Survival Benefit of Surgical Treatment for Elderly Patients with Intrahepatic Cholangiocarcinoma: A Retrospective Cohort Study in the SEER Database by Propensity Score Matching Analysis
Bibliographic record
Abstract
Despite a rising trend in intrahepatic cholangiocarcinoma (ICC) incidence in the elderly population worldwide, the benefit of surgery for those patients is still controversial. Data from 811 elderly patients diagnosed with non-metastatic ICC were obtained from the US surveillance, epidemiology, and end results (SEER) program database. Propensity score matched (PSM) was conducted for the better balance of baseline. The associations between tumor characteristics and surgery with overall survival (OS) and cancer specific survival (CSS) were estimated using hazard ratios (HR) and 95% confidence intervals (CI). The results showed that ICC patients above 60 years old taking surgery had better OS (hazard ratio [HR], 0.258; 95% CI, 0.205-0.324) and CSS (hazard ratio [HR], 0.239; 95% CI, 0.188-0.303) than patients without surgery. Similar trends in patients above 65 years old, above 70 years old, above 75 years old, and above 80 years old were observed, separately. This benefit was also showed in lymph node-negative (N0) and lymph node-positive (N1) subgroups and N0 patients are more likely to take an advantage from surgery than N1 patients. The different outcomes between surgery and non-surgery suggest that surgical treatment may be recommended for elderly ICC if the tumor is resectable to ensure optimal treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".