Prognostic Value of Pre-Treatment Prognostic Nutritional Index in Esophageal Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background Prognostic nutritional index, combining albumin and lymphocyte counts, which represents the nutritional and immune status, was considered as a effective predictor for the patient's prognosis after surgery. To comprehensively analyze the relative effectiveness of prognostic performance of pretreatment prognostic nutritional index in esophageal cancer, we performed this meta-analysis. Methods We performed a systemic search in PubMed, EMBASE, CNKI and Web of science. The hazard ratios (HRs) or odds ratios (ORs) with their corresponding 95% confidence intervals (CIs) were extracted to explore the correlation between PNI and the postoperative survival of patients with esophageal cancer, including overall survival(OS), recurrence-free survival(RFS) and postoperative complications. The Newcastle-Ottawa Scale(NOS) was applied to estimate the quality of the included studies. The Begg's test was applied to assess the publication bias. Result A total of 13 articles with 3543 patients, were included in our meta-analysis, and 9 studies reported OS in 2731 esophageal cancer patients. The pooled results of the 9 studies suggested that esophageal cancer patients with a low prognostic nutritional index would have a worse overall survival(HR=1.14 95% CI 0.99-1.31 P<0.05). The integrated results also indicated that the prognostic nutritional index was a negative predictor for RFS. Conclusion This meta-analysis indicated a high correlation between PNI and postoperative survival of esophageal cancer. Esophageal cancer patients with low PNI value tend to have worse overall survival(OS) and may be at a higher risk of esophageal cancer recurrence. However, more relevant researches are needed to confirm the association between PNI and postoperative complications of esophageal cancer. Keywords: Prognostic nutritional index, Esophageal cancer, Prognosis, Meta-analysis, Overall survival
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".