Development and Validation of a Prognostic Score Involving Disease Status, Patient Age and Donor Type for Outcomes of Allogeneic Hematopoietic Cell Transplantation in Patients with Acute Myeloid Leukemia
Notice bibliographique
Résumé
Abstract Allogeneic hematopoietic cell transplantation (HCT) is a curative treatment option for acute myeloid leukemia (AML) when indicated. Numerous pre-transplant risk scores have been developed to predict post-transplant outcome, utilizing a variety of parameters. The purpose of this single-center study was to retrospectively develop and validate a prognostic score based on known significant pre-transplant variables for outcomes of 747 patients that underwent HCT for AML between 1978 and 2013. Median age of all patients at transplant was 44 years (range 17-71 years), 391 patients (52%) were female. HCT was performed in first complete remission (CR1) for 497 patients (67%) and in second complete remission (CR2) or advanced disease for 250 patients (33%). Donors were related for 538 patients (72%) and unrelated for 209 patients (28%). Peripheral blood stem cells (PBSC) were used as a graft source in 367 patients (49%). Myeloablative conditioning (MAC) was administered to 615 (82%) patients, 132 (18%) received reduced-intensity conditioning (RIC) regimens. HCT was performed over the time periods 1978-1990 (n=139), 1991-1999 (n=192), 2000-2006 (n=183) and 2007-2013 (n=233). Median follow-up of survivors was 90 months. Patients were assigned a combined score based on patient age, disease status and donor status. For disease status CR1, age <45 years and related donors, each parameter received a score 0. For disease status CR2 or advanced stage, age ≥45 and unrelated donors, each parameter received a score 1. Patients demonstrated a cumulative score of 0 (n=197), 1 (n=326), 2 (n=179) or 3 (n=45). All 747 patients were randomized into two groups, a test cohort (n=373) and a validation cohort (n=374). Univariate analysis for the test cohort demonstrated a favorable risk group with score 0 (n=92), an intermediate risk group of score 1-2 (n=255) and an unfavorable risk group with score 3 (n=26) with a 5-year overall survival (OS) of 61%, 35% and 20% respectively (p=0.0001)(Figure). Cumulative incidence of relapse (CIR) demonstrated a marginally significant difference between groups (p=0.05) with 5-year CIR 14%, 28% and 23% respectively. Non-relapse mortality (NRM) was marginally different (p=0.07) with 5-year NRM 27%, 39% and 54% respectively. Multivariable analysis of the test cohort for OS demonstrated that the presented scoring system remained significantly prognostic (p<0.0001) accounting for year of transplant as a continuous variable in the analysis (p=0.001, HR for transplant year 0.97, 95%CI 0.96-0.98). For OS, HR was 2.3 and 4.0 for the intermediate and high risk group respectively compared to favorable risk. For CIR, HR was 2.1 and 1.8 for intermediate and high risk patients respectively (p=0.05). For NRM, HR was 1.5 and 2.8 for intermediate and high risk patients respectively (p=0.01). Analysis of the validation cohort confirmed significant stratification for OS on univariate (p<0.0001, 5-year OS 68%, 36% and 30% for the three risk groups respectively) and multivariable analysis (p<0.0001). For CIR, no significant difference was seen on univariate (p=0.3, 5-year CIR 15%, 23% and 17% respectively) or multivariable analysis (p=0.3). For NRM, the validation cohort confirmed significant stratification between the risk groups on univariate (p<0.0001, 5-year NRM 19%, 42% and 48% respectively) and multivariable analysis (p<0.0001). In the presented study we developed and validated this readily calculable pre-transplant scoring system involving age, CR status and donor type which is highly prognostic for OS and NRM of patients undergoing allogeneic HCT for AML. We also demonstrated that the year transplant was performed over the last three decades had no influence on the prognostic significance of the scoring system. Figure 1 Figure 1. Disclosures Messner: Otsuka Pharmaceuticals Inc: Research Funding.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».