A Novel Prognostic Index in Patients with Resectable Esophageal Squamous Cell Carcinoma: Fibrinogen/Prealbumin ratio
Bibliographic record
Abstract
BACKGROUND: Fibrinogen (Fib) to albumin (ALB) fibrinogen-to-albumin ratio as a prognostic index for esophageal cancer has been confirmed. A novel prognostic index was initially proposed with fibrinogen to prealbumin ratio (FPR) in patients with resectable esophageal squamous cell carcinoma (ESCC). OBJECTIVE: The objective of the study was to study the prognostic role of the novel prognostic index (FPR) in patients with resectable ESCC without any neoadjuvant treatment. METHODS: In this retrospective study, a total of 372 resectable ESCC patients without any neoadjuvant treatment were included. The best cutoff values were selected by the receiver operating characteristic curves. Two Cox regression analyses with forward stepwise (one for categorical variables and the other for continuous variables) were used to evaluate the overall survival (OS) and cancer-specific survival (CSS). RESULTS: The best cutoff point was 0.014 for FPR. Patients with lower levels of FPR (≤0.014) had better CSS (50.7% vs. 18.0%, p < 0.001) and OS (48.0% vs. 17.6%, p < 0.001) than patients with higher levels of FPR (> 0.014). Multivariate Cox analyses (categorical and continuous) demonstrated that FPR was an independent prognostic factor in CSS (categorical: hazard ratio [HR]: 2.014, 95% confidence interval [CI]: 1.504-2.697, p < 0.001; continuous per 0.01: HR: 1.438, 95% CI: 1.154-1.793, p = 0.001) and OS (categorical: HR: 1.964, 95% CI: 1.475-2.617, p < 0.001; continuous per 0.01: HR: 1.429, 95% CI: 1.146-1.781, p = 0.002). CONCLUSIONS: Our study indicated that FPR served as an independent prognostic factor in patients with resectable ESCC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".