Background: Composite measures are useful for distilling quality data into summary scores; yet, there has been limited use of composite measures for cancer care.
Objective: Compare multiple approaches for generating cancer care composite measures and evaluate how well composite measures summarize dimensions of cancer care and predict survival.
Study Design: We computed hospital-level rates for 13 colorectal, lung, and prostate cancer process measures in 59 Veterans Affairs hospitals. We computed 4 empirical-factor (based on an exploratory factor analysis), 3 cancer-specific (colorectal, lung, prostate care), and 3 care modality-specific (diagnosis/evaluation, surgical, nonsurgical treatments) composite measures. We assessed correlations among all composite measures and estimated all-cause survival for colon, rectal, non-small cell lung, and small cell lung cancers as a function of composite scores, adjusting for patient characteristics.
Results: Four factors emerged from the factor analysis: nonsurgical treatment, surgical treatment, colorectal early diagnosis, and prostate treatment. We observed strong correlations (r) among composite measures comprised of similar process measures (r=0.58-1.00, P<0.0001), but not among composite measures reflecting different care dimensions. Composite measures were rarely associated with survival.
Conclusions: The empirical-factor domains grouped measures variously by cancer type and care modality. The evidence did not support any single approach for generating cancer care composite measures. Weak associations across different care domains suggest that low-quality and high-quality cancer care delivery may coexist within Veterans Affairs hospitals.
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http://dx.doi.org/10.1097/MLR.0000000000000257 | DOI Listing |
Neurology
February 2025
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Background And Objectives: Lipid metabolism in older adults is affected by various factors including biological aging, functional decline, reduced physiologic reserve, and nutrient intake. The dysregulation of lipid metabolism could adversely affect brain health. This study investigated the association between year-to-year intraindividual lipid variability and subsequent risk of cognitive decline and dementia in community-dwelling older adults.
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January 2025
Nanophotonic Systems Laboratory, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland.
Droplet-based microfluidics is a powerful tool for high-throughput analysis of liquid samples with significant applications in biomedicine and biochemistry. Nevertheless, extracting content-rich information from single picolitre-sized droplets at high throughputs remains challenging due to the weak signals associated with these small volumes. Overcoming this limitation would be transformative for fields that rely on high-throughput screening, enabling broader multiparametric analysis.
View Article and Find Full Text PDFJ Vis Exp
January 2025
Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee;
Cardiovascular disease (CVD) is the leading cause of death in the United States. Damage in the cardiovascular system can be due to environmental exposure, trauma, drug toxicity, or numerous other factors. As a result, cardiac tissue and vasculature undergo structural changes and display diminished function.
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February 2025
Motion and Exercise Science, University of Stuttgart, Stuttgart, Germany.
The maintenance of an appropriate ratio of body fat to muscle mass is essential for the preservation of health and performance, as excessive body fat is associated with an increased risk of various diseases. Accurate body composition assessment requires precise segmentation of structures. In this study we developed a novel automatic machine learning approach for volumetric segmentation and quantitative assessment of MRI volumes and investigated the efficacy of using a machine learning algorithm to assess muscle, subcutaneous adipose tissue (SAT), and bone volume of the thigh before and after a strength training.
View Article and Find Full Text PDFLab Chip
January 2025
Antwerp Engineering, Photoelectrochemistry and Sensing (A-PECS), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium.
Wearable microfluidic sweat sensors could play a major role in the future of monitoring health and wellbeing. Sweat contains biomarkers to monitor health and hydration status, and it can provide information on drug intake, making it an interesting non-invasive alternative to blood. However, sweat is not created in excess, and this requires smart sweat collection strategies to handle small volumes.
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