ArticleBritish journal of cancer2019
Using prognostic and predictive clinical features to make personalised survival prediction in advanced hepatocellular carcinoma patients undergoing sorafenib treatment.
Article in British journal of cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Article
- Outcome prediction model for patients with unresectable hepatocellular carcinoma treated with targeted therapy.Scientific reports · 2025Article
- Deep Learning-Based Prediction of Post-treatment Survival in Hepatocellular Carcinoma Patients Using Pre-treatment CT Images and Clinical Data.Journal of imaging informatics in medicine · 2025Article
- Predictive value of biomarkers for lenvatinib in hepatocellular carcinoma.Therapeutic advances in medical oncology · 2025Review
- Tumor burden affects the progression pattern on the prognosis in patients treated with sorafenib.Frontiers in oncology · 2024Article
- Development of a Multivariate Prognostic Model for Lenvatinib Treatment in Hepatocellular Carcinoma.The oncologist · 2023Article
- Prognostic model for predicting outcome and guiding treatment decision for unresectable hepatocellular carcinoma treated with lenvatinib monotherapy or lenvatinib plus immunotherapy.Frontiers in immunology · 2023Article
- Circulating immune index predicting the prognosis of patients with hepatocellular carcinoma treated with lenvatinib and immunotherapy.Frontiers in oncology · 2023Article
- Prognostic significance of cachexia index in patients with advanced hepatocellular carcinoma treated with systemic chemotherapy.Scientific reports · 2022Article
- Neoadjuvant Therapy for Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2022Review
- Sorafenib is associated with a reduced rate of tumour growth and liver function deterioration in HCV-induced hepatocellular carcinoma.Journal of hepatology · 2021Article
- Treatment strategies for hepatocellular carcinoma with extrahepatic metastasis.World journal of clinical cases · 2021Review
- Review
- A Nomogram-Based Prognostic Model for Advanced Hepatocellular Carcinoma Patients Treated with Sorafenib: A Multicenter Study.Cancers · 2021Article
- Sequential Treatment of Sorafenib-Regorafenib Versus Sorafenib-Physician's Choice: A Propensity Score-Matched Analysis.Targeted oncology · 2021Article
- Effects of vitamin D level on survival in patients with hepatocellular carcinoma.Hepatology forum · 2020Article
- Sorafenib for Patients with Hepatocellular Carcinoma and Child-Pugh B Liver Cirrhosis: Lessons Learned from a Terminated Study.The oncologist · 2020Article
- The role of PNI to predict survival in advanced hepatocellular carcinoma treated with Sorafenib.PloS one · 2020Article
- Neoadjuvant therapy and immunotherapy strategies for hepatocellular carcinoma.American journal of cancer research · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundSorafenib is the current standard of care for patients with advanced hepatocellular carcinoma (aHCC) and has been shown to improve survival by about 3 months compared to placebo. However, survival varies widely from under three months to over two years. The aim of this study was to build a statistical model that allows personalised survival prediction following sorafenib treatment.
methodsWe had access to 1130 patients undergoing sorafenib treatment for aHCC as part of the control arm for two phase III randomised clinical trials (RCTs). A multivariable model was built that predicts survival based on baseline clinical features. The statistical approach permits both group-level risk stratification and individual-level survival prediction at any given time point. The model was calibrated, and its discrimination assessed through Harrell's c-index and Royston-Sauerbrei's R
resultsThe variables influencing overall survival were vascular invasion, age, ECOG score, AFP, albumin, creatinine, AST, extra-hepatic spread and aetiology. The model-predicted survival very similar to that observed. The Harrell's c-indices for training and validation sets were 0.72 and 0.70, respectively indicating good prediction.
conclusionsOur model ('PROSASH') predicts patient survival using baseline clinical features. However, it will require further validation in a routine clinical practice setting.
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