Introduction: Alzheimer's disease (AD) is a neurological disorder with variability in pathology and clinical progression. AD patients may differ in individual-level benefit from amyloid beta removal therapy.
Methods: Random forest models were applied to the EMERGE trial to create an individual-level treatment response (ITR) score which represents individual-level benefit of high-dose aducanumab relative to the placebo. This ITR score was used to test the existence of heterogeneity in treatment effect (HTE).
Results: We found statistical evidence of HTE in the Clinical Dementia Rating-Sum of Boxes (CDR-SB;P = 0.034). The observed CDR-SB benefit was 0.79 points greater in the group with the top 25% of ITR score compared to the remaining 75% (P = 0.020). Of note, the highest treatment responders had lower hippocampal volume, higher plasma phosphorylated tau 181 and a shorter duration of clinical AD at baseline.
Discussion: This ITR analysis provides a proof of concept for precision medicine in future AD research and drug development.
Highlights: Emerging trials have shown a population-level benefit from amyloid beta (Aβ) removal in slowing cognitive decline in early Alzheimer's disease (AD). This work demonstrates significant heterogeneity of individual-level treatment effect of aducanumab in early AD. The greatest clinical responders to Aβ removal therapy have a pattern of more severe neurodegenerative process.
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http://dx.doi.org/10.1002/alz.13431 | DOI Listing |
Diagn Progn Res
January 2025
Department of Clinical Medicine, Hammel Neurorehabilitation Centre-University Research Clinic, Aarhus University, Voldbyvej 15, 8450, Hammel, Denmark.
Background: The initial theme of the PROGRESS framework for prognosis research is termed overall prognosis research. Its aim is to describe the most likely course of health conditions in the context of current care. These average group-level prognoses may be used to inform patients, health policies, trial designs, or further prognosis research.
View Article and Find Full Text PDFPLoS One
January 2025
School of Public Health, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia.
Introduction: One of the key strategies to achieve the sustainable development goal by reducing maternal deaths below 70 per 100,000 is improving knowledge of obstetric danger signs (ODS). However, mothers' knowledge of ODS is low in general and very low in rural settings, regardless of local and national efforts in Ethiopia. Further, there is significant variation of ODS knowledge among women from region to region and urban/rural settings.
View Article and Find Full Text PDFJ Speech Lang Hear Res
January 2025
Center for Speech and Language Sciences, Department of Rehabilitation Sciences, Ghent University, Belgium.
Purpose: The aim was to determine and compare the short-term effects of two intensive semi-occluded vocal tract (SOVT) programs, "straw phonation" (SP) and "resonant voice therapy" (RVT), on the phonation of children with vocal fold nodules.
Method: A pretest-posttest randomized controlled study design was used. Thirty children aged 6-12 years were randomly assigned to the SP group ( = 11), RVT group ( = 11), or control group receiving indirect treatment ( = 8) for their voice problems.
Hum Brain Mapp
January 2025
Amsterdam UMC, Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, the Netherlands.
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.
View Article and Find Full Text PDFHealth Econ
January 2025
School of International Trade and Economics, University of International Business and Economics, Beijing, China.
While the direct health impacts of air pollution are widely discussed, its indirect effects, particularly during pandemics, are less explored. Utilizing detailed individual-level data from all designated hospitals in Wuhan during the initial COVID-19 outbreak, we examine the impact of air pollution exposure on treatment costs and health outcomes for COVID-19 patients. Our findings reveal that patients exposed more intensively to air pollution, identified by their residence in downwind areas of high-polluting enterprises, not only had worsened health outcomes but also consumed more medical resources.
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