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Background: Following the introduction of an algorithm aiming to maximise life-years gained from liver transplantation in the UK (the transplant benefit score [TBS]), donor livers were redirected from younger to older patients, mortality rate equalised across the age range and short-term waiting list mortality reduced. Understanding age-related prioritisation has been challenging, especially for younger patients and clinicians allocating non-TBS-directed livers. We aimed to assess age-related prioritisation within the TBS algorithm by modelling liver transplantation prioritisation based on data from a UK transplant unit and comparing these data with other regions.
Methods: In this population-based modelling study, serum parameters and age at liver transplantation assessment of patients attending the Scottish Liver Transplant Unit, Edinburgh, UK, between December, 2002, and November, 2023, were combined with representative synthetic data to model TBS survival predictions, which were compared according to age group (25-49 years vs ≥60 years), chronic liver disease severity, and disease cause. Models for end-stage liver disease (UKELD [UK], MELD [Eurotransplant region], and MELD 3.0 [USA]) were used as validated comparators of liver disease severity.
Findings: Of 2093 patients with chronic liver disease, 1808 (86%) had complete datasets and liver disease parameters consistent with eligibility for the liver transplant waiting list in the UK (UKELD ≥49). Disease severity as assessed by UKELD, MELD, and MELD 3.0 did not differ by age (median UKELD scores of 56 for patients aged ≥60 years vs 56 for patients aged 25-49 years; MELD scores of 16 vs 16; and MELD 3.0 scores of 18 vs 18). TBS increased with advancing age (R=0·45, p<0·0001). TBS predicted that transplantation in patients aged 60 years or older would provide a two-fold greater net benefit at 5 years than in patients aged 25-49 years (median TBS 1317 [IQR 1116-1436] in older patients vs 706 [411-1095] in younger patients; p<0·0001). Older patients were predicted to have shorter survival without transplantation than younger patients (263 days [IQR 144-473] in older patients vs 861 days [448-1164] in younger patients; p<0·0001) but similar survival after transplantation (1599 days [1563-1628] vs 1573 days [1525-1614]; p<0·0001). Older patients could reach a TBS for which a liver offer was likely below minimum criteria for transplantation (UKELD <49), whereas many younger patients were required to have high-urgent disease (UKELD >60). US and Eurotransplant programmes did not prioritise according to age.
Interpretation: The UK liver allocation algorithm prioritises older patients for transplantation by predicting that advancing age increases the benefit from liver transplantation. Restricted follow-up and biases in waiting list data might limit the accuracy of these benefit predictions. Measures beyond overall waiting list mortality are required to fully capture the benefits of liver transplantation.
Funding: None.
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http://dx.doi.org/10.1016/S2666-7568(24)00044-8 | DOI Listing |
Eur J Med Res
December 2024
Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, No. 7 Weiwu, Zhengzhou, 450003, Henan, China.
Background: Nicastrin, a subunit of the γ-secretase complex, is encoded by the NCSTN gene and regulates notch signaling, it is involved in the pathogenesis of hidradenitis suppurativa (HS), Alzheimer disease (AD), and liver cancer. However, the animal models for studying HS are relatively scarce.
Methods: CRISPR/Cas-mediated genetic engineering was used to generate targeted knockout offspring mice (C57BL/6J).
J Health Popul Nutr
December 2024
Gastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Nonalcoholic fatty liver disease (NAFLD) or metabolic dysfunction-associated steatotic liver disease (MASLD) is a significant global public health dilemma with wide-ranging social and economic implications. Diet and lifestyle modifications remain essential components of NAFLD management. The current study investigated the association between diet-related inflammation and NAFLD among 3110 Iranian adults participating in the Amol Cohort Study (AmolCS), employing the Structural Equation Modeling (SEM) approach.
View Article and Find Full Text PDFJ Nanobiotechnology
December 2024
Cancer Stem Cells and Fibroinflammatory Microenvironment Group, Instituto de Investigaciones Biomédicas (IIBm) Sols-Morreale CSIC-UAM, 28029, Madrid, Spain.
Background: Pancreatic ductal adenocarcinoma (PDAC) requires innovative therapeutic strategies to counteract its progression and metastatic potential. Since the majority of patients are diagnosed with advanced metastatic disease, treatment strategies targeting not only the primary tumor but also metastatic lesions are needed. Tumor-Associated Macrophages (TAMs) have emerged as central players, significantly influencing PDAC progression and metastasis.
View Article and Find Full Text PDFBiol Direct
December 2024
Department of Gastrointestinal Surgery, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214062, Jiangsu Province, China.
Background: Accumulating studies have focused on long noncoding RNAs (lncRNAs) because of their regulatory effects on multiple cancers. However, the biological functions and molecular mechanisms of lncRNAs in gastric cancer (GC) remain to be elucidated in depth.
Methods: Long intergenic nonprotein coding RNA 1094 (LINC01094), a differentially expressed lncRNA between GC tissues and adjacent normal tissues, was identified.
BMC Gastroenterol
December 2024
Shenzhen Hospital of Beijing University of Traditional Chinese Medicine (Long Gang), Shenzhen, Guangdong, China.
Background: This study aimed to investigate the association between Metabolic-dysfunction-associated steatotic liver disease(MASLD)and C-reactive protein/lymphocyte ratio (CLR).
Methods: MASLD was defined as a Controlled Attenuation Parameter (CAP ≥ 274dB/m) and CLR = C-reactive protein/lymphocyte. A multifactor linear regression model was used to test the relationship between MASLD and CLR.
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