Analysis of Impact of Comorbidities Constituting the HCT-CI Score on the Outcome of Patients Undergoing Allogeneic Hematopoietic Cell Transplant for Acute Myeloid Leukemia
Notice bibliographique
Résumé
Abstract The Hematopoietic Cell Transplant Co-morbidity Index (HCT-CI, Sorror et al 2005) was developed as a prognostic tool for overall survival (OS) and non-relapse mortality (NRM) in allogeneic hematopoietic cell transplant (HCT) patients. The prognostic significance of the score for patients with acute myeloid leukemia (AML) undergoing HCT has been demonstrated, however reports are conflicting. The purpose of this single-center study was to retrospectively investigate the prognostic impact of the individual component co-morbidities of the HCT-CI on the outcome of 418 patients that underwent HCT for AML at our center between 2000 and 2013. Patients underwent HCT in first (CR1, n=303) and second (CR2, n=115) complete remission. Median age at HCT was 50 years (range 18-71), 212 (51%) patients were female. Myeloablative conditioning (MAC) was used in 283 (68%) patients, reduced-intensity (RIC) in 135 (32%) patients. Donors were related for 236 (56%) patients, unrelated for 182 (44%) patients. Grafts were peripheral blood stem cells (PBSC) in 339 (81%) patients and bone marrow in 79 (19%) patients. Median follow-up of patients alive was 62 months (range 12-168). Cytogenetics at diagnosis were available for 84% of patients, of which 31 (7%) were favorable, 246 (59%) were intermediate and 74 (18%) were unfavorable risk (MRC classification). HCT-CI scores were grouped as 0 (n=109, 26%), 1-2 (n=157, 38%) and ≥3 (n=152, 36%). A total of 171 patients (41%) underwent HCT during the years 2000-2006 and 247 patients (59%) during the years 2007-2013. The observed frequency of the co-morbidities composing the HCT-CI is summarized in Table 1. Univariate analysis for OS demonstrated the following significant variables: Age (HR=1.02, 95%CI=1.01-1.03, p=0.0002), CR status (HR=1.42 for CR2, 95%CI=1.08-1.87, P=0.01), donor type (HR=0.73 for related, 95%CI=0.57-0.94, p=0.02), HCT-CI group (overall p-value=0.004). For OS, univariate analysis of the impact of individual co-morbidities was performed for the components of the HCT-CI score that were observed in ≥5% of the patients (Table 1). All variables with a p-value ≤0.2 were introduced into the multivariable analysis (not including the HCT-CI itself), and these included cardiac disorder (CAD, CHF, MI or EF≤50%) (HR=1.65, 95%CI=1.17-2.32, p=0.004), prior solid tumor (HR=1.56, 95%CI=1.06-2.30, p=0.02) and diabetes (HR=1.40, 95%CI=0.89-2.19, p=0.14). In the multivariable analysis for OS, none of the aforementioned co-morbidities demonstrated independent prognostic relevance. For NRM, univariate analysis demonstrated cardiac disorder (HR=1.89, 95%CI=1.27-2.81, p=0.002), diabetes (HR=1.94, 95%CI=1.20-3.12, p=0.007) and moderate pulmonary (FEV1 and/or DLCO 66-80% or dyspnea on slight activity) (HR=1.31, 95%CI=0.93-1.84, p=0.12) to meet the significance criteria for inclusion in the multivariable analysis, which finally demonstrated diabetes (HR=2.17, 95%CI=1.31-3.60, p=0.003) and cardiac disorder (HR=1.78, 95%CI=1.15-2.76, p=0.01) to be independent predictors of NRM post-transplant. In conclusion, among the pre-transplant co-morbidities included in the HCT-CI, diabetes and cardiac dysfunction are independent prognostic indicators for NRM but not for OS. Pulmonary dysfunction does not seem to negatively influence outcomes in this cohort of patients. Disclosures Kim: Novartis Pharmaceuticals: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, 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 | 0,000 | 0,002 |
| 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 | 0,000 | 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 ».