease Metabolomics Consortium (ADMC)) to identify mitochondrial genes associated with disrupted metabolism in AD. Additionally, biodomain analysis was used to identify key processes associated with pathology. Result A total of 62 common genes were identified across these approaches, highlighting their potential significance in mitochondrial processes. We also developed the framework to perform metabolite‐gene correlation analyses revealing key mitochondrial‐metabolic interactions (eg. homocysteine and MTHFR gene; acetyl‐CoA and PDHA1 gene). Integrated in silico metabolic analysis identified reaction fluxes, uncovering sex‐specific differences in mitochondrial transport and tricarboxylic acid (TCA) cycle subsystems, with notable alterations in females. Biodomain enrichment analysis focused on mitochondrial processes, identifying disruptions in pathways critical for energy production and redox homeostasis. Additionally, we analyzed datasets related to metformin and complex I inhibitors, linking mitochondrial complex I modulation with metabolic alterations in AD. This analysis identified druggable targets and potential therapeutic candidates for mitochondrial metabolic pathways. Conclusion Our findings integrate multiple data sources to provide a systems‐level understanding of mitochondrial metabolism in AD. Sex‐specific differences associated with mitochondrial dysfunction in AD were identified. We identify important mitochondrial transport proteins and metabolites that could potentially be used as druggable targets in AD.

Abstract Background Plasma biomarkers of Alzheimer's disease (AD) pathology and neurodegeneration provide a non‐invasive method to assess brain pathology associated with dementia and cognitive decline. However, it remains unclear whether these biomarkers are differentially associated with changes in specific cognitive domains or how they relate to subsequent cognitive change in participants with or without cognitive impairment. Methods Plasma biomarkers were assayed in a subset of ARIC participants using Quanterix SiMoA technology on stored specimens collected in midlife (visit 3: 1993‐95, mean age: 59) and late‐life (visit 5: 2011‐13, mean age: 77). Biomarkers included 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). Factor scores for global cognition and cognitive domains (memory, language, executive function) were calculated from ten neuropsychological tests administered at visits 5 (2011‐13), 6 (2016‐17), 7 (2018‐19), 8 (2020), and 9 (2021‐22). Linear mixed effects models with multiple imputation of pre‐death cognitive change estimated the association between biomarkers in midlife and late‐life, and biomarker change from midlife to late‐life, with 5‐year change in late‐life global and domain‐specific cognition, adjusting for demographics, lifestyle and cardiovascular risk factors, and APOE‐ε4 status. Exploratory analyses examined effect modification of the biomarker‐global cognition associations by visit 5 adjudicated cognitive impairment. Results Among 1515 participants with plasma biomarkers (60.7% female, 25.5% identified as Black), 39% had late‐life cognitive impairment (Table 1). Higher midlife NfL and GFAP were associated with faster 5‐year declines in global cognition and language during late‐life (Table 2). Only midlife NfL was associated with faster late‐life memory decline. No midlife biomarkers were associated with executive function. In late‐life, lower Aβ42:Aβ40 and higher p ‐Tau 181, NfL, and GFAP were associated with faster declines in global cognition, memory, and language. Midlife to late‐life changes in p ‐Tau 181, NfL, and GFAP were associated with declines in global cognition and language. No consistent effect modification by cognitive impairment was observed (Figure 1). Conclusions Plasma biomarkers of AD pathology, neuronal injury, and astrogliosis, measured at different life epochs (midlife vs. late‐life) show distinct association patterns with subsequent changes in cognitive function across domains.

Abstract Background Plasma biomarkers show promise as a noninvasive method for measuring Alzheimer's disease pathology and neurodegeneration throughout the lifecourse. However, the relationship between longitudinal changes in these biomarkers and late‐life brain morphology in community‐dwelling populations requires further investigation. Method Between 2011 and 2013, 1,977 participants from the Atherosclerosis Risk in Communities Study received an adjudicated cognitive diagnosis and underwent 3 Tesla magnetic resonance imaging scans. Whole‐brain cortical thickness was quantified by Freesurfer. Stored plasma samples collected in midlife (1993‐95, mean age 59.0 years) and late‐life (2011‐13, mean age 76.8 years) from a subsample of 1,515 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). Linear regression models estimated the association of plasma biomarkers from midlife, late‐life, and the change from midlife to late‐life with cortical thickness in late‐life. Interactions and effect modification by age were examined in exploratory analyses. Result The sample (Table 1) included 920 (60.7%) women, 387 (25.5%) Black participants, 513 (33.9%) participants with mild cognitive impairment, and 85 (5.6%) participants with dementia. The average age in late‐life was 76.8 (5.3 SD) years and the average cortical thickness was 2.27 (0.11 SD) millimeters. Cortical thickness was lower in individuals with adjudicated mild cognitive impairment or dementia compared to individuals without cognitive impairment (2.25 mm versus 2.29 mm, p <0.0001). In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, higher midlife measures of p ‐Tau181 and increases from midlife to late‐life in NfL and GFAP were associated with lower cortical thickness in late‐life (Table 2). Concurrent measures of plasma biomarkers in late‐life were associated with lower cortical thickness (Table 2) and exhibited a stronger association among participants ≥75 years compared to <75 years (Table 3). Conclusion Plasma biomarkers of Alzheimer's disease pathology and neurodegeneration obtained in midlife and late‐life were associated with late‐life differences in cortical thickness. Additional longitudinal research is needed to determine whether plasma biomarkers predict cortical thinning over time and may serve as an early indicator of accelerated brain atrophy.

Background: Institutions that participate in PCORnet ® transform their local electronic health record (EHR) data into the PCORnet ® Common Data Model (CDM), which is then used to generate data extracts for PCORnet ® Studies. PCORnet ® Studies can also include institutions that do not participate in PCORnet, and for these organizations, the cost of instantiating a PCORnet ® CDM can be prohibitive. Fast Health care Interoperability Resources (FHIR) provides an alternative method of obtaining EHR data. Objective: To determine whether data obtained through FHIR might be a viable study solution for those sites that do not participate in PCORnet. ® This mixed-methods project had 2 objectives: (1) survey sites participating in PCORnet on the availability of FHIR (FHIR survey); (2) compare the coverage of a FHIR-based data extract using REDCap with one from the PCORnet ® CDM across 3 sites (FHIR extract). Methods: (1) FHIR survey: A series of questions were asked about the use of FHIR in a production capacity. (2) FHIR extract: REDCap FHIR and PCORnet ® CDM extracts were created based on study variables from 2 prior PCORnet ® Studies. Data were extracted for 40 patients and concordance measures were computed between the 2 sources. Results: (1) FHIR survey: Of responding organizations, 73% (n=49) reported that FHIR was deployed in a production capacity. (2) FHIR extract: Results were highly variable. Cohen kappa ranged from 0.01 to 0.76 for certain diagnoses, 0.24 to 0.84 for laboratory results, and 0.1 to 0.87 for medications. Conclusions: Despite differences in data, certain studies may be well-suited for FHIR-based extracts.

Abstract Blood-based biomarkers show promise as a noninvasive method for measuring Alzheimer’s disease pathology and neurodegeneration throughout the lifecourse. However, the relationship between longitudinal changes in these biomarkers and late-life brain morphology in community-dwelling populations requires further investigation. Between 2011 and 2013, 1,977 participants from the Atherosclerosis Risk in Communities Study received underwent 3 Tesla magnetic resonance imaging scans. Whole-brain cortical thickness was quantified by Freesurfer. Stored plasma samples collected in midlife (1993-95, mean age 59.0 years) and late-life (2011-13, mean age 76.8 years) from a subsample of 1,515 participants (60.7% female, 25.5% Black adults) 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). Linear regression models estimated the association of blood-based biomarkers from midlife, late-life, and the change from midlife to late-life with cortical thickness in late-life. In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, higher midlife measures of p-Tau181 and increases from midlife to late-life in NfL and GFAP were associated with lower cortical thickness in late-life. Concurrent measures of p-Tau181, NfL, and GFAP were associated with lower cortical thickness in late-life and exhibited a stronger association among participants ≥75 years old compared to participants &lt;75 years old. Additional longitudinal research is needed to determine whether blood-based biomarkers predict cortical thinning over time and may serve as an early indicator of accelerated brain atrophy.

Abstract Background Even among cognitively unimpaired (CU) older adults, specific patterns of neuropsychological performance impart differential risk for progression to Alzheimer's disease and related dementias (ADRD). Early identification in the prodromal phase may inform early intervention efforts. We used a data‐driven approach to classify neuropsychological phenotypes within CU older adults from the Atherosclerosis Risk in Communities (ARIC) study and tested for differences in ADRD and cerebrovascular outcomes. Method Participants included 4737 CU (via a previously published algorithm plus consensus diagnosis protocol) older adults (mean age=75.1 years, 60.8% female, 23.1% Black) with neuropsychological data from Visit 5 (2011‐2013) of the ARIC study. Latent profile analysis was leveraged to identify unique cognitive phenotypes using 10 demographically adjusted (age, sex/gender, education, race‐center, WRAT Reading) neuropsychological z‐scores. Cognitive phenotypes were then compared on demographics, depressive symptoms, and vascular risk factors (VRFs). In a subset with available neuroimaging and biofluid data ( n range=1102‐1678), white matter hyperintensity (WMH) and bilateral hippocampal (HV) volumes normalized for intracranial volume and plasma biomarkers (i.e., Aβ42/40, ptau181, NfL, and GFAP) were examined by phenotype. Phenotype comparisons adjusted for demographic variables, VRFs, and an indicator of kidney function (i.e., eGFR‐creatinine) for plasma biomarkers. We applied Tukey adjustment for pairwise comparisons. Result A 6‐class solution of cognitive phenotypes emerged as the best fitting model: Average Overall (28%), Low Overall/Very Low Memory (7%), Average Overall/Super Memory (11%), Subtle Low Overall/Low Executive (22%), Subtle Low Executive/High Memory (13%), and Average Overall/Low Memory (19%; Figure 1). Phenotypes differed on education, race, and word reading, despite prior adjustments for these variables when creating the neuropsychological z‐scores (Table 1). Additionally, phenotypes differed on depressive symptoms, VRFs, WMH, HV, Aβ42/40, and ptau181 (all p s < .05). The Subtle Low Overall/Low Executive group had the highest WMH volumes, the Subtle Low Executive/High Memory group had the lowest Aβ42/40, and the Low Overall/Very Low Memory group had the lowest HV and highest levels of plasma ptau181 (Table 2). Conclusion Cognitive heterogeneity is observed even among CU older adults, with lower executive performance associated with cerebrovascular changes and lower memory associated with certain AD‐related changes, possibly indicating risk for cognitive progression through distinct pathways.

Abstract Background The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) randomized trial ( n = 977;ClinicalTrials.gov:NCT03243422) demonstrated that hearing intervention slowed 3‐year cognitive decline by 48% among a subgroup of participants. To further investigate differences by treatment with respect to cognitive benefit, we tested the hypothesis that hearing intervention is associated with improved neurodegeneration blood biomarkers 3‐years post‐randomization and assessed whether combining biomarkers and cognitive results improved power in the trial design. Method The ACHIEVE study is a multicenter, parallel‐arm, randomized trial (hearing intervention vs health education control) on 3‐year cognitive decline among adults 70–84years with untreated hearing loss and without substantial cognitive impairment. Participants were recruited from two populations: (1) a long‐standing cardiovascular health observational study (Atherosclerosis Risk in Communities [ARIC]), and (2) de novo community volunteers. Plasma was collected in year 3 in a subsample ( n = 540) while ARIC participants ( n = 164) also had baseline plasma. Glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) neurodegenerative biomarkers were derived using the Alamar CNS protein panel. Regression models estimated the association of treatment with 3‐year biomarkers and global cognitive differences in the combined sample and by recruitment source and annualized change from baseline in the ARIC sample. We included a simple composite score of the standardized outcomes (Table 2). Result Among the subsample, baseline characteristics were balanced by treatment. There were no significant differences on 3‐year neurodegeneration biomarker levels by treatment in the combined (Table 1) or de novo groups (Table 2). Among ARIC participants, intervention resulted in lower 3‐year GFAP (mean:‐0.415;95%CI:‐0.712,‐0.118) and NfL (mean:‐0.349;95%CI:‐0.652,‐0.046) (Table 2). Annualized change from baseline analyses among ARIC participants (Table 3) revealed intervention was associated with a slower rate of cognitive decline (difference‐in‐means:0.059;95%CI:0.018,0.100) and a slower rate of increase in GFAP (difference‐in‐means: ‐0.060;95%CI:‐0.112,‐0.009). Differences in estimates suggest combined score, relative to cognition alone, may increase power in clinical trials that show a positive effect (ARIC subgroup: p = 0.02vs. 0.08[Table 2] and p = 0.0009vs.0.048[Table 3]). Conclusion Hearing intervention was associated with positive 3‐year effects on neurodegeneration blood biomarkers in ARIC participants which parallels cognitive decline results. Results provides objective evidence of brain changes following hearing intervention and potential signal of a more powerful combined outcome approach for future brain health clinical trials.

PURPOSE The feasibility of Oncotype DX Breast Recurrence Score testing on diagnostic core needle biopsy (CNB) samples has been demonstrated through analysis of a large central laboratory experience. However, concordance with paired samples from the same primary breast tumor has not been comprehensively evaluated. The primary objective of this study was to determine the degree of concordance of Recurrence Score (RS) results between paired CNB and surgical excision (SE) specimens from the same untreated primary breast tumor of patients with early-stage, hormone receptor–positive, human epidermal growth factor receptor 2–negative invasive breast cancer. MATERIALS AND METHODS Patients with a clinical RS result on either a CNB or SE specimen were included. Lin concordance correlation coefficient (CCC) with 95% CIs was estimated to assess agreement of continuous RS results between paired samples. Cohen Kappa with 95% CIs was used to evaluate categorical RS result concordance. RESULTS A total of 134 patients were identified with paired CNB and SE specimens. The median age was 62 years (range, 33-99; 23 patients [17%] were age ≤50 years v 111 [83%] age >50 years). The mean RS results were 15.6 (range, 0-56) for CNB and 16.6 (range, 0-59) for SE ( P = .003), with no statistically significant differences in RS categories. Agreement between continuous RS results from paired samples was strong, with a Lin CCC of 0.86 (95% CI, 0.80 to 0.90). The overall percent agreement in RS categories was 91.8% (95% CI, 87.1 to 96.4). Categorical agreement was further supported by a Cohen Kappa statistic of 0.64 (95% CI, 0.44 to 0.83), indicating substantial agreement between CNB and SE specimens. CONCLUSION The results of this study demonstrate high concordance of RS results between paired samples, which supports the use of CNB for Oncotype DX testing.