The Modified Pre-Transplant EBMT Risk Score Is Superior To The HCT-CI Score In Predicting Overall Survival and Non-Relapse Mortality After Allogeneic Hematopoietic Cell Transplantation In Patients With Acute Myeloid Leukemia
Notice bibliographique
Résumé
Abstract A variety of factors have been investigated for their influence on outcomes post-allogeneic hematopoietic cell transplantation (HCT). Pre-HCT risk scores have been developed such as the Hematopoietic Cell Transplantation-Comorbidity Index (HCT-CI) and the modified EBMT score (mEBMT) for acute leukemias (involving age, CR status, donor type and gender mismatch). The purpose of this single-center study was to investigate the influence of these scores on outcome post-HCT in 350 patients transplanted between 1999 and 2012 for acute myeloid leukemia (AML) and to compare the predictive value of these scores. Median age of all patients at transplant was 49 years (range 18-71 years), 174 patients (50%) were female. HCT was performed in first complete remission (CR1) for 245 patients (70%) and in second complete remission (CR2) for 105 patients (30%). Cytogenetics at diagnosis were available in 289 patients (83%). Donors were matched related (n=213, 61%) or matched unrelated (n=137, 39%). Cytomegalovirus (CMV) serostatus was negative for both donor and recipient in 113 patients (32%). Peripheral blood stem cells were used as a graft source in 272 patients (78%). Myeloablative conditioning was administered to 239 (68%) patients, 111 (32%) received reduced-intensity conditioning (RIC) regimens. The HCT-CI scores were grouped as 0, 1-2 and ≥3 (94, 137 and 119 patients respectively). The mEBMT scores were grouped as 0-1, 2, 3 and 4-5 (32, 134, 120 and 64 patients respectively). Median follow-up duration among survivors was 62 months (range 12-156 months). Univariate analysis demonstrated a significant difference of overall survival (OS) according to the HCT-CI score (p=0.03), 3-year OS 52%, 53% and 39% in HCT-CI score 0, 1-2 and ≥3 (Figure 1). The mEBMT score also demonstrated a significant difference of OS among the patients with scores 0-1, 2, 3 and 4-5 (p=0.002), 3-year OS 75%, 53%, 40% and 39% respectively (Figure 2). The HCT-CI and mEBMT scores could not stratify the patients according to the cumulative incidence of relapse (CIR) with p-value of 0.99 and 0.50 respectively. For cumulative incidence of non-relapse mortality (NRM), the HCT-CI showed a trend of statistical significance (p=0.07), while the mEBMT score could stratify the patients according to the risk of NRM (p=0.01). Multivariable analysis was performed including the HCT-CI and mEBMT scores as previously defined. Covariates already incorporated in the mEBMT score (age, CR status, related donors) were not included in the multivariable analysis. For OS, the HCT-CI score was removed from the final model due to statistical insignificance (p=0.17). However, the mEBMT score was confirmed as an independent prognostic variable for OS (p=0.00002, HR=1.5, 95%CI=1.2-1.8). For NRM, HCT-CI did not maintain significance (p=0.11) while mEBMT again was confirmed as an independent prognostic factor (p=0.0003, HR=1.5, 95%CI=1.2-1.9). The current study showed that the mEBMT score was confirmed as an independent prognostic factor for OS and NRM in patients with AML undergoing HCT, while the HCT-CI score was not confirmed. In conclusion, the mEBMT risk score is superior to the HCT-CI score in predicting OS and NRM following allogeneic HCT in AML patients. Disclosures: No relevant conflicts of interest to declare.
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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 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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 ».