Alemtuzumab Added to CHOP for Treatment of Peripheral T-Cell Lymphoma (PTCL) in Previously Untreated Young and Elderly Patients: Pooled Analysis of the International ACT-1/2 Phase III Trials
Notice bibliographique
Résumé
Abstract Background: Standard treatment in PTCL pts is unsatisfactory due to a high rate of early progression. Alemtuzumab (A), a monoclonal anti CD52 antibody, has demonstrated efficacy in relapsed PTCL pts. The results of the final analyses of the ACT-1 phase III and the ACT-2 phase III trial, comparing standard CHOP to A-CHOP showed higher response rates, but did not yield significant differences in EFS, PFS and OS in both previously untreated young and elderly patients, but the planned sample sizes could not be reached due to low recruitment. We undertook a planned pooled analysis of both ACT trials comparing CHOP with A-CHOP to increase statistical power. Patients and Methods: Between 2007 and 2013, 252 pts from Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Norway, Poland, Portugal, Sweden and The Netherlands were randomized to receive either 6 cycles CHOP or A-CHOP at 14 day intervals. The planned pooled analysis was performed to compare patient outcome adding A to CHOP with patients treated with CHOP alone. Primary endpoint within ACT-1 and ACT-2 trial was the 3 years event free survival (EFS), secondary endpoints were progression free survival (PFS) and overall survival (OS). EFS is defined as the time from randomization to disease progression, start of salvage treatment, additional (unplanned) treatments, relapse, or death of any cause. Results: 252 pts were randomized (ACT-1: 136; ACT-2: 116). Five patients received no study treatment; therefore, 247 pts were analyzed (CHOP: 124; A-CHOP: 123). Median age was 61 years. 62% were male. Histologies were 33% AITL, 34% PTCL NOS, 33% other subtypes. In the pooled data set, the two treatment groups were comparable. Infections grade ≥3 occurred more often in patients treated with Alemtuzumab (A-CHOP: 55% [95% CI: 45% - 64%] vs. CHOP 23% [16% - 32%]; p<0.001). Complete remissions were achieved in 56% [47% - 65%] of A-CHOP and 43% [34% - 52%] of CHOP pts (p=0.036). However, EFS (A-CHOP at 3 yrs: 32% [23% - 40%] vs. CHOP 25% [17% - 33%]; p=0.159), PFS (33% [25% - 42%] vs. 27% [19% - 35%]; p=0.220) and OS (46% [37% - 55%] vs. 53% [44% - 62%]; p=0.332) showed no significant differences. Multivariate analyses, adjusted for IPI factors, bulky disease and gender, confirmed these results (hazard ratio HREFS: 0.8 ([95% CI: 0.6 - 1.1]; p=0.196), HRPFS: 0.8 ([95% CI: 0.6 - 1.1]; p=0.246), HROS: 1.2 ([95% CI: 0.8 - 1.6]; p=0.370). Male gender (HR 2.5), ECOG > 1 (HR 2.1) and bulky disease (HR 2.1) were the most prominent unfavorable risk factors for EFS. With the sample size of 247 pts the power for detecting the planned EFS difference of 15% was 74%. Conclusion: Adding Alemtuzumab to CHOP increased the rate of CR in PTCL patients, albeit at the costs of higher treatment related toxicity. Addition of Alemtuzumab did not improve EFS, PFS, or OS. Female gender is associated with a significantly better prognosis. This is the largest prospective dataset collected for PTCL. Supported by Federal Ministry of Research BMBF FKZ 01KG0705 and unrestricted research grants by Genzyme-Sanofi and AMGEN Disclosures No relevant conflicts of interest to declare.
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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 | 0,017 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,009 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».