Outcomes of Geriatric Patients with Hepatocellular Carcinoma
Bibliographic record
Abstract
Background: The treatment modalities and outcomes of geriatric patients with hepatocellular carcinoma (HCC) remain controversial. This retrospective observational cohort study compared the outcomes of HCC between geriatric and younger patients. Methods: The medical records of patients with HCC managed between January 2001 and December 2017 were retrieved from the Chang Gung Memorial Hospital Research Database. Patients were stratified by age into two groups: a geriatric group (65−75 years) and a younger group (<65 years). The two groups were matched through 1:2 propensity score matching (PSM) according to sex, cardiovascular disease, cerebrovascular attack, diabetes mellitus, cirrhosis, hepatitis, and hypertension. Results: Of the 11,033 patients with HCC, 2147 patients aged 65−75 years and 4294 patients aged <65 years were identified after 1:2 PSM. The Kaplan−Meier model revealed that the HCC outcomes in patients older than 65 years were not significantly different after 3 years (p = 0.060). Consistent results were also obtained when the laboratory data associated with HCC incidence were included in the Fine−Gray competing risk model after 1:2 PSM (p = 0.1695). The major risk factors for HCC survival were systemic immune-inflammation index (SII) ≥ 610 × 109 cells/L, advanced tumor stage, and model for end-stage liver disease (MELD) score, etc. Conclusion: Age was not an independent factor for mortality in patients with HCC in the first 3 years. Geriatric patients with HCC should be as aggressively managed as younger patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".