Systemic Therapy for Advanced Hepatocellular Carcinoma: ASCO Guideline
Bibliographic record
Abstract
PURPOSE: To develop an evidence-based clinical practice guideline to assist in clinical decision making for patients with advanced hepatocellular carcinoma (HCC). METHODS: ASCO convened an Expert Panel to conduct a systematic review of published phase III randomized controlled trials (2007-2020) on systemic therapy for advanced HCC and provide recommended care options for this patient population. RESULTS: Nine phase III randomized controlled trials met the inclusion criteria. RECOMMENDATIONS: Atezolizumab + bevacizumab (atezo + bev) may be offered as first-line treatment of most patients with advanced HCC, Child-Pugh class A liver disease, Eastern Cooperative Oncology Group Performance Status (ECOG PS) 0-1, and following management of esophageal varices, when present, according to institutional guidelines. Where there are contraindications to atezolizumab and/or bevacizumab, tyrosine kinase inhibitors sorafenib or lenvatinib may be offered as first-line treatment of patients with advanced HCC, Child-Pugh class A liver disease, and ECOG PS 0-1. Following first-line treatment with atezo + bev, and until better data are available, second-line therapy with a tyrosine kinase inhibitor may be recommended for appropriate candidates. Following first-line therapy with sorafenib or lenvatinib, second-line therapy options for appropriate candidates include cabozantinib, regorafenib for patients who previously tolerated sorafenib, or ramucirumab (for patients with α-fetoprotein ≥ 400 ng/mL), or atezo + bev where patients did not have access to this option as first-line therapy. Pembrolizumab or nivolumab are also reasonable options for appropriate patients following sorafenib or lenvatinib. Consideration of nivolumab + ipilimumab as an option for second-line therapy and third-line therapy is discussed. Further guidance on choosing between therapy options is included within the guideline. Additional information is available at www.asco.org/gastrointestinal-cancer-guidelines.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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 source (direct Gemma or distilled Codex), 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".