Stereotactic body radiation therapy for hepatocellular carcinoma: From infancy to ongoing maturity
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) accounts for 90% of liver tumours and is one of the leading causes of mortality. Cirrhosis due to viral hepatitis, alcohol or steatohepatitis is the major risk factor, while liver dysfunction due to cirrhosis is a deciding factor in its treatment. The treatment modalities for HCC include liver transplant, hepatectomy, radiofrequency ablation, transarterial chemoembolisation, transarterial radioembolisation, targeted therapy, immunotherapy, and radiation therapy. The role of radiation therapy has been refined with the increasing use of stereotactic body radiation therapy (SBRT). Trials over the past two decades have shown the efficacy and safety of SBRT in recurrent and definitive HCC, leading to its acceptance and adoption in some more recent guidelines. However, high quality level I evidence supporting its use is currently lacking. Smaller randomised trials of external beam radiation therapy suggest high efficacy of radiation therapy compared to other treatments for patients with unresectable HCC, and phase III trials comparing SBRT with other modalities are ongoing. In this review, we discuss the rationale for SBRT in HCC and present evidence on its efficacy, associated toxicity, and technological advances.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".