Attempts to characterize and formally qualify biomarkers for regulatory purposes have raised questions about how histological and histopathological methods impact the evaluation of biomarker performance. A group of pathologists was asked to analyze digitized images prepared from rodent kidney injury experiments in studies designed to investigate sources of variability in histopathology evaluations. Study A maximized variability by using samples from diverse studies and providing minimal guidance, contextual information, or opportunities for pathologist interaction. Study B was designed to limit interpathologist variability by using more uniform image sets from different locations within the same kidneys and allowing pathologist selected interactions to discuss and identify the location and injury to be evaluated but without providing a lexicon or peer review. Results from this study suggest that differences between pathologists and across models of disease are the largest sources of variability in evaluations and that blind evaluations do not generally make a significant difference. Results of this study generally align with recommendations from both industry and the U.S. Food and Drug Administration and should inform future studies examining the effects of common lexicons and scoring criteria, peer review, and blind evaluations in the context of biomarker performance assessment.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1177/0192623314562072 | DOI Listing |
J Chromatogr B Analyt Technol Biomed Life Sci
December 2024
Clinical Laboratory, Catharina Hospital Eindhoven, Eindhoven 5623 EJ, The Netherlands; Department of Biomedical Engineering, Chemical Biology, Eindhoven University of Technology, Groene Loper 3, Eindhoven 5612 AE, The Netherlands.
Monitoring of kidney function traditionally relies on plasma creatinine concentrations, necessitating invasive blood draws. Non-invasively obtainable biofluids, such as sweat and saliva, present a patient-friendly alternative with potential for continuous monitoring. This study focusses on developing and validating a novel Liquid Chromatography- tandem Mass Spectrometry (LC-MS/MS) assay as a reference test for measuring low creatinine concentrations in sweat and saliva.
View Article and Find Full Text PDFRadiat Prot Dosimetry
January 2025
Medical Physics, Ghent University, Proeftuinstraat 86, 9000 Ghent, Belgium.
Quality control (QC) of personal radiation protective equipment (PRPE) is essential to detect tears and holes in the attenuating layers. Routinely, this QC is performed using fluoroscopy on a conventional X-ray table. However, such a QC procedure is laborious and time consuming.
View Article and Find Full Text PDFRetina
January 2025
Neuroradiology Department, CHRU Gui de Chauliac, F-34091 Montpellier, France.
Purpose: To investigate retinal microvascular changes in ischemic stroke patients using optical coherence tomography angiography (OCT-A) and assess these alterations based on stroke etiology.
Methods: Case-control study conducted at Montpellier University Hospital from May 2021 to March 2022 (IRB: 202000607). Retinal vascular features were compared between strokes patients and age- and sex- matched controls.
Pediatr Emerg Care
January 2025
University of California Davis School of Medicine, Sacramento, CA.
Objective: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric emergency department patients and assess the impact of medically oriented fine-tuning.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Working Group for Data-Driven Innovation, Hamburg University of Technology, Hamburg, Germany.
Background: Health care innovation faces significant challenges, including system inertia and diverse stakeholders, making regulated market access pathways essential for facilitating the adoption of new technologies. The German Digital Healthcare Act, introduced in 2019, offers a model by enabling digital health applications (DiGAs) to be reimbursed by statutory health insurance, improving market access and patient empowerment. However, the factors influencing the success of these pathways in driving innovation remain unclear.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!