Outcome of Transplantation for Acute Leukemia in Down Syndrome
Notice bibliographique
Résumé
Abstract Abstract 1991 Children with Down syndrome (DS) have a 10-to 20-fold increased incidence of acute lymphoblastic (ALL) and acute myeloid leukemia (AML) compared to the overall pediatric population. Available data on HCT in children with DS are scarce, suggest unsatisfactory outcomes and are conflicting as far as causes of treatment failure are concerned. All but one case series identified treatment-related mortality (TRM) as the major barrier to success. To better understand factors associated with HCT-outcomes we studied 28 patients with DS-AML and 27 patients with DS-ALL, the largest cohort of DS patients with acute leukemia to date. All transplants occurred in 2000–2009. Transplantations occurred in second remission for 43% of patients with DS-AML and 52%, with DS-ALL. With a median follow-up of 3-years disease-free survival (DFS) was 14% for DS-AML and 24% for DS-ALL. Leukemia recurrence was the predominant cause of treatment failure in the current analysis, 61% for DS-AML and 54% for DS-ALL, both substantially higher than expected for pediatric non-DS AML or ALL. In the subset of patients with DS-AML, we conducted a matched pair analysis. Cases (DS-AML) were matched to non-DS AML controls for age, disease status, cytogenetic risk group, donor-source, donor-recipient HLA match and graft source. The results of multivariate analysis, adjusted for interval from diagnosis to transplantation are shown below. Relapse risk was significantly higher in DS-AML than non DS-AML (62% vs. 37%; p<0.001). TRM was also higher in patients with DS-AML compared to non DS-AML (24% vs. 15%, p=0.04). Consequently, 3-year DFS was significantly lower for DS-AML compared to non DS-AML (14% vs. 48%, p<0.001). The corresponding probabilities of overall survival (OS) were 21% and 52% (p<0.001). Interval from diagnosis to transplant was significantly associated with OS; transplantation that occurred within 12 months from diagnosis was associated with higher mortality (hazard ratio 1.90, p=0.03). Interval between diagnosis and transplantation was not significantly associated with relapse (hazard ratio 1.42, p=0.27) or TRM (hazard ratio 2.17, p=0.15). In conclusion, after adjusting for known risk factors, leukemic relapse and TRM contribute to treatment failure after HCT in the recent treatment era. Cooperative group trials appear warranted that improve the selection of HCT candidates, optimize transplant-conditioning regimen and explore novel therapeutic approaches to improve the depth of remission prior to HCT in these children. Table Hazard Ratio 95% confidence interval P-value Transplant-related mortality DS-AML vs. non DS-AML 2.52 (1.06–6.00) 0.04 Leukemia recurrence DS-AML vs. non DS-AML 2.84 (1.75–4.59) <0.001 Treatment failure (death or relapse; inverse of DFS) DS-AML vs. non DS-AML 2.75 (1.75–4.31) <0.001 Overall mortality DS-AML vs. non DS-AML 2.86 (1.77–4.64) <0.001 Disclosures: No relevant conflicts of interest to declare.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».