Outcome of Treatment for Relapsed Acute Lymphoblastic Leukemia in Children with Down Syndrome
Notice bibliographique
Résumé
Abstract Abstract 669 Background. Children with Down syndrome (DS) have a higher risk for developing not only acute lymphoblastic leukemia (ALL) but also significant adverse effects of chemotherapy compared to the overall pediatric population. Currently, it is unknown how children with DS, who develop a relapse of ALL, respond to treatment protocols that were optimized in the pediatric population without DS. We hypothesized that a concomitant diagnosis of DS is an independent prognostic factor of survival after treatment for relapsed ALL and that decreased tolerance of therapy impairs the success of relapse treatment in children with DS. Patients and Methods. The probability of event-free (EFS) and overall survival (OS) and the causes of treatment failure were determined for 51 children with DS and a matched cohort of 102 children without DS among 2736 children and young adults (up to 22 years of age) who were treated for relapsed ALL on a series of clinical trials conducted by the ALL-REZ-BFM Study Group between 1983 and 2012. Results. Among children with DS, who were enrolled on clinical trials of the ALL-REZ-BFM Study Group, ALL relapse more frequently exhibited favorable prognostic characteristics compared to the unmatched population of 2579 patients without DS. High risk forms of relapse were less frequent among children with DS (risk group S4, 10 vs. 28%, p<0.001) including relapse at a very early and early time point (35 vs. 56%, p<0.001). A higher proportion of relapse in DS involved the bone marrow (94 vs. 83% p<0.001). Transcripts of ETV6-RUNX1 or BCR-ABL1 were detected in none of the cases of relapsed ALL in DS compared to 20% (231/895, p<0.001) and 6% (83/1379, p=0.02) of cases in the population without DS. Treatment for relapsed ALL in children with DS less frequently included irradiation (of the central nervous system or total body) and hematopoietic stem cell transplantation compared to the matched non-DS group (28 vs. 70%, p<0.001, and 15 vs. 40%, p=0.002), respectively. Despite the apparent favorable risk profile, EFS and OS were lower in children with DS than the matched control group without DS (EFS 16 ± 08% vs. 39 ± 06%, p=0.005; OS 17 ± 08% vs. 48 ± 06%, p<0.001). Fatal adverse events of treatment developed more frequently in children with DS than the control group (36 ± 07% vs. 9 ± 03%, p<0.001). In contrast, the cumulative incidence of a subsequent relapse was similar in both groups (32 ± 07%, DS vs. 36 ± 05%, non-DS, p=0.373). The proportion of children with DS registered on clinical trials for relapsed ALL after frontline treatment on ALL-BFM trials showed an increase over time (from 1 registered vs. 1 non registered patient in ALL-BFM 81 to 18 registered vs. 8 non registered patients in ALL-BFM 2000). Furthermore, the proportion of patients with high risk relapse features (S4 group) and DS increased from 5 to 15%. During the more recent study period (2000–2012) EFS and OS were no longer significantly different in children with and without DS (EFS 30 ± 09% vs. 35 ± 09%, p=0.403; OS 30 ± 11% vs. 51 ± 08%, p=0.158). DS was an independent prognostic factor of outcome after relapse of ALL in multivariate analysis. Conclusion. A higher rate of induction deaths and treatment-related mortality was the main barrier to successful outcomes of relapse therapy in children with DS whereas relapse rates were not different from patients without DS. An increased representation of children with DS including those with high risk features in recent time suggests that access to clinical trials for relapsed ALL has been successfully broadened for children with DS. Specific optimization of treatment modifications and supportive care have improved survival in children with DS and are suggested to further decrease the number of fatal treatment-related events during relapse therapy in this group. Disclosures: No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».