Disease Risk Index Predicts Relapse in Children Undergoing Allogeneic Hematopoietic Cell Transplantation (HCT)
Notice bibliographique
Résumé
Relapse is most common cause of death after HCT. However, given the heterogeneity of diseases and disease states among patients (pts), risk for relapse is often difficult to manage in clinical trials when survival is the endpoint. The Disease Risk Index (DRI) predicts overall survival (OS) based on pre-HCT disease characteristics such as type of disease, remission status, and cytogenetic abnormalities and can be used to group heterogeneous diseases into 4 risk strata: very high risk [VHR, 1% of pts], high risk [HR, 23%], intermediate risk [IR, 64%], and low risk [LR, 12%] (Armand, Blood, 2014). OS for each of these strata is distinctly different. The DRI has been validated for adults, but not for children. Furthermore, the DRI cannot be calculated for some pediatric diseases like juvenile myelomonocytic leukemia (JMML). To determine its validity for children we calculated the DRI for 280 pediatric pts transplanted between 2008 and 2018 at Mount Sinai Acute GVHD International Consortium centers. The median age was 8.9 years (range, 0.4 - 17). The most common indications for HCT were ALL (51%), AML (31%), MDS (10%), and JMML (4%). Donors were adult unrelated donors (48%), unrelated cord blood (20%), haploidentical donors (17%), and matched siblings (15%). We first determined 2y survival by DRI for the 270 pts without JMML. Survival for JMML was closest to the VHR strata and we grouped JMML with VHR for all further analyses. The size of each of the risk strata were different for children compared to adults, VHR (n=32, 11%), HR (n=108, 39%), IR (n=128, 46%), and LR (n=12, 4%). Given the small number of LR pts, we excluded them from further analyses. We then determined that DRI effectively stratified pts into distinct strata for relapse (FIG 1A) and disease-free survival (FIG 1B). Because transplant practices are different for children compared to adults (e.g., more myeloablative conditioning), we examined whether DRI remained predictive of outcomes after adjustment for age, donor type, stem cell source, and conditioning intensity. We used IR as the reference group for these multivariate analyses. Children with HR DRI were significantly more likely to relapse (HR 2.1, 95% CI 1.2-3.7) and have worse DFS (HR 1.6, 95% CI 1.0-2.5). The risks for relapse and worse DFS were even greater for children with VHR DRI (relapse, HR 3.4, 95% CI 1.6-7.3, DFS 3.59, 95% CI 2.0-6.5). There were no significant differences in 2y non-relapse mortality by DRI. VHR pts had significantly worse 2y OS (HR 3.2, 95% CI 1.6-6.4) but HR pts were not significantly different for 2y OS than IR pts (HR 1.3, 95% CI 0.7-2.2). OS for HR and IR pts may diverge with longer follow-up. In summary, the LR strata is small and more pts are needed to determine their outcomes. However, for >95% of children the DRI creates 3 distinct risk strata. The DRI can be used in pediatric clinical trials to stratify for risk of relapse.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».