Correlation of urinary comprehensive genomic profile with risk of recurrence of BCG-unresponsive non-muscle invasive bladder cancer treated with atezolizumab in SWOG S1605.
Notice bibliographique
Résumé
529 Background: Radical cystectomy is recommended for patients with BCG-unresponsive (BU) non-muscle invasive bladder cancer (NMIBC) due to high risk of progression. Improved methods for assessing these risks would greatly facilitate the potential for bladder preservation. Here, we tested the capacity of the urinary comprehensive genomic profile (uCGP) to predict event-free survival (EFS) in patients with BU-NMIBC treated with atezolizumab in the single arm phase 2 trial SWOG S1605. Methods: Urine was collected from patients with BU NMIBC (CIS, Ta, T1) treated with at least one dose of intravenous atezolizumab at baseline and before the 5th cycle of therapy (3 months). The uCGP was assessed using UroAmp (Convergent Genomics). Risk scores for recurrence at baseline and at 3 months were calculated by a prespecified machine learning algorithm incorporating alterations in 60 genes and low pass whole genome sequencing, and categorized as high versus low. Molecular response was classified based on change in uCGP between the two time points. Risk scores and molecular response were submitted to SWOG for clinical correlation with EFS using a Cox model, adjusting for CIS status. Time to event was calculated from date of study entry (baseline risk) or from the 2nd collection time (3-month risk) to first high grade (HG) recurrence or persistent CIS at 3 months. Death unrelated to bladder cancer and patients last known to be alive without HG recurrence were censored at date of last visit. Results: Samples were provided at baseline in 89 patients and before the 5th cycle in 77; 68 had both samples available for paired analysis. The risk score at baseline was classified as high in 69% of samples (73% for CIS ±Ta/T1 and 62% for Ta/T1). At 12 and 18 months the EFS probabilities were 26% and 23% for high-risk and 67% and 51% for low-risk patients, respectively, with a HR of 2.82 (95% CI: 1.58, 5.03; p<0.001). The risk score at the 3-month timepoint was classified as high in 81% of samples, and the EFS probabilities at 12 and 18 months after urine collection were 26% and 22% for high-risk and 80% and 72% for low-risk patients, respectively, with a HR of 3.39 (95% CI: 1.41, 8.13; p<0.006). Molecular response to treatment was classified as complete (CR) in 8%, partial (PR) in 14%, stable (SD) in 25% and progression (PD) in 46%, with 7% having no detectable genomic abnormalities at both time points. Clinical recurrence was observed by 18 months in 0/6 patients with CR, 7/9 (78%) with PR, 11/14 (79%) with SD and 25/33 (76%) with PD by genomic profile. Conclusions: This study suggests that uCGP at baseline and after 4 cycles of treatment can identify genomic patterns associated with an increased risk of HG persistence, recurrence or progression in BU NMIBC treated with immune checkpoint inhibition. Future studies will determine if this can be used to guide early treatment intensification.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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) | 0,001 | 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 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 ».