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Hantavirus antibody seroprevalence and risk factors among adults in West Kazakhstan, 2023.
Front Public Health
January 2025
Department of Global Health, Emory Rollins School of Public Health, Atlanta, GA, United States.
Background: Orthohantaviruses (also known as hantaviruses) are pathogens, primarily transmitted by rodents, that can cause hemorrhagic fever with renal syndrome (HFRS). In endemic regions of Kazakhstan, no confirmed HFRS cases were detected between 2020 and 2022 raising concerns about detection. Estimate antibody seroprevalence for hantaviruses and identify associated risk factors among high-risk adults in western Kazakhstan in 2023.
View Article and Find Full Text PDFLINC01322 may serve as a potential diagnostic marker for advanced stage tumors in renal cell carcinoma patients eligible for total nephrectomy.
Biochem Biophys Rep
December 2024
Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Background: Renal cell carcinoma (RCC) is a common urological cancer globally and shows a favorable prognosis in early stages of the tumor progression. Due to the poor prognosis for metastatic RCC patients, it is crucial to explore the molecular biology of RCC progression to establish efficient diagnostic and therapeutic markers for these patients. Long non-coding RNAs (lncRNAs) have critical roles in regulation of tumor cell proliferation, migration, and apoptosis during RCC progression.
View Article and Find Full Text PDFFrom prediction to practice: mitigating bias and data shift in machine-learning models for chemotherapy-induced organ dysfunction across unseen cancers.
BMJ Oncol
November 2024
Department of Computer Science, Durham University, Durham, UK.
Objectives: Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.
View Article and Find Full Text PDFEnhancing individual glomerular filtration rate assessment: can we trust the equation? Development and validation of machine learning models to assess the trustworthiness of estimated GFR compared to measured GFR.
BMC Nephrol
January 2025
Department of Nephrology-Dialysis-Transplantation, University of Liège, CHU Sart Tilman, Liège, Belgium.
Background: Creatinine-based estimated glomerular filtration rate (eGFR) equations are widely used in clinical practice but exhibit inherent limitations. On the other side, measuring GFR is time consuming and not available in routine clinical practice. We developed and validated machine learning models to assess the trustworthiness (i.
View Article and Find Full Text PDFUnanchored simulated treatment comparison on survival outcomes using parametric and Royston-Parmar models with application to lenvatinib plus pembrolizumab in renal cell carcinoma.
BMC Med Res Methodol
January 2025
Clifton Insight, Bristol, UK.
Background: Population-adjusted indirect comparison using parametric Simulated Treatment Comparison (STC) has had limited application to survival outcomes in unanchored settings. Matching-Adjusted Indirect Comparison (MAIC) is commonly used but does not account for violation of proportional hazards or enable extrapolations of survival. We developed and applied a novel methodology for STC in unanchored settings.
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