Effects of Serum Lipids on the Long-Term Prognosis of Ampullary Adenocarcinoma Patients after Curative Pancreatoduodenectomy
Bibliographic record
Abstract
Background: Serum lipids (SLs), the prominent indicators of lipid metabolism, produce an intricate impact on proliferation, invasion, and metastasis of cancer cells. However, the effects of serum lipids on the prognosis of ampullary adenocarcinoma (AC) have not been investigated. Methods: Patients with AC in the National Cancer Center of China between January 1998 and December 2020 were retrospectively reviewed. Survival analysis for overall survival (OS, Time from operation to death) and recurrence-free survival (RFS, Time from operation to first-time recurrence) was performed using Kaplan–Meier analysis and Cox proportional hazards models. Results: A total of 232 AC patients were enrolled into the study. SLs levels were significantly lower in patients with vascular invasion compared to those without (all p < 0.05). The 1-year, 3-year, and 5-year OS rates for AC patients were 86.1%, 64.1%, and 47.6% and 75.8%, 54.8%, and 46.5% for RFS. Biliary/pancreatic fistula (31.9%) and chemotherapy (81.4%) were the majority of postoperative complications and adjuvant therapy, respectively. According to Cox analysis, preoperative LDL-C was an independent prognostic factor for RFS (HR = 0.43, 95% CI: 0.21–0.85, p = 0.015), whereas no statistical significance existed in the analysis of HDL-C, TC, and TG. Conclusions: High levels of preoperative LDL-C is a significant predictor of prolonged prognosis in AC patients, which was also observed to be a protective factor to reduce vascular invasion.
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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 | 0.001 | 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".