Citations

Abstract Background Progressive supranuclear palsy (PSP) is a tauopathy for which there is limited understanding of epidemiological risk factors. Objective The objective of this study was to identify premorbid nonmedical and medical risk factors for PSP diagnosis in a large prospective population‐based cohort. Methods We performed a matched nested case–control study using the UK Biobank (UKB) cohort consisting of >500,000 adults aged 37 to 73 years. PSP diagnoses were identified from 2007 to censor date (August 2025) and matched 1:10 by age and sex to control subjects without parkinsonism or dementia diagnoses. We derived risk factors using an iterative logistic regression approach. Results There were 240 incident PSP diagnoses in the UKB. In the fully adjusted model, premorbid depression (odds ratio [OR], 3.22; 95% confidence interval [CI], 2.30–4.50; P < 0.001), delirium (OR, 6.76; 95% CI, 4.08–11.19; P < 0.001), and functional gastrointestinal disorders (OR, 1.91; 95% CI, 1.39–2.63; P < 0.001) were associated with increased risk. Heavy alcohol consumption was associated with higher risk compared with moderate consumption (OR, 1.65; 95% CI: 1.21–2.26; P = 0.0017). Body mass index (BMI) and alcohol consumption had nonlinear risk profiles. Cancer diagnosis was inversely associated with PSP (OR, 0.56; 95% CI, 0.40–0.79; P < 0.001). Depression and delirium diagnoses remained significant 5 to 10 years before diagnosis. Conclusions In this large prospective cohort, PSP was associated with premorbid lifestyle practices and neuropsychiatric diagnoses years before diagnosis. This suggests a long premotor phase and highlights opportunities for earlier diagnosis and further mechanistic investigation. The inverse association with cancer mirrors the relationship seen in other neurodegenerative conditions and may point toward shared mechanisms. © 2026 International Parkinson and Movement Disorder Society.

ABSTRACT Background Primary lateral sclerosis (PLS) is an ultrarare upper motor neuron syndrome with a prognosis unique from classical ALS. The study of PLS is complicated by its rarity and the difficulty distinguishing PLS from ALS. We present data from a 1‐year prospective follow‐up study on PLS and efforts to distinguish it from ALS. Methods Seventy‐six PLS participants enrolled in this prospective natural history study. EMG studies, blood neurofilament light chain levels (NfLs), and demographic characteristics were obtained at baseline. At 1‐year follow‐up, repeat EMG studies were conducted to determine which participants fulfilled criteria for ALS. Baseline characteristics were then compared to determine features that predict reclassification. Results Seventy participants completed 1‐year follow‐up. Five of the 70 were reclassified to ALS (7.1%). Those reclassified had higher trends in baseline blood NfL levels (91.4 vs. 34.0 pg/mL, p = 0.13) and shorter symptom duration (39 vs. 69 months in the PLS group, p = 0.15). Reclassification was noted in both probable and definite PLS participants. All cases with a symptomatic duration of less than 2 years retained the PLS phenotype (5 of 5). NfL levels over 90 pg/mL predicted reclassification with 94% specificity and 60% sensitivity. No other features predicted reclassification to ALS. Conclusions In our population, reclassification of PLS to ALS occurred at a low frequency at 1 year follow‐up (7.1%). Baseline NfL was the strongest predictor in differentiating UMN dominant ALS from PLS at 1‐year follow‐up. Based on our data, we propose EMG and NfL criteria for enrollment in future PLS trials.

Background Uncontrolled hypertension is common in chronic kidney disease (CKD) patients. Electro-hydraulic acoustic therapy (eHAT) is a non-invasive treatment that may lower blood pressure (BP), but its safety and efficacy in CKD remain unclear. This study aimed to evaluate eHAT's feasibility and safety in this population. Methods In this single-arm, prospective, single-center proof-of-concept study, CKD patients received six eHAT treatments over three weeks. BP was assessed in-office (attended and unattended) at baseline and at 4-, 12-, 24-, and 48-weeks post-treatment. Ambulatory BP monitoring (ABPM) was performed at baseline, 12, and 48 weeks. The primary endpoint was change in systolic office BP (OBP) from baseline to 12 weeks. Secondary endpoints included additional BP measurements, kidney function, and safety. Results Fifteen patients completed all follow-ups. At 12 weeks, mean systolic OBP decreased by 9.73 mmHg (SD 14.77; p = 0.0032) and remained significantly lower at 24 weeks (−7.67 mmHg; p = 0.0335) and 48 weeks (−19.40 mmHg; p &lt; 0.0001). Diastolic OBP reductions were significant at 12 ( p = 0.0413) and 48 weeks ( p = 0.0022). By 12 weeks, 26% of participants reduced the number or dose of antihypertensive medications. Kidney function remained stable throughout. No safety signals were detected. Conclusion Our study highlights the feasibility and tolerability of eHAT in patients with CKD and HTN. Nonetheless, due to the small sample size and lack of a control group, these findings should be considered preliminary.

PURPOSE The continuous development of new imaging approaches, molecular phenotyping, genetic subtypes, prognosis assessments, and effective therapies across a range of disease states has created a need to redefine terminology and best practices for clinical trial conduct in patients with advanced prostate cancer. Methods We convened an international expert committee of diverse working groups, the Prostate Cancer Working Group 4 (PCWG4), between 2016 and 2025. Our objective was to formulate updated criteria based on emerging evidence and clinical trial data in a biomarker context to provide guidance for clinical trial design, eligibility, and end point assessments for patients with advanced prostate cancer. RESULTS PCWG4 redefines terminology around the disease state and previous therapies in a patient-centric context and terminology focused on androgen pathway modulation. We consider imaging, with a particular focus on positron emission tomography (PET)–defined disease. New recommendations are provided for disease state terminology, defining eligibility criteria, response and delay/prevent end points, intervals for reassessments including imaging, and patient-reported outcome determination. We provide recommendations in a biomarker-based context of use for the intended indication, reflective of patient benefit for specific interventions. We emphasize the need for development of validated PET imaging and molecular and phenotypic criteria as well as trial designs to appropriately risk stratify patients, predict and assess benefit, and measure post-treatment outcomes reliably in a trial framework. CONCLUSION PCWG4 updates recommendations on patient and tumor characterization, therapy development, and imaging criteria and extends guidance into earlier androgen pathway modulator–naïve/sensitive disease states to reflect an evolving, heterogeneous, and diverse patient population to optimize treatment benefits for all patients.

Abstract Background The ability of large language models (LLMs) to work collaboratively and screen studies in a systematic review (SR) is under-explored. Hence, we aimed to evaluate the effectiveness of LLMs in automating the process of screening in systematic reviews. Methods This is an observational study which included labeled data (title and abstracts) for five SRs. Originally, two reviewers screened the citations independently for eligibility. A third reviewer cross-checked each citation for quality assurance. GPT-4, Claude-3-Sonnet, and Gemini-Pro-1.0 were used using zero-shot chain-of-thought prompting. Collaborative approaches included (i): conflict resolution using benefit of the doubt, (ii) majority voting using an independent third LLM and (iii) conflict resolution using an informed third LLM. Performance was assessed using accuracy, precision for exclusion, and recall for inclusion. Work saved over samples (WSS) was computed to estimate the reduction in manual human effort. Results A total of 11300 articles were included in this study. The individual models, GPT-4, Claude-3-Sonnet, and Gemini-Pro-1.0 exhibited a high precision for exclusion, achieving 99.7%, 99.7%, and 99.2% and high recall for inclusion achieving 95.5%, 96.6% and 85.7%, respectively. However, the collaborative approach utilizing the two best-performing models (GPT-4 and Claude-3S) achieved an average precision of 99.9% and a recall of 98.5% (across all collaborative approaches). Furthermore, the proposed collaborative approach resulted in an average WSS of 63.5%, compared to the average WSS of 45.2% for individual models. Conversational LLM interactions showed a consistent pattern of results. Limitations This study was limited due to reliance on proprietary models, and evaluation on oncology datasets. Conclusion Evidence shows that collaborative LLMs enable efficient, high-performing screening in systematic reviews, supporting continuous evidence updates. Primary funding source NIH (U24CA265879-01-1) and Carolyn-Ann-Kennedy-Bacon Fund.