PET4 Response As an Independent Predictor of Long-Term Outcomes in ECHELON2 (A+CHP Vs. CHOP) in CD30+PTCL
Notice bibliographique
Résumé
Background: Peripheral T-cell lymphomas (PTCLs) are uncommon, heterogeneous, and often aggressive subtypes of lymphoma characterized by a high risk of progression even after combination chemotherapy. The phase III, ECHELON-2 trial showed that the combination of brentuximab vedotin with chemotherapy (A+CHP) in patients (pts) with CD30-positive PTCLs improved progression-free survival (PFS) and overall survival (OS) compared to CHOP. In PTCL, positron emission tomography (PET) is a valuable way to assess disease burden and stage at the time of diagnosis and evaluate treatment response. Prior retrospective studies have shown that interim and end of treatment PET may predict outcomes; however, there are no prospective studies confirming their predictive value. In the ECHELON-2 study, PET4 outcomes were prospectively collected, and the objective of this exploratory analysis is to investigate the potential for interim PET scans to predict treatment response and long-term outcomes. Objective: To evaluate the role of interim 18F-FDG PET imaging (PET4) in predicting end of treatment (EOT) response, progression free survival (PFS), and overall survival (OS) in pts (pts) with CD30+PTCL treated with A+CHP or CHOP in the ECHELON-2 trial. Methods: The ECHELON-2 trial included prospective 18F-FDG PET scans and assessment of treatment response including long-term PFS per investigator and OS. PET4 status was based on Deauville score by Independent Review Facility (IRF) assessment using scans at the cycle 4 response assessment. Deauville scores 1-3 are considered negative (PET4neg) and 4-5 positive (PET4pos). EOT response is the best response after completion of study treatment and prior to long term follow up per Cheson 2007 by IRF assessment. Kaplan-Meier methods were used to estimate PFS and OS; p-values are based on stratified log-rank tests. All analyses are exploratory, and p-values are descriptive. Results: In this study, 452 pts were included, with 226 randomized to the A+CHP treatment arm and 226 to the CHOP treatment arm; median follow up was 66.8 months (range 0-90). Of randomized pts, 32 pts in the A+CHP arm and 41 pts in the CHOP arm were not evaluable for PET4. The overall results showed that the PET4neg evaluable subgroup had a higher proportion of pts achieving complete responses (CR) than PET4pos (80% vs. 9%) at EOT (Table 1). In pts assessed for PET4, pts who were PET4neg had improved PFS and OS in both the A+CHP and CHOP treatment arms (Figure 1). For A+CHP pts, those who achieved PET4neg had an improved PFS [HR 0.36, CI-95 (0.19-0.66), p=0.0006] and OS [HR 0.38, CI-95 (0.18-0.78), p=0.0060] compared to those who were PET4pos. Similarly, pts in the CHOP arm who achieved PET4neg had an improved PFS [HR 0.26, CI-95 (0.17-0.41), p<0.0001] and OS [HR 0.24, CI-95 (0.14-0.41), p< 0.0001] compared to those who were PET4pos. Among pts with anaplastic large cell lymphoma (sALCL) (n=316), 19 pts in the A+CHP arm and 32 in the CHOP arm were not evaluable for PET4. The results in this subgroup show that 128/143 (90%) A+CHP pts who had PET4 assessments achieved PET4neg. These pts experienced improved PFS [HR 0.28, CI-95 (0.14-0.60), p=0.0004] and OS [HR 0.38, CI-95 (0.16-0.94), p 0.0292] compared to PET4pos pts. For CHOP pts who had PET4 assessments 98/122 (80%), achieved PET4neg; these pts experienced improved PFS [HR 0.31, CI-95 (0.12-0.55), p<0.0001] and improved OS [HR 0.25, CI-95 (0.12-0.25), p= 0.0002] compared to PET4pos pts. Conclusion: In an exploratory analysis of interim PET imaging as part of the ECHELON-2 study, PET4neg by Deauville was associated with improved PFS and OS in both the A+CHP and CHOP arms. Our findings support the use of PET4 response in PTCL as a predictor of outcomes in both the A+CHP and CHOP pts. These findings emphasize the potential of PET scans to enhance risk stratification, individualize therapy decisions, and improve pt outcomes in the management of PTCLs. Further analysis will be presented at the meeting.
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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».