Long driving distances to transplantation centers may impede access to care for hematopoietic cell transplantation (HCT) survivors. As a secondary analysis from the multicenter INSPIRE study (NCT01602211), we examined baseline data from relapse-free HCT adult survivors (2 to 10 years after allogeneic or autologous HCT) to investigate the association between driving distances and patient-reported outcome (PRO) measures of distress and physical function. We analyzed predictors of elevated distress and impaired physical function using logistic regression models that operationalized driving distance first as a continuous variable and separately as a dichotomous variable (<100 versus 100+ miles). Of 1136 patients available for analysis from 6 US centers, median driving distance was 82 miles and 44% resided 100+ miles away from their HCT centers. Elevated distress was reported by 32% of patients, impaired physical function by 19%, and both by 12%. Driving distance, whether operationalized as a continuous or dichotomous variable, had no impact on distress or physical function in linear regression modeling (95% confidence interval, 1.00 to 1.00, for both PROs with driving distance as a continuous variable). In contrast, chronic graft-versus-host-disease, lower income, and lack of Internet access independently predicted both elevated distress and impaired physical function. In summary, we found no impact of driving distance on distress and physical function among HCT survivors. Our results have implications for how long-term follow-up care is delivered after HCT, with regard to the negligible impact of driving distances on PROs and also the risk of a "digital divide" worsening outcomes among HCT survivors without Internet access.
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http://dx.doi.org/10.1016/j.bbmt.2020.08.002 | DOI Listing |
ChemMedChem
January 2025
National Institute of Standards and Technology, Material Measurement Laboratory, UNITED STATES OF AMERICA.
Antibody-based pharmaceuticals are the leading biologic drug platform (> $75B/year). Despite a wealth of information collected on them, there is still a lack of knowledge on their inter-domain structural distributions, which impedes innovation and development. To address this measurement gap, we have developed a new methodology to derive biomolecular structure ensembles from distance distribution measurements via a library of tagged proteins bound to an unlabeled and otherwise unmodified target biologic.
View Article and Find Full Text PDFChembiochem
January 2025
Institute for Drug Discovery, University of Leipzig, Brüderstr. 34, 04103, Leipzig, Germany.
Recent advances in computational methods like AlphaFold have transformed structural biology, enabling accurate modeling of protein complexes and driving applications in drug discovery and protein engineering. However, predicting the structure of systems involving weak, transient, or dynamic interactions, or of complexes with disordered regions, remains challenging. Nuclear Magnetic Resonance (NMR) spectroscopy offers atomic-level insights into biomolecular complexes, even in weakly interacting and dynamic systems.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Science and Technology - Food and Nutrition Research Institute, Taguig, Metro Manila, Philippines.
This study aimed to assess the environmental variables affecting the Body Mass Index of older adults at neighborhood levels (1 ha) while mapping probability distributions of normal, overweight-obese, and underweight older adults. We applied a data-driven method that integrates open-access remote sensing products and geospatial data, along with the first nutritional survey in the Philippines with geo-locations conducted in 2021. We used ensemble machine learning of different presence-only and presence-absence models, all subjected to hyperparameter tuning and variable decorrelation.
View Article and Find Full Text PDFAnn Biomed Eng
January 2025
Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, CCIT216, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.
Purpose: Simulation studies, such as finite element (FE) modeling, offer insights into knee joint biomechanics, which may not be achieved through experimental methods without direct involvement of patients. While generic FE models have been used to predict tissue biomechanics, they overlook variations in population-specific geometry, loading, and material properties. In contrast, subject-specific models account for these factors, delivering enhanced predictive precision but requiring significant effort and time for development.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
Institut de Mathématiques de Jussieu - Paris Rive Gauche (IMJ-PRG), UMR 7586, CNRS, Université Paris Diderot, 8, Pace Aurélie Nemours, 75013 Paris, France.
Accurate protein synthesis requires ribosomes to integrate signals from distant functional sites and execute complex dynamics. Despite advances in understanding ribosome structure and function, two key questions remain: how information is transmitted between these distant sites, and how ribosomal movements are synchronized? We recently highlighted the existence of ribosomal protein networks, likely evolved to participate in ribosome signaling. Here, we investigate the relationship between ribosomal protein networks and ribosome dynamics.
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