Preoperative prognostic nutritional index predicts survival of patients with intrahepatic cholangiocarcinoma after curative resection
Bibliographic record
Abstract
BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy. We sought to examine the association between preoperative prognostic nutritional index (PNI) and long-term overall survival among patients with ICC who underwent curative-intent resection. METHODS: Patients who underwent hepatectomy for ICC between 1990 and 2015 were identified using an international multi-institutional database. Clinic-pathological characteristics and long-term outcomes of patients with PNI ≥ 40 and <40 were compared using univariable and multivariable analyses. RESULTS: Among 637 patients, 53 patients had PNI < 40 (8.3%) and 584 patients had PNI ≥ 40 (91.7%). While there was no difference between PNI groups with regard to tumor size (P = .87), patients with PNI < 40 were more likely to have multifocal disease (PNI < 40, n = 16, 30.2% vs PNI ≥ 40, n = 65, 11.1%; P < 0.001), poorly differentiated or undifferentiated ICC (PNI < 40, n = 13, 25.5% vs PNI ≥ 40, n = 75, 13.1%; P = 0.020) and T2/T3/T4 disease vs patients with PNI ≥ 40 (PNI < 40, n = 38, 71.7% vs PNI ≥ 40, n = 265, 45.4%; P < 0.001). Patients with PNI ≥ 40 had better OS vs patients with PNI < 40 (5-year OS: PNI ≥ 40: 47.5%, 95% CI, 42.2 to 52.6% vs PNI < 40: 24.6%, 95% CI, 12.1 to 39.6%; P < 0.001). On multivariable analysis, PNI < 40 remained associated with increase risk of death (HR, 1.71; 95% CI, 1.15 to 2.53; P = 0.008). CONCLUSION: A low preoperative PNI was associated with a more aggressive ICC phenotype. After controlling for these factors, PNI remained independently associated with a markedly worse prognosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".