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Chimeric antigen receptor T-cell (CAR-T) and CD20xCD3 bispecific antibody (BsAb) therapies are both effective for relapsed/refractory (R/R) follicular lymphoma (FL), but comparative real-world survival outcomes and time toxicity have not been characterized. We performed a multicenter retrospective study of 228 patients with R/R FL treated with standard-of-care CAR-T (n = 141) or BsAb (n = 87) across 17 U.S. academic centers in the third-line or later setting. Progression-free survival (PFS) and overall survival (OS) were stratified by 2 or ≥3 prior lines of therapy (LOT2 or LOT3+), including propensity matching. Time toxicity was measured by physical health care contact days. Median PFS was not reached (NR) with CAR-T and 581 days with BsAb in the LOT2 cohort (p < .0001), and was NR with CAR-T and 584 days with BsAb in the LOT3+ cohort (p = .0064). CAR-T recipients were younger (p < .0001) and had better performance status (p = .007) but were more refractory to prior LOT (p = .017). PFS advantages of CAR-T were independent of these differences. OS did not differ between treatment groups. CAR-T had significantly greater time toxicity over the first year, with higher mean contact days than BsAb in both the LOT2 (58 vs 44) and LOT3+ (69 vs 49) cohorts. In this large multicenter cohort of patients with R/R FL, CAR-T was associated with superior PFS but greater time toxicity compared with BsAb therapy. These findings provide real-world outcomes data and time toxicity benchmarks to support treatment sequencing decision-making in R/R FL.

ABSTRACT Artificial intelligence (AI) has emerged as a transformative technology in the fields of medicine and ophthalmology. Recent advances in machine learning, deep learning and convolutional neural networks have significantly improved cataract detection and grading, intraocular lens power calculations, surgical decision‐making, risk prediction and patient education. Intraoperative AI‐assisted surgical phase recognition, workflow analysis, real‐time guidance, robotic technologies and femtosecond laser integration can improve surgical precision, efficiency and safety. AI has shown promise in predicting visual outcomes, detecting postoperative complications and facilitating telemedicine follow‐up. Though challenges with AI include transparency, data diversity, regulatory oversight and clinical validation, continued advances are expected to further personalise cataract surgery, support clinical decision‐making, optimise surgical performance and improve patient outcomes. This narrative summarises the current and emerging applications of AI in preoperative, intraoperative and postoperative management of cataracts.

Abstract Context Menstrual irregularities have been associated with cardiovascular disease (CVD) risk, but underlying etiologies may confer distinct risk profiles. Functional hypothalamic amenorrhea (FHA) has not been evaluated as a separate risk phenotype. Objective To assess the association between FHA phenotype and incident CVD and cardiometabolic risk factors. Design Prospective cohort study with biennial follow-up from 1993 to 2019. Setting Nurses’ Health Study II cohort. Participants The sample included 52,655 premenopausal women free of CVD in 1993. FHA phenotype was defined as irregular or absent cycles without PCOS traits combined with low body mass index and/or high physical activity. Intervention None Main Outcome Measures Incident CVD (coronary heart disease [CHD; myocardial infarction or coronary revascularization] and stroke) and incident elevated cholesterol, hypertension, and type 2 diabetes (T2DM). Results During up to 26 years of follow-up, 1,007 CVD events occurred. Among women who developed CVD, the median time to the first CVD event was 17.0 years (IQR, 11.3-21.0). FHA phenotype in mid-adulthood was associated with a 62% higher risk of CVD (95% confidence interval [CI]: 1.01–2.59), driven by an almost two-fold higher risk of CHD (hazard ratio [HR] = 1.91; 95% CI: 1.11–3.27), compared with women with regular cycles. FHA was also associated with T2DM (HR = 1.86; 95% CI: 1.41–2.47), but not hypertension or elevated cholesterol. Non-FHA menstrual irregularity was associated with elevated cholesterol, hypertension, and T2DM, but not CVD. FHA in early adulthood was not associated with outcomes. Conclusions FHA phenotype in mid-adulthood was associated with increased CHD risk independent of traditional risk factors. Menstrual history may serve as an early marker of cardiometabolic risk.

Abstract Introduction Quantitative interpretation of pediatric brain [ 18 F]-FDG PET is limited by the lack of age-matched normative reference databases, despite substantial developmental variation in cerebral glucose metabolism. This study aimed to construct a large-scale normative pediatric [ 18 F]-FDG PET database and develop an age-specific z-score mapping framework for quantitative evaluation of pediatric epilepsy. Method Pediatric brain PET data were retrospectively derived from clinically acquired whole-body or dedicated [ 18 F]-FDG PET examinations in participants 0–19 years of age without neurologic disease or visible brain abnormalities. A total of 417 PET scans from 341 participants were stratified into five developmental age groups: infancy, early childhood, middle childhood/school age, adolescence, and late adolescence. SUVR maps were generated using whole-brain atlas and brainstem reference regions. Voxel-wise t-test analyses were performed to characterize age- and sex-related metabolic differences. Age-specific voxel-wise mean and standard deviation maps were generated from the normative cohort and used to calculate age-matched hypometabolic z-score maps in 14 pediatric patients with epilepsy. The resulting abnormalities were qualitatively evaluated for concordance with epileptogenic findings identified on clinical MRI and/or PET by expert image review. Results Voxel-wise analyses demonstrated prominent age-dependent SUVR differences, particularly between infancy and older age groups. With whole-brain atlas normalization, older children showed progressively higher relative SUVR in cortical and cerebellar gray matter regions, whereas infancy showed relatively higher SUVR in the occipital cortex, white matter, thalamus, and brainstem. Brainstem normalization produced distinct developmental patterns, emphasizing higher white matter SUVR in infancy and broader gray matter differences in older groups. Sex-related differences were limited and regionally specific. Whole-brain atlas normalization showed lower variability than brainstem normalization and was selected for z-score mapping. In representative epilepsy cases, age-matched z-score maps identified focal or regional hypometabolism corresponding to malformations of cortical development, focal cortical dysplasia, mesial temporal sclerosis, nonlesional MRI cases, remote insult, tumor-related abnormalities, and Sturge-Weber syndrome. Discussion A large-scale normative pediatric [18F]-FDG PET database can support developmentally appropriate quantitative interpretation of pediatric brain PET. Age-matched z-score mapping may complement visual assessment by highlighting abnormal cerebral glucose metabolism in pediatric epilepsy, although findings should be interpreted with MRI, EEG, seizure semiology, and other presurgical data.

Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.

Follicular occlusion disorders (FOD) represent a tetrad of chronic, recurrent inflammatory conditions united by a common pathophysiologic mechanism: follicular hyperkeratosis leading to occlusion, rupture, and subsequent abscess or sinus tract formation. First conceptualized as a triad in the 1950s and later expanded to a tetrad in the 1970s, this grouping includes hidradenitis suppurativa (HS), acne conglobata (AC), dissecting cellulitis of the scalp (DCS), and pilonidal sinus (PS). Despite their shared pathogenesis, each condition carries distinct clinical features, epidemiological profiles, and management considerations. This article aims to provide a comprehensive review of FOD, with a primary emphasis on HS (the most prevalent of the disorders). Hidradenitis suppurativa is a debilitating disease affecting ∼1% of the global population, predominantly in females, and the diagnosis is often delayed by 7 or more years. Multiple genes are linked to FOD patients with a positive familial history in 35% to 40%, along with lifestyle factors (smoking, alcohol consumption, and obesity). Key inflammatory mediators, including TNF-α, IL-1β, and IL-17, drive the chronic tissue destruction characteristic of FOD, frequently resulting in scarring, lymphedema, and significant psychosocial impairment. Wound care is critical and often underemphasized in disease management. This article outlines evidence-informed wound care strategies for both nonsurgical and postsurgical presentations, including dressing selection, exudate and odor management, pain and itch control, infection management, and the emerging role of intravenous ertapenem as rescue therapy. An interprofessional approach, integrating dermatology, surgery, wound care nursing, and psychosocial support, is emphasized throughout as essential to improving patient outcomes and quality of life. GENERAL PURPOSE: To increase clinicians’ understanding of follicular occlusion disorders including the associated risk factors, clinical manifestations, and evidence-based approaches for management. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and registered nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After participating in this educational activity, the participant will: Assess clinical characteristics of each follicular occlusion disorder Evaluate the basic disease mechanisms for follicular occlusion disorders Describe principal disease burdens that require wound care attention Identify the unique wound care strategies and follicular occlusion disorder challenges JOURNAL/aswca/04.03/00129334-202610000-00004/figure1/v/2026-09-18T181327Z/r/image-jpeg