Long‐Term Survival and Prognostic Factors of Pulmonary Metastasectomy in Liver Cancer: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Abstract Background Lung is the most common extrahepatic metastatic organ of liver cancer. Surgical resection is a common local treatment for pulmonary metastasis. But the long‐term prognosis of pulmonary metastasectomy varies greatly due to the small sample size and different results of previous studies. Therefore, we conducted this meta‐analysis to evaluate the combined 5‐year overall survival (OS) rate and prognostic factors after pulmonary metastasectomy in liver cancer. Methods Key words such as liver cancer pulmonary metastasis and metastasectomy were retrieved firstly in PubMed, Cochrane Library, Embase and Chinese Wanfang databases. Eligible studies were identified by manual searches. Each included study should report 5‐year OS rate and/or prognostic factors of pulmonary metastasectomy. Newcastle–Ottawa Scale was used for quality assessment, and heterogeneity was estimated by I2. We calculated the combined 5‐year survival rates and determined the prognostic factors for OS by the hazard ratios (HR) and number of events. Results Seventeen cohort studies with a total of 513 patients were included in this meta‐analysis. The combined 5‐year survival rates after pulmonary metastasectomy were 33% [95% confidence interval (95% CI) 29–37%]. The poor prognostic factors were disease‐free interval (DFI) < 12 months (HR = 2.421 95% CI 1.384 4.236) and existence of cirrhosis (HR = 1.936 95% CI 1.031 3.636). Conclusion The 5‐year OS rate of patients with pulmonary metastasectomy after resection of primary liver cancer is 33%. DFI < 12 months and existence of cirrhosis are probably poor prognostic factors.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".