Overall Survival Rates Become Similar Between Percutaneous Ablation and Hepatic Resection With Increasing Age Among Elderly Patients With Early Hepatocellular Carcinoma
Bibliographic record
Abstract
Background: This study aimed to investigate the efficacy and safety of percutaneous ablation versus hepatectomy in an elderly population with hepatocellular carcinoma (HCC). Methods: Retrospective data on patients aged ≥ 65 years with very-early/early stages of HCC (≤ 50 mm) were obtained from three centers in China. Inverse probability of treatment weighting analysis was performed after stratifying the patients by age (65 - 69, 70 - 74 and ≥ 75 years). Results: Of the 1,145 patients, 561 and 584 underwent resection and ablation, respectively. For patients aged 65 - 69 and 70 - 74 years, resection resulted in significantly better overall survival (OS) than ablation (age 65 - 69, P < 0.001, hazard ratio (HR) = 0.27; age 70 - 74, P = 0.012, HR = 0.64). However, in patients aged ≥ 75 years, resection and ablation resulted in a similar OS (P = 0.44, HR = 0.84). An interactive effect existed between treatment and age (effect of treatment on OS, age 65 - 69 as the reference, for age 70 - 74, P = 0.039; for age ≥ 75, P = 0.002). The HCC-related death rate was higher in patients aged 65 - 69, and the liver/other cause-related death rate was higher in patients aged > 69. Multivariate analyses showed that the type of treatment, number of tumors, α-fetoprotein level, serum albumin level and associated diabetes mellitus were independent factors associated with OS, but not hypertension or heart diseases. Conclusion: With increasing patient age, the treatment outcomes of ablation become similar to those of resection. A higher liver/other cause-related death rate in very elderly patients may shorten the life expectancy, which may lead to the same OS regardless of whether resection or ablation is chosen.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".