Background: Reducing the burden of dementia in First Nations populations may be addressed through developing population specific methods to quantify future risk of dementia.
Objective: To adapt existing dementia risk models to cross-sectional dementia prevalence data from a First Nations population in the Torres Strait region of Australia in preparation for follow-up of participants. To explore the diagnostic utility of these dementia risk models at detecting dementia.
Methods: A literature review to identify existing externally validated dementia risk models. Adapting these models to cross-sectional data and assessing their diagnostic utility through area under the receiver operating characteristic curve (AUROC) analyses and calibration using Hosmer-Lemeshow Chi.
Results: Seven risk models could be adapted to the study data. The Aging, Cognition and Dementia (AgeCoDe) study, the Framingham Heart Study (FHS), and the Brief Dementia Screening Indicator (BDSI) had moderate diagnostic utility in identifying dementia (i.e., AUROC >0.70) before and after points for older age were removed.
Conclusion: Seven existing dementia risk models could be adapted to this First Nations population, and three had some cross-sectional diagnostic utility. These models were designed to predict dementia incidence, so their applicability to identify prevalent cases would be limited. The risk scores derived in this study may have prognostic utility as participants are followed up over time. In the interim, this study highlights considerations when transporting and developing dementia risk models for First Nations populations.
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http://dx.doi.org/10.3233/ADR-220093 | DOI Listing |
Discov Oncol
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Department of General Surgery, The Second Affiliated Hospital of the Air Force Medical University, Xi'an, 710038, China.
A common digestive system cancer with a dismal prognosis and a high death rate globally is breast cancer (BRCA). BRCA recurrence, metastasis, and medication resistance are all significantly impacted by cancer stem cells (CSCs). However, the relationship between CSCs and the tumor microenvironment in BRCA individuals remains unknown, and this information is critically needed.
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Division of Medical Oncology, Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, 8700 Beverly Blvd., Los Angeles, CA, 90048, USA.
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Am J Sports Med
January 2025
Department of Pharmacology and Biostatistics, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
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Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196).
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Cosmetics Europe, Brussels, Belgium.
Grouping of chemicals has been proposed as a strategy to speed up the screening and identification of potential substances of concern among the broad chemical universe under REACH. Such grouping is usually based on shared structural features and should only be used for the prioritization objectives. However, additional considerations (as well as structural similarity) are needed, e.
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