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Enregistrement W4389243340 · doi:10.1182/blood-2023-179333

<i>ATM</i> Germline Pathogenic Variants Affect Treatment Outcomes in Children with Acute Lymphoblastic Leukemia/Lymphoma and Ataxia Telangiectasia

2023· article· en· W4389243340 sur OpenAlexaff
Sarah Elitzur, Ruth Shiloh, Jan Loeffen, Agata Pastorczak, Masatoshi Takagi, Simon Bomken, André Baruchel, Stéphane Ducassou, Nizar Mahlaoui, Marion Strullu, Thomas Lehrnbecher, Kjeld Schmiegelow, Oussama Abla, L. Kh. Anderzhanova, Nira Arad‐Cohen, Itziar Astigarraga, Miriam Ben-Harosh, Francesco Ceppi, Nicole Bodmer, Triantafyllia Brozou, Luciano Dalla‐Pozza, Gabriele Escherich, Roula Farah, Amber Gibson, Henrik Hasle, Julieta Hoveyan, Elad Jacoby, Janez Jazbec, Alexandra Kolenová, Jelena Lazić, Luca Lo Nigro, Lane R. Miller, Vassilios Papadakis, Lucie Pecheux, Marta Pillon, Ifat Sarouk, Jan Starý, Eftichia Stiakaki, Sarah K. Tasian, Thai Hoa Tran, Marek Ussowicz, Anna Wakulińska, Joanna Zawitkowska, Dominique Stoppa‐Lyonnet, Malcolm Taylor, Yosef Shiloh, Shai Izraeli, Ronit Nirel, Véronique Minard‐Colin, Andishe Attarbaschi, Arndt Borkhardt

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueDNA Repair Mechanisms
Établissements canadiensCentre Hospitalier Universitaire Sainte-JustineUniversity of AlbertaStollery Children's HospitalHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésMedicineAtaxia-telangiectasiaOncologyCancerInternal medicineCohortIncidence (geometry)LymphomaImmunologyPediatricsBiology

Résumé

récupéré en direct d'OpenAlex

Introduction Ataxia telangiectasia (A-T) is a multisystem disorder caused by biallelic germline pathogenic variants (PV) in the ATM gene. An important feature of A-T is an increased predisposition to cancer with a reported incidence of 25%, primarily attributed to hematological malignancies. Patients with A-T and cancer are usually excluded from therapeutic clinical trials, limited information thus exists concerning their treatment outcomes and toxicity profiles and consequently, optimal management strategies are unclear and an unmet need. In this multinational study, we aimed to investigate the characteristics and outcomes of leukemia and lymphoma in a large cohort of children with A-T and to determine risk factors which impact treatment outcome in order to generate consensus and data-based prospective treatment recommendations. Methods This study of patients aged ≤25 years with A-T and hematological malignancies was conducted through the International BFM Study Group. Patient data were collected from medical records, including specific patient comorbidities. Each reported ATM PV identified in the cohort was classified as null (resulting in complete loss of ATM activity) or hypomorphic (allowing residual ATM activity) according to the expected functional activity of the ATM protein and published functional studies. Patients with reported ATM PV were then classified as Group A (two null PV) or Group B (at least one hypomorphic PV). Results We report 202 pediatric and adolescent/young adult patients with A-T and hematological malignancies from 25 countries. The cohort included 82 patients with ALL/LBL (41%), predominantly (85%) of T-cell lineage, 91 with mature B-cell lymphomas (45%), 21 with Hodgkin lymphoma (10%) and 8 with other hematological malignancies (4%) (Fig 1). Of 111 patients with classifiable germline ATM variants, 82 (74%) were classified as Group A and 29 as Group B (26%). The distribution of patients with Group A and Group B germline ATM PV differed considerably between tumor types with 44% of the patients with lymphoblastic leukemia/lymphoma classified as Group B vs. 5% of those with mature B cell lymphomas ( p<.001). In total, 185 patients (92%) treated with curative intent were included in the outcome analyses, 135 (73%) of whom were treated with attenuated therapy regimens. Four-year OS and EFS for the entire cohort were 50.8% (95% CI 43.6-59.1) and 47.9% (95% CI 40.8-56.2), respectively. Surprisingly, cure rates of patients with A-T and malignancy did not appear to improve significantly with therapy modernization over the last four decades with 4-year EFS rates of 41.6% (95% CI 26.6-65), 49.6% (95% CI 38.8-63.4) and 48.0% (95% CI 37.4-61.7) for those treated before 2000, between 2000-2009 and since 2010, respectively ( p=.54). The major cause of treatment failure for the entire cohort was treatment-related mortality (TRM) with a 4-year cumulative incidence of 32.8% (95% CI 19.5-32.4), followed by progressive cancer in 14.5% (95% CI 10-19.8) and second malignancy in 4.9% (95% CI 13.1-85.8) (Fig 2). We identified factors that were significantly associated with survival for this unique patient population. Older age had a significantly deleterious effect upon survival with 4-year EFS rates of 69.1% (95%CI 55.9-85.4), 45.3% (95% CI 34.5-59.4), 39.8% (95% CI 25-63.2), and 33.7% (95% CI 20.8-54.6) for children aged ≤5 years, 5-10 years, 10-15 years and ≥15 years, respectively ( p=.003). The type of germline ATM PV also had a significant impact: 4-year EFS for patients with Group B ATM PV was 78.7% (95% CI 63.7-97.2) vs. 39.4% (95% CI 29-53.3) for Group A ( p<.001). Group A PV were associated with an increased TRM (OR 9.3; 95% CI 1.6-180.1; p=.042) and decreased EFS (HR .371 95% CI 16.6-82.6; p=.009). Conclusions We demonstrate in this first comprehensive international study that leukemia and lymphoma in children with A-T are curable. While the standard treatment stratification system for patients with hematological malignancies without A-T focuses upon cancer relapse/progression as the main cause of treatment failure, TRM was the main cause of therapy failure in patients with A-T and was strongly associated with the underlying germline ATM variant type. This study further fulfills an unmet need for international collaboration and provides a platform for data-based guidelines for a novel risk stratification system and optimal therapy selection for this unique patient population.

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)0,002
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 enseignants0,005
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
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 Opus0,005
Tête enseignante GPT0,217
Écart entre enseignants0,212 · 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

Citations5
Publié2023
Routes d'admission1
Résumé présentoui

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