Early predictive value of circulating biomarkers for sorafenib in advanced hepatocellular carcinoma
Bibliographic record
Abstract
INTRODUCTION: Sorafenib is currently the first-line therapeutic regimen for patients with advanced hepatocellular carcinoma (HCC). However, many patients did not experience any benefit and suffered extreme adverse events and heavy economic burden. Thus, the early identification of patients who are most likely to benefit from sorafenib is needed. AREAS COVERED: This review focused on the clinical application of circulating biomarkers (including conventional biomarkers, immune biomarkers, genetic biomarkers, and some novel biomarkers) in advanced HCC patients treated with sorafenib. An online search on PubMed, Web of Science, Embase, and Cochrane Library was conducted from the inception to 15 August 2021. Studies investigating the predictive or prognostic value of these biomarkers were included. EXPERT OPINION: The distinction of patients who may benefit from sorafenib treatment is of utmost importance. The predictive roles of circulating biomarkers could solve this problem. Many biomarkers can be obtained by liquid biopsy, which is a less or noninvasive approach. The short half-life of sorafenib could reflect the dynamic changes of tumor progression and monitor the treatment response. Circulating biomarkers obtained from liquid biopsy resulted as a promising assessment method in HCC, allowing for better treatment decisions in the near future. ABBREVIATIONS: Alpha-fetoprotein (AFP); American Association for the Study of Liver Diseases (AASLD); Angiopoietin (Ang); Barcelona Clinic Liver Cancer stage (BCLC); Circulating endothelial progenitor (CEP); Circulating free DNA (cfDNA); Complete response (CR); Des-γ-carboxy prothrombin (DCP); Endothelium-derived nitric oxide synthase (eNOS); Hepatocellular carcinoma (HCC); Hepatocyte growth factor (HGF); Hepatoma arterial-embolization prognosis score (HAP); High mobility group box 1 (HMgb1); Interferon-gamma (IFN-γ); Long non-coding RNA (lncRNAs); Micro RNAs (miRNAs); Monocyte-to-lymphocyte ratio (MLR); National Comprehensive Cancer Network (NCCN); Neutrophil-lymphocyte ratio (NLR); Newcastle-Ottawa Scale (NOS); Nitric oxide (NO); Overall survival (OS); Partial response (PR); Platelet-lymphocyte ratio (PLR); Prediction of survival in advanced sorafenib-treated HCC (PROSASH); Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA); Prognostic nutritional index (PNI); Progression-free survival (PFS); Progressive disease (PD); Randomized controlled trials (RCTs); Response Evaluation Criteria in Solid Tumors (RECIST); Single nucleotide polymorphisms (SNPs); Sorafenib advanced HCC prognosis score (SAP); Stable disease (SD); Time to progression (TTP); Transcatheter arterial chemoembolization (TACE); Vascular endothelial growth factor (VEGF).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".