Abstract P6-06-12: Prognostic significance of pretreatment neutrophil/-lymphocyte ratio in breast cancer: A meta-analysis
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,015 | 0,055 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».