Background/aim: We assessed suitable factors indicating newly developed lenvatinib (LEN) treatment for unresectable hepatocellular carcinoma (u-HCC) by investigating real-world clinical features of patients.
Materials/methods: One hundred fifty two u-HCC patients, who receive LEN treatment from March to December 2018, were enrolled. (Child-Pugh score [CPS] 5/6/7/8 = 76/61/13/2, modified albumin-bilirubin grade [mALBI] 1/2a/2b/3 = 53/35/60/4). Clinical features were evaluated retrospectively.
Results: Overall-response rate (ORR)/disease control rate (DCR) at 1 month after starting LEN were 38.7%/86.0%, respectively. Estimated median time to progression (TTP) was 7.0 months, while median survival time was not reached within the observation period. CPS (≥7) and past history of tyrosine-kinase inhibitor (TKI) were not significant prognostic factors. mALBI ≥2b was an only significant prognostic factor (HR 4.632, 95%CI 1.649-13.02, P = 0.004) in Cox-hazard multivariate analysis. In patients with Child-Pugh A, c-index/Akaike's information criterion (AIC) of prognostic predictive value of mALBI were superior to CPS (0.682/135.6 vs 0.652/138.7), while those of stopping LEN also showed that mALBI was better (0.575/447.3 vs 0.562/447.8). Additional analysis of patients with good mALBI (1/2a) revealed that time to stopping LEN was significantly shorter in those with the adverse event (AE) of appetite loss (any grade) than those without (P = 0.006) and body mass index (BMI) was also lower in patients with that AE (20.3 ± 3.0 vs 23.6 ± 4.0kg/m , P < 0.001), while patients with a hand-foot skin reaction (any grade) showed good ORR/DCR (59.1%/86.4%) and longer TTP as compared to patients without (P = 0.007).
Conclusion: Good hepatic function (mALBI 1/2a) is the best indication for LEN, while potential appetite loss in association with low BMI should be kept in mind in such cases.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6639201 | PMC |
http://dx.doi.org/10.1002/cam4.2241 | DOI Listing |
Postgrad Med J
January 2025
Department of Pediatric Metabolic Diseases, University of Health Sciences, Ankara Etlik City Hospital, Ankara 06170, Turkey.
Metabolism is the name given to all of the chemical reactions in the cell involving thousands of proteins, including enzymes, receptors, and transporters. Inborn errors of metabolism (IEM) are caused by defects in the production and breakdown of proteins, fats, and carbohydrates. Micro ribonucleic acids (miRNAs) are short non-coding RNA molecules, ⁓19-25 nucleotides long, hairpin-shaped, produced from DNA.
View Article and Find Full Text PDFCNS Neurosci Ther
January 2025
Qingshan Lake Science and Technology Innovation Center, Hangzhou Medical College, Hangzhou, China.
Background: Ischemic stroke is a prevalent and life-threatening cerebrovascular disease that is challenging to treat and associated with a poor prognosis. Astragaloside IV (AS-IV), a primary bioactive component of Astragali radix, has demonstrated neuroprotective benefits in previous studies. This study aimed to explore the mechanisms through which AS-IV may treat cerebral ischemia-reperfusion injury (CIRI).
View Article and Find Full Text PDFActa Radiol
January 2025
R Madhavan Nayar Center for Comprehensive Epilepsy Care, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India.
Background: The role of imaging in autoimmune encephalitis (AIE) remains unclear, and there are limited data on the utility of magnetic resonance imaging (MRI) to diagnose, treat, or prognosticate AIE.
Purpose: To evaluate whether MRI is a diagnostic and prognostic marker for AIE and assess its efficacy in distinguishing between various AIE subtypes.
Material And Methods: We analyzed data from 96 AIE patients from our prospective autoimmune registry.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFHum Reprod Open
November 2024
Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?
Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.
What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!