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Enregistrement W2713994360 · doi:10.1182/blood.v128.22.4651.4651

Autologous Transplantation As Consolidation for High Risk Aggressive T-Cell Non-Hodgkin's Lymphoma: A SWOG S9704 Intergroup Trial Subgroup Analysis

2016· article· en· W2713994360 sur OpenAlexaff
Patrick J. Stiff, Hongli Li, James R. Cook, Louis S. Constine, Stephen Couban, Douglas A. Stewart, Thomas C. Shea, Pierluigi Porcu, Jane N. Winter, Brad S. Kahl, Sonali M. Smith, Deborah Marcellus, Kevin Barton, Glenn Mills, Michael LeBlanc, Lisa M. Rimsza, Stephen J. Forman, John P. Leonard, Richard I. Fisher, Jonathan W. Friedberg

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensJuravinski HospitalDalhousie University
Organismes subventionnairesnon disponible
Mots-clésMedicineAutologous stem-cell transplantationInternal medicineAggressive lymphomaOncologyLymphomaTransplantationCHOPRandomized controlled trialInternational Prognostic IndexDiffuse large B-cell lymphomaRegimenRituximab

Résumé

récupéré en direct d'OpenAlex

Abstract Background: We recently clarified the use of consolidative autologous stem cell transplantation (ASCT) as first remission consolidation therapy for high grade diffuse aggressive T and B non-Hodgkin's lymphoma (NHL)in patients with high-intermediate (HI) or High (H) age adjusted IPI disease (Stiff et al, NEJM 369:1681). After receiving CHOP or R-CHOP for 5 cycles responding patients were randomized to either 3 more induction cycles or 1 cycle followed by an ASCT using either a BCNU or TBI based preparative regimen. We found a PFS but not OS advantage for those randomized to transplant and no differential treatment effect for those with T-NHL patients as compared to B-NHL in the initial analysis of this study. In light of Phase II data suggesting a value of early ASCT for T-NHL, a lack of randomized ASCT trials for T-NHL and the inferior prognosis for T-NHL as compared to B cell disease, we further evaluated this sub group, since a post hoc analysis of the entire trial did find a survival advantage for those with H IPI disease. This then provided a unique opportunity to evaluate the role of ASCT consolidation for T-cell NHL in the setting of a prospective randomized trial. Method: Among the 370 eligible B-NHL and T-NHL patients with HI/H IPI disease treated on this trial, 40 had a T-NHL phenotype and were the subject of this analysis. Individual patient files were re-reviewed and those randomized after the first 5 cycles of CHOP were further analyzed for stage, IPI group, histology (centrally reviewed), and response to induction and consolidation and updated survival outcome. Results: Of the 40 T-NHL patients enrolled on study, 28 (70%) were randomized after induction therapy, a similar ratio to the entire trial (68%). Twelve were not randomized; 1 was ineligible for study, and of the eligible 11, 9 were HI IPI and 8 had peripheral T cell (PTCL-NOS). These 11 were not randomized due to patient choice in 2, and all of the remaining 9 pts progressed early: 2 after C1; 3 after C3, 1 after C4, and 3 after C5. For the 28 randomized, their median age was 50 and 19 were males. Of the group, 21/28 had B symptoms at diagnosis, 14 had stage IV disease, and 18 and 10 were in the HI and H IPI groups respectively. Histologies included 11 with PTCL-NOS, 7 angioimmunoblastic and 10 anaplastic large cell NHL. At randomization 13 were to continue CHOP and 15, ASCT. Of the 15 assigned to ASCT, 3 did not undergo transplant (2-refusals, 1- unable to mobilize); 7 received the BCNU-etoposide-cyclophosphamide and 5 the TBI-etoposide-cyclophosphamide preparative regimen. The 5 year estimates of PFS and OS for the randomized ASCT vs CHOP only groups (intent to treat) were 40% vs 38% (p=0.56) and 40% vs 45% (p=0.98) respectively. We found no difference in outcome based on IPI group, histology or stage of disease. Interestingly, only 1/7 patients who received BCV as the ASCT preparative regimen are long term survivors vs 4/5 receiving the TBI-based regimen. Conclusions: We did not observe a PFS/OS advantage for those with high-risk T-NHL in first remission randomized to ASCT following CHOP induction vs CHOP alone in this retrospective analysis. In addition, the 30% early drop out rate before randomization due primarily to early progression strongly suggests that more optimal induction regimens need to be developed for this disease. While the numbers are small the finding that TBI based preparative regimens might be associated with a higher PFS is of interest and deserves further study. Support: NIH/NCI grants CA180888 and CA180819; Bristol-Myers Squibb. Contributions of Dr. Raymond R Tubbs, deceased, are gratefully acknowledged. Figure 1 Figure 1. Disclosures Porcu: miRagen: Other: Investigator in a clinical trial; celgene: Other: Investigator in a clinical trial; Millenium: Other: investigator in a clinical trial; Innate Pharma: Other: Investigator in a clinical trial. Winter:Pharmacyclics: Research Funding; Medivation: Other: Provision of investigational agent for clinical trial; Seattle Genetics: Research Funding; GSK: Research Funding. Kahl:This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award number: Research Funding. Smith:Juno: Consultancy; TGTX: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Genentech: Consultancy, Other: on a DSMB for two trials ; Gilead: Consultancy; Portola: Consultancy; Amgen: Other: Educational lecture to sales force; Pharmacyclics: Consultancy. Rimsza:NCI/NIH: Patents & Royalties: L.M. Rimsza is a co-inventor on a provisional patent, owned by the NCI of the NIH, using Nanostring technology for determining cell of origin in DLBCL.. Fisher:Gilead: Consultancy; Seattle Genetics: Consultancy; Johnson and Johnson: Consultancy. Friedberg:Bayer: Honoraria, Other: Data Safety Monitoring Board.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,029

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,005
Méta-épidémiologie (sens strict)0,0020,000
Méta-épidémiologie (sens large)0,0050,010
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,253
Écart entre enseignants0,246 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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