Efficacy of radiofrequency ablation versus laparoscopic liver resection for hepatocellular carcinoma in China: a comprehensive meta-analysis.
Bibliographic record
Abstract
INTRODUCTION: Hepatocellular carcinoma (HCC) has been the second leading cause of cancer-related death in China. Radiofrequency ablation is a relatively novel treatment that may improve the treatment of HCC. AIM: To evaluate and compare the efficacy and safety of radiofrequency ablation (RFA) versus laparoscopic liver resection (LLR) in the treatment of HCC. MATERIAL AND METHODS: We searched for relevant published studies in English (PubMed, Cochrane Library, EMBASE) and in Chinese (CBM, CNKI and Wanfang) from their inception until September 23, 2019. The quality of included studies was evaluated by the Newcastle-Ottawa Scale. RESULTS: A total of 19 retrospective studies including 2038 patients were eligible for the meta-analysis. The results of the meta-analysis demonstrated that LLR was superior to RFA in terms of 3-year overall survival rate (OR = 0.62), 1 to 3-year disease-free survival rates (OR = 0.57; OR = 0.41, respectively) and local recurrence rates (OR = 2.71). CONCLUSIONS: The meta-analysis demonstrates that laparoscopic liver resection should be preferred in tumors of size 3-5 cm, while for < 3 cm the long term results are equal.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.042 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".