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Enregistrement W4417016745 · doi:10.1182/blood-2025-7188

Radiotherapy consolidation post-autologous stem cell transplant in Relapsed/Refractory aggressive non-Hodgkin lymphoma improves progression-free and overall survival in patients with partial but not complete metabolic response pre-transplant

2025· article· en· W4417016745 sur OpenAlexaff
John S. Yi, Chathuri Abeyakoon, David Hodgson, Vanessa Murad, Ho‐Young Yhim, Meenakshi Jeeva, Inna Y. Gong, John Kuruvilla, Michael Crump, Anca Prica, Vishal Kukreti, Sita Bhella, Chloe Yang, Tomohiro Aoki, Danielle Rodin, Woodrow Wells, Nauman Malik, Ur Metser, Robert Kridel, Abi Vijenthira

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésAggressive lymphomaRadiation therapyProportional hazards modelLymphomaAutologous stem-cell transplantationChemotherapySalvage therapyStem cellCohortPrognostic variable

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Salvage chemotherapy followed by autologous stem cell transplant (ASCT) is a potentially curative procedure for patients with relapsed/refractory (R/R) aggressive non-Hodgkin lymphoma (NHL). To improve long-term outcomes, the International Lymphoma Radiation Oncology Group (ILROG) guidelines recommend the use of radiotherapy (RT) after ASCT for limited stage relapse, sites of bulk, and sites with partial metabolic response (PMR) prior to transplant. However, there are limited data supporting this recommendation in the PET era. Our study objective was to evaluate whether consolidative RT per the ILROG guidelines improves progression-free survival (PFS) and overall survival (OS), compared to patients not receiving consolidative RT. Methods: Retrospective single centre study of patients receiving ASCT between October 2014 and December 2024. Inclusion criteria: adults ≥18 years with histological diagnosis of aggressive NHL (B- or T-cell) who received salvage chemotherapy (anthracycline or platinum-based) with pre-ASCT PET demonstrating complete metabolic response (CMR, Lugano 2014 criteria) with limited stage disease or baseline bulk (≥5 cm), or PMR with one residual avid site. To prevent immortal time bias, we only included patients without progression ≥6 weeks following ASCT so they would have been eligible for RT. The exposure variable was consolidative RT. Outcomes included PFS and OS from ASCT. Survival probability and effect sizes were calculated using Kaplan-Meier method and cox regression. Sensitivity analyses were conducted including only patients without progression >90 days following ASCT, with a residual nodal mass ≥2 cm, and assessing the impact of post-ASCT metabolic response in patients with a post-ASCT PET within 90 days (PMR cohort only). A two-sided p-value of 0.05 was considered significant. Results: Out of 424 patients receiving ASCT, we included 172 (92 PMR (57 received RT), 80 CMR (11 received RT)). Median age was 60 years (IQR 49-66) with 38% female patients. In the PMR cohort, baseline characteristics (age, sex, T or B-cell origin, timing of relapse, stage, international prognostic index risk score, bulk, Deauville score) did not differ significantly between RT and non-RT patients. In the CMR cohort, patients receiving RT were younger compared to those who did not, but there were otherwise no differences in baseline characteristics. Median dose of RT was 35 Gy (IQR 30-36 Gy) over 20 fractions. Median follow-up was 688 days (IQR 330-1605). In the PMR cohort, patients receiving RT had significantly higher 2-year PFS (72% (95% CI 60-84) vs. 25% (95% CI 10-40), HR 0.19 (95% CI 0.11-0.35), p<0.0001) and OS (78% (95% CI 67-90) vs. 59% (95% CI 41-76), HR 0.32 (95% CI 0.15-0.65), p=0.002) than patients who did not. In the CMR cohort of patients with limited stage disease or bulk (>5 cm), there were no significant differences in 2-year PFS (74% (95% CI 43-100) vs. 66% (95% CI 54-77), HR 0.41 (95% CI 0.10-1.74), p=0.2) or OS (71% (95% CI 38-100) vs. 75% (95% CI 64-87), HR 0.61 (95% CI 0.14-2.65), p=0.5) between RT and non-RT patients. In subgroup analysis, a trend towards improved 2-year PFS was observed in patients receiving RT for limited stage relapse (N=8) (100% vs. 73% (95% CI 59-87), p=0.08), though this did not reach statistical significance. There was no difference in 2-year PFS for patients receiving RT for bulk in CMR (N=5) compared to those who did not (57% (95% CI 39-75) vs. 55% (95% CI 37-73), p=0.7). The primary outcome of PFS did not change in sensitivity analyses including only patients without progression >90 days following ASCT, with a residual nodal mass ≥2 cm, or considering post-ASCT metabolic response. In patients with PMR with disease relapse, the most common site of relapse was both in-field/out-of-field for patients receiving RT (35%), whereas for patients not receiving RT the most common sites were both in-field (37%) and in-field/out-of-field (37%). In patients with CMR with disease relapse, the most common site of relapse was out-of-field for patients receiving RT (100%), and in-field for patients not receiving RT (33%). Conclusion: Our data represent a sizable cohort of patients meeting ILROG guidelines for post-ASCT consolidation RT. RT consolidation appears to significantly improve PFS and OS in patients with PMR in one site. RT does not appear to benefit patients in CMR with limited stage or bulk, but analyses were limited by sample size and power.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,006
Tête enseignante GPT0,235
Écart entre enseignants0,228 · 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'étudeObservationnel
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
Publié2025
Routes d'admission1
Résumé présentoui

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