Abstract P6-06-12: Prognostic significance of pretreatment neutrophil/-lymphocyte ratio in breast cancer: A meta-analysis
Bibliographic record
Abstract
Abstract Background: There is an increasing body of evidence that the host inflammatory response plays an important prognostic role in cancer. High level of the neutrophil/lymphocyte ratio (NLR) has been associated with poor prognosis in many cancers. The association of NLR with survival in breast cancer and its different subtypes remains unclear. Methods: A literature review of electronic databases was conducted to identify studies exploring the prognostic role of NLR in breast cancer. Data were extracted from individual publications or estimated from associated figures. Where possible, data were included in a meta-analysis. The association of high NLR with other classical prognostic factors (e.g. tumor size, histological grade, nodal metastasis, and estrogen receptor or HER2/neu expression) was evaluated using the Mantel-Haenszel odds ratio (OR). Both univariable and multivariable analyses of NLR with overall survival (OS) were assessed using generic inverse variance. Subgroup analysis was conducted to assess the effect of different cut-offs to define high versus low NLR. Breast cancer-specific survival was assumed to be equivalent to OS if non-breast cancer deaths contributed to <5% of evaluable patients. Results: The analysis included a total of 5 retrospective studies comprising of 3,449, predominantly early-stage, breast cancer patients. Three studies defined high NLR based on the most discriminating cut-off evaluated by receiver operator characteristic (ROC) analysis, while two studies compared upper to lower quartiles for NLR. The mean age was 56.9 and there were no differences in age between those with high and low NLR (mean difference +1.54 years, 95% confidence intervals [CI] -0.17-3.24, P = 0.08). Compared with low NLR, patients with high NLR were more likely to have tumors larger than 2cm (OR 1.69, 95% CI 1.23-2.32, P = 0.001), nodal metastases (OR 1.65, 95% CI 1.21-2.23, P = 0.001) and HER2/neu overexpression or amplification (OR 1.77, 95% CI 1.20-2.62, P = 0.004). There were no differences in the proportion of tumors that were high grade (OR 1.27, 95% CI 0.90-1.79, P = 0.18) or estrogen receptor positive (OR 0.76, 95% CI 0.54-1.09, P = 0.13) between those with high and low NLR. High NLR showed an association with worse OS (univariable hazard ratio [HR] 3.42, 95% CI 2.75-4.24, P<0.001). This association was retained in multivariable analyses (HR 3.16, 95% CI 2.13-4.68, P<0.001). There was no difference in this association with worse survival when NLR was assessed based on a single cut-off or when compared between upper and lower quartiles (subgroup difference P = 0.68, table). Conclusion: High NLR is associated with various poor prognostic factors, but despite this appears to be an independent factor for worse survival from breast cancer. These findings may be explained by an adverse host response to cancer. SubgroupNumber of studiesHR for OS95% CIPCut-off determined by ROC analysis33.362.64-4.29<0.001Upper versus lower quartile23.872.08-7.23<0.001 Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-06-12.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.055 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".