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Enregistrement W3034137463 · doi:10.1182/blood.v130.suppl_1.4156.4156

Treatment Outcomes in the Management of Lymphoblastic Lymphoma (LBL) in Adults: An Institutional Review

2017· article· en· W3034137463 sur OpenAlexaff
Rohan Kehar, Vishal Kukreti, Michael Crump, Melania Pintilie, John Kuruvilla

Notice bibliographique

RevueBlood · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Lymphoblastic Leukemia research
Établissements canadiensPrincess Margaret Cancer CentreUniversity of TorontoLondon Health Sciences Centre
Organismes subventionnairesnon disponible
Mots-clésLymphoblastic lymphomaLymphomaMedicineOncologyClinical endpointInternal medicineImmunologyRandomized controlled trial

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Lymphoblastic lymphoma (LBL) is a rare and aggressive form of Non-Hodgkin's Lymphoma (NHL) representing only 1-2% of overall cases. LBL consists of B-cell (B-LBL) and T-cell (T-LBL) variants with T-LBL accounting for 90% of adult cases. LBL is felt to represent the nodal disease equivalent to acute lymphoblastic leukemia (ALL). In fact, the WHO Classification of Tumors of Hematopoietic and Lymphoma Tissues classifies LBL and ALL as a single entity with variants based on genetic and molecular phenotype. As with many other centers, the Princess Margaret Cancer Centre has employed a similar treatment strategy for LBL as with ALL given their biological similarities. Methods We conducted a retrospective analysis of 43 patients at Princess Margaret Cancer Centre with LBL who initiated treatment between 1995 and 2015. Patients had a histologically confirmed diagnosis of Pre-T Lymphoblastic Lymphoma, Pre-B Lymphoblastic Lymphoma or Lymphoblastic Lymphoma NOS confirmed by a hematopathologist at the University Health Network. Patients were treated with a variety of regimens including dose intensive or paediatric ALL protocols and less dose-intensive (NHL) protocols. The primary endpoint was the rate of overall survival (OS) at 5 years. Survival times were calculated from chemotherapy start date to last follow-up date. Plots were created using Kaplan-Meier and Log Rank test was used to compare patient groups' survival experience. Secondary endpoints included the rates of complete remission (CR), progression-free survival (PFS) at 5 years and the frequency of treatment-related toxicities and their impact on OS and PFS. We hypothesized that age was likely an important factor in determining toxicity as well as treatment efficacy. Results A total of 43 patients with LBL were identified in our database. The median age was 33 with a range of 5-83 years and the male-to-female ratio was approximately 3:1. The majority of patients (88%) had T-LBL subtype and 24 patients (56%) were stage IV at presentation. With respect to chemotherapy regimen, 23 patients (53%) received Dana Farber, 11 patients (26%) received another ALL-type regimen, a pediatric protocol was given in 4 patients (9%) and 5 patients (12%) received a less-dose intensive (NHL) regimen. A complete response (CR) was seen in 29/39 (74%) of patients and a partial response (PR) seen in 7/39 (18%) of patients. Rates of overall survival (OS) and progression-free survival (PFS) at 5 years were non-significantly higher in patients treated with ALL protocols including the Dana Farber (DF) protocol (90% and 88% respectively) compared to less dose-intensive regimens (53% and 60% respectively). A statistically significant difference in OS and PFS in patients less than or equal to age 50 was seen compared to those greater than age 50. On the other hand, clinical stage, LDH level at diagnosis and ECOG performance status did not have prognostic significance. With respect to toxicity, 14 patients experienced a total of 24 toxicity events of interest including venous thromboembolism, hypersensitivity reactions, febrile neutropenia, ileus and other gastrointestinal complications. In those who received DF, 10/23 (43%) of patients experienced a toxicity compared to 4/20 (20%) of patients who received a regimen other than DF (p-value=0.12). Of note, toxicity had no impact on 5-year OS as 85% patients with a toxicity outcome survived at 5 years compared to 80% without a toxicity outcome (p-value=0.49). Conclusion ALL treatment protocols have higher rates of OS and PFS in patients with LBL compared to less dose-intensive protocols with no significant difference in toxicity. Given the balance of benefit (favorable OS, PFS and CR rate) with aggressive ALL protocols versus the risks of toxicity (higher rates which do not appear to negatively influence OS), we believe our data favors treatment with ALL regimens in younger adults with LBL. Future research on LBL should assess the treatment experience at other centers given the relative rarity of this disease as well as assess long-term efficacy and toxicity outcomes. Download : Download high-res image (171KB) Download : Download full-size image Disclosures Kukreti: Celgene: Honoraria; Amgen: Honoraria. Crump: Servier: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen Ortho: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kuruvilla: Roche: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Seattle Genetics: Consultancy, Honoraria; Hoffman LaRoche: Consultancy; Janssen: Consultancy; Gilead: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Research Funding; Roche: Research Funding; Celgene: Honoraria, Research Funding; Lundbeck: Honoraria; Merck: Honoraria.

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)0,007
score de la tête « metaresearch » (Gemma)0,018
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: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,036

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,018
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0030,005
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,025
Tête enseignante GPT0,321
Écart entre enseignants0,296 · 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
GenreSynthèse

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
Publié2017
Routes d'admission1
Résumé présentoui

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