Effectiveness and safety of focused ultrasound ablation surgery compared with radiofrequency ablation in primary hepatocellular carcinoma treatment: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: The effectiveness and safety of focused ultrasound ablation surgery (FUAS) for primary hepatocellular carcinoma (HCC) treatment has not been fully evaluated. This study analyzed the effectiveness and safety of FUAS compared to radiofrequency ablation (RFA). METHODS: Studies published before November 1, 2020, in the following databases were analyzed: PubMed, Embase, Cochrane Library, Web of Science, Wanfang Data, CqVip, China National Knowledge Infrastructure (CNKI), and Chinese Biomedical (CBM) database. All publications were reviewed independently by two authors. Both randomized controlled trials (RCTs) and cohort studies examining the effectiveness and safety of FUAS and RFA were considered. RCTs and cohort studies' methodological quality were evaluated using the Cochrane collaboration tool and the Newcastle-Ottawa Scale, respectively. RESULTS: A total of 6,597 records were identified, from which 3 cohort studies were selected for quantitative synthesis. All studies had relatively high methodological quality. The meta-analysis indicated that FUAS and RFA had comparable 3-month overall survival (OS) rates [risk ratio (RR): 0.99, 95% confidence interval (CI): 0.86 to 1.14], 6-month OS rates (RR: 1.03, 95% CI: 0.82 to 1.29), and 1-year OS rates (RR: 0.96, 95% CI: 0.84 to 1.11). Also, individual studies reported that the tumor response (reflected by tumor response and tumor ablation rate) and posttreatment complications were comparable between patients treated with FUAS and patients treated with RFA. Due to the limited number of studies reporting tumor response and posttreatment complications, further meta-analyses could not be conducted. DISCUSSION: FUAS and RFA were comparable in terms of effectiveness and safety in the treatment of primary HCC. However, current evidence is limited, and more prospective RCTs are warranted to confirm these findings.
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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 | 0.023 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.068 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".