Correlation of eTILs with recurrence free survival (RFS) in stage IIB-IIIA melanoma and use as biomarker for stratification for clinical trials.
Notice bibliographique
Résumé
9567 Background: Immunotherapy is approved for resected stage IIB-IIIC, but treatment of all patients, particularly those with IIB-IIIA disease, incurs unneeded expense and toxicity. Biomarkers are urgently needed for patient stratification. Time constraints in clinical trial design have led to the adoption of recurrence free survival (RFS) as a primary endpoint in adjuvant melanoma trials. Tumor infiltrating lymphocytes (TILs) are a well-established biomarker in primary melanoma, but quantification is subjective. Electronic TILs (eTILs) are a previously published automated digital pathology tool to quantify TILs. Methods: A retrospective cohort of 194 patients with Stage II-III melanoma from Roswell Park Comprehensive Cancer Center (RPCCC, n=133) and Geisinger Medical Center (GMC, n=61) were evaluated for eTILS by blinded investigators. Patients were included based on a search of dermatopathology databases and tissue availability. Digital images of diagnostic slides were analyzed using quPath, a publicly available software. Briefly, tumor areas were selected to include infiltrating lymphocytes with minimal adjacent stroma. Color variations in H&E images were standardized, and cell types quantified utilizing a machine learning algorithm. A previously published threshold of 16.6% eTILs, calculated as lymphocytes/tumor cells x 100, was used. Patients were staged using American Joint Committee on Cancer (AJCC) guidelines, version 8. Survival was assessed using Kaplan-Meier Curves and correlation of clinic-pathologic features with survival was tested using Cox Proportional Hazards Models. Results: Of 194 patients, 56 were stage IIA, 85 were IIB-IIIA, and 53 were IIIB-D. Median follow up was 47.5 months. 103 patients had eTILs >16.6% of whom 13 (12.6%) died and 84 had eTILS <16.6% of whom 23 (27.4%) died during follow-up. HR for death from melanoma within 5 years for the high eTIL group was 0.53 (CI 0.21-0.90, p=0.024). DSS was significantly longer in the high eTIL group than the low eTIL group (p=0.0095). Among 85 stage IIB-IIIA patients, local and distant recurrence data was available for the RPCCC cohort of 68 patients. 46 of these patients had high eTILs of whom 9(19.6%) recurred and 22 had low eTILS of whom 10 (45.95%) recurred. HR for recurrence within 5 years for the high eTIL group was 0.44 (CI0.23-0.83, p=0.012). RFS was significantly longer in the high TIL group (p=0.016) as was distant metastatic recurrent survival (p= 0.0063). eTIL score correlated with RFS in a univariable Cox model (p=0.033) and added to stage and depth in a multivariable Cox model (p=0.018). Conclusions: eTILs, readily evaluable at low cost using diagnostic slides, correlate with clinical outcome in a retrospective cohort of 194 patients. eTILS should be prospectively evaluated as a biomarker to stratify early-stage melanoma patients for adjuvant clinical trials.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».