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http://dx.doi.org/10.1001/jamainternmed.2015.1616 | DOI Listing |
J Clin Neurophysiol
February 2025
Division of Child Neurology, Department of Neurology, Stanford University, Palo Alto, California, U.S.A.
The development of clinical practice guidelines is an evolving field. In response to the need for consistent, evidence-based medical practice, the American Clinical Neurophysiology Society identified the need to update the Society's guideline development process. The American Clinical Neurophysiology Society Guidelines Committee created an action plan with the goal of improving transparency and rigor for future guidelines and bringing existing guidelines to current standards.
View Article and Find Full Text PDFCancer
February 2025
University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland Medical Center, Baltimore, Maryland, USA.
Tarlatamab is a bispecific T-cell engager immunotherapy targeting delta-like ligand 3 (DLL3) and the cluster of differentiation 3 (CD3) molecule. In the phase 2 DeLLphi-301 trial of tarlatamab for patients with previously treated small cell lung cancer, tarlatamab 10 mg every 2 weeks achieved durable responses and encouraging survival outcomes. Analyses of updated safety data from the DeLLphi-301 trial demonstrated that the most common treatment-emergent adverse events were cytokine release syndrome (53%), pyrexia (38%), decreased appetite (36%), dysgeusia (32%), and an emia (30%).
View Article and Find Full Text PDFJ Infect
January 2025
Research Your Health, 6020 West Parker Road, Suite 430, Plano, Texas, 75093, USA.
Objectives: Safety and immunogenicity assessment of updated monovalent and bivalent SARS-CoV-2 vaccines in adolescents.
Methods: This phase 3, double-blinded study randomised 12-<18-year-old participants, who received ≥2 prior doses of an approved/authorised mRNA-based COVID-19 vaccine, 1:1 to receive NVX-CoV2601 (XBB.1.
Sci Rep
January 2025
CALCE University of Maryland, College Park, MD, 20742, USA.
Remaining useful life (RUL) prediction is a crucial aspect of the prognostics health management of lithium-ion batteries (LIBs). Owing to the influence of resampling technology, particle degradation is often observed in the particle filter-based RUL prediction of LIBs, resulting in a low prediction accuracy and large uncertainty. In this paper, a novel particle flow filter with the grey model method (GM-PFF) is proposed to forecast the RUL and state of health of batteries.
View Article and Find Full Text PDFStat Med
February 2025
U.S. Food and Drug Administration, Silver Spring, Maryland.
The recent U.S. Food and Drug Administration guidance on complex innovative trial designs acknowledges the use of Bayesian strategies to incorporate historical information based on clinical expertise and data similarity.
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