Safety of Combination TARE and SBRT in Hepatocellular Carcinoma: A Review of Literature & Single-Center Case Series
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer. At the time of diagnosis, many HCC patients are not candidates for surgical resection and are considered for other locoregional therapies, including transarterial radioembolization (TARE) and stereotactic body radiation therapy (SBRT). To date only a few studies have explored the safety and efficacy of combining TARE and SBRT. Therefore, we aimed to evaluate it. Patients who received both SBRT and TARE from 2016 to 2024 were retrospectively evaluated for treatment-related toxicity based on criteria for adverse events (CTCAE v4.0). Treatment response was evaluated by modified response evaluation criteria for solid tumors (m-RECIST). We identified 12 patients with median age of 66.5 (range: 40, 87) and median follow up of 12 months. The median time between TARE and SBRT was 6.5 months (range: 1.5 to 24). Following the second treatment, ALBI grade remined the same among all patients at 3-month post treatment compared to baseline. Baseline CP was A among all patients and remained unchanged during follow-up and no higher than grade 3 clinical or biochemical toxicity was seen. The objective response rate (ORR) among patients receiving treatment to the same lesion was 100%. The combination treatment was consistent with prior studies in which the combination of TARE and SBRT has been shown to have good local control with few cases of grade 3 toxicity. Our study demonstrates that treatment with TARE and SBRT was safe and effective among our small sample of patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".