Comparison of the efficacy and safety of selective internal radiotherapy and sorafenib alone or combined for hepatocellular carcinoma: a systematic review and Bayesian network meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Selective internal radiation therapy (SIRT) is a developing technique and its efficacy and modality of application in hepatocellular carcinoma (HCC) are still controversial. This network meta-analysis aims to determine whether the efficacy and safety of SIRT alone and in combination are superior to that of sorafenib. METHODS: Four databases (PubMed, Embase, Cochrane Library, and Web of Science) were searched before August 2022. Cochrane Randomized Trial Risk of Bias Assessment Tool and the Newcastle-Ottawa scale were used to assess the quality. The outcomes of interest included overall survival (OS), progression-free survival (PFS), and adverse events (AEs). RESULTS: A total of 9 eligible trials involving 1954 patients were included, and SIRT ranked first among the three treatment modalities in terms of both OS (probability, 52.3%) and PFS (probability, 68.6%). The combination of SIRT and sorafenib did not improve OS or PFS in patients with HCC. Although the combination of SIRT and sorafenib did not raise the risk of grade 3 or higher AEs, it may have introduced more AEs than either alone. CONCLUSIONS: SIRT alone was found to be superior to sorafenib and the combination of the two in improving OS or PFS in patients with non-surgical HCC, especially in patients with combined portal vein tumor thrombus. The AEs induced by SIRT were different from those of sorafenib, but the overall toxicity was manageable, the combination of the two may cause an increase in the types of AEs that occur.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it