Prognostic value of lymph node ratio in non-small-cell lung cancer: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: This meta-analysis aimed to investigate the prognostic value of lymph node ratio in non-small-cell lung cancer. METHODS: We searched systematically for eligible studies in PubMed, Web of Science, Medline (via Ovid) and Cochrane library through 6 November 2018. The primary outcome was overall survival. Disease-free survival and cancer-specific survival were considered as secondary outcomes. Hazard ratio with corresponding 95% confidence interval were pooled. Quality assessment of included studies was conducted. Subgroup analyses were performed based on N descriptors, types of tumor resection, types of lymphadenectomy and study areas. Sensitivity analysis and evaluation of publication bias were also performed. RESULTS: Altogether, 20 cohorts enrolling 76 929 patients were included. Mean Newcastle-Ottawa Scale was 7.65 ± 0.59, indicating the studies' quality was high. The overall result showed non-small-cell lung cancer patients with lower lymph node ratio was associated with better overall survival (HR: 1.946; 95% CI: 1.746-2.169; P < 0.001), disease-free survival (HR: 2.058; 95% CI: 1.717-2.467; P < 0.001) and cancer-specific survival (HR: 2.149; 95% CI: 1.864-2.477; P < 0.001). Subgroup analysis prompted types of lymphadenectomy and the station of positive lymph node have an important effect on the prognosis. No significant discovery was found in sensitivity analysis. CONCLUSION: Patients with lower lymph node ratio was associated with better survival, indicating that lymph node ratio may be a promising prognostic predictor in non-small-cell lung cancer. The type of lymphadenectomy, an adequate examined number and the removed stations should be considered for more accurate prognosis assessment.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| 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 | 0.001 | 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".