Background: Sorafenib is the gold standard therapy for the advanced hepatocellular carcinoma (HCC). No scoring/staging is universally accepted to predict the survival of these patients.

Aims: To evaluate the accuracy of the available prognostic models for HCC to predict the survival of advanced HCC patients treated with Sorafenib included in the Italian Liver Cancer (ITA.LI.CA.) multicenter cohort.

Methods: The performance of several prognostic scores was assessed through a Cox regression-model evaluating the C-index and the Akaike Information Criterion (AIC).

Results: Data of 1129 patients were analyzed. The mean age of patients was 61.6 years, and 80.8% were male. During a median follow-up period of 13 months, 789 patients died. The median period of Sorafenib administration was 4 months. All the prognostic scores were able to predict the overall survival (p<0.001) at univariate analysis, except the Albumin-Bilirubin score. The Italian Liver Cancer score (CLIP) yielded the highest accuracy (C-index 0.604, AIC 9898), followed by the ITA.LI.CA. prognostic score (C-index 0.599, AIC 9915).

Conclusions: The CLIP score had the highest accuracy in predicting the overall survival of HCC patients treated with Sorafenib, although its performance remained poor. Further studies are needed to refine the current ability to predict the outcome of HCC patients undergoing Sorafenib.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.dld.2020.12.001DOI Listing

Publication Analysis

Top Keywords

predict survival
12
prognostic models
8
advanced hepatocellular
8
hepatocellular carcinoma
8
prognostic scores
8
patients
5
comparison prognostic
4
models advanced
4
carcinoma patients
4
patients undergoing
4

Similar Publications

Background: Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.

Aim: In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).

Methods And Results: Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes.

View Article and Find Full Text PDF

COLOFIT: Development and Internal-External Validation of Models Using Age, Sex, Faecal Immunochemical and Blood Tests to Optimise Diagnosis of Colorectal Cancer in Symptomatic Patients.

Aliment Pharmacol Ther

January 2025

Gastrointestinal and Liver Theme, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust and the University of Nottingham, School of Medicine, Queen's Medical Centre, Nottingham, UK.

Background: Colorectal cancer (CRC) is the third most common cancer in the United Kingdom and the second largest cause of cancer death.

Aim: To develop and validate a model using available information at the time of faecal immunochemical testing (FIT) in primary care to improve selection of symptomatic patients for CRC investigations.

Methods: We included all adults (≥ 18 years) referred to Nottingham University Hospitals NHS Trust between 2018 and 2022 with symptoms of suspected CRC who had a FIT.

View Article and Find Full Text PDF

Incidence of fall-from-height injuries and predictive factors for severity.

J Osteopath Med

January 2025

McAllen Department of Trauma, South Texas Health System, McAllen, TX, USA.

Context: The injuries caused by falls-from-height (FFH) are a significant public health concern. FFH is one of the most common causes of polytrauma. The injuries persist to be significant adverse events and a challenge regarding injury severity assessment to identify patients at high risk upon admission.

View Article and Find Full Text PDF

Patients with cancer expect prolonged life (overall survival, OS) or better life (quality of life, QOL) from cancer treatments. However, majority of new cancer drugs are now being approved not based on improved OS or QOL, but based on surrogate endpoints such as tumor shrinkage or delayed tumor progression. These surrogate endpoints, including their validity as a proxy for overall survival, differ based on disease settings and lines of treatment but in general, most surrogate measures have weak correlation with outcomes that matter to patients.

View Article and Find Full Text PDF

Objectives: Diabetic ketoacidosis (DKA) is an acute complication in patients who suffer from diabetes mellitus that could progress to fatal outcomes if not identified and treated promptly. DKA poses a substantial impact on healthcare systems. In this study, we aim to identify the predictors of prolonged hospital length of stay (LOS) and mortality in patients admitted with DKA.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!