Nonsurgical Management of Advanced Hepatocellular Carcinoma: A Clinical Practice Guideline
Bibliographic record
Abstract
Background: Practice guidelines based on a systematic review of the literature regarding the nonsurgical management of hepatocellular carcinoma (hcc) in North America are lacking. Resection and transplantation are the foundations for cure of hcc; however, most patients are diagnosed at an advanced stage, precluding those curative treatments. A number of local or regional therapies are used and are followed by systemic therapy for advanced or progressive disease. Other treatments are available, but their efficacy, compared with those standards, is not well known. Methods: First, systematic review questions were developed. Literature searches of the medline, embase, and Cochrane library databases (January 2000 to July 2018 or January 2005 to July 2018 depending on the question) were conducted; in addition, abstracts from the 2018 annual meeting of the American Society of Clinical Oncology were reviewed. A practice guideline was drafted that was then scrutinized by internal and external reviewers. Results: Seventy-seven studies were included in the guideline: no guidelines, two systematic reviews, and seventy-five primary studies published in full (including one pooled analysis). Five recommendations were developed. Conclusions: There is no evidence for or against the use of local or regional interventions other than transarterial chemoembolization for the treatment of intermediate- or advanced-stage hcc. Furthermore, there is no evidence to support the addition of sorafenib to any local or regional therapy. Sorafenib or lenvatinib are recommended for first-line systemic treatment of intermediate-stage hcc. Regorafenib or cabozantinib provide survival benefits when given as second-line treatment. Antiviral treatment is recommended in individuals with advanced hcc who are positive for the hepatitis B surface antigen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.059 | 0.136 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".