Impact of Age on Hospitalization and Readmission on Post Allogeneic Stem Cell Transplantation Outcome, Single Center Experience
Notice bibliographique
Résumé
Abstract Background: Recent advances and improvement of supportive care allowed allogeneic stem cell transplantation (HCT) to be offered to selected older patients. However, data regarding outcome and factors affecting the outcomes are limited. Method: We retrospective analyzed the outcome in 332 patients, median age 65 years (60-76), who underwent HLA-matched related (n=85), matched unrelated (n=205) and haploidentical donor (n=42) HCT, between January 2014 to December 2019. Of these 60% were male. Diagnosis was leukemia: 193, MDS: 76, MF: 46 and others: 17. Graft source was PBSC in 98%. Reduce-intensity conditioning regimen was used in 95%, and in vivo T-cell depleted in 89% of patients. We categorized them to 3 age-groups (G): G1 60-65y, (n=175), G2 >65-70y (n=127), and G3 >70y (n=30).Cox models were used to compare the rates of overall survival (OS), non-relapse mortality( NRM), event free-survival (EFS), length of hospitalization for HCT, GVHD and reasons of re-hospitalization during the first year post HCT. Results: The median follow up was 14 months (range: 1-123 months). Median days of hospitalization during HCT period were 30-days (range: 20-132 days), with trend towards significance when stratified by age group (p=0.049). HCT-CI scores were 0-1 (n=143), 2-3 (n=107) and >3 (n=70). The cumulative incidences of grade II-IV acute-GVHD was 38.3% and 16.3% for grades III-IV. Moderate-severe chronic-GVHD was 23.7%. Increasing age was not associated with increases in acute GVHD (p=0.86) or chronic-GVHD (p= 0.6). Overall, 188 (56%) patients were re-hospitalized within the first 6-month of HCT, and 61 (18%) in the second 6-month period. The 2-year OS rate (Fig 1) were 56% in G1, 53% in G2 and 34% in G3 (p=0.05). The 2-year EFS rate (Fig 2) were 54% for G1, 49% for G2, and 31% for G3 (P=0.04). Cumulative incidence of NRM at 2-year (Fig 3) were 25% in G1, 36% in G2 and 52% in G3 (p=0.008). Further results are illustrated in Table 1. Risk factors such as age, KPS, HCT-CI, donor-type, readmission and GVHD were analyzed for their associations with outcomes using univariate analyses, those with significant results entered in multivariate-analysis Table 2. Patients aged 60-≤65 had significantly better EFS (p=0.04) and associated with a border line significant trend for lower NRM (p=0.05) than those aged >70. Re-admission in the first 6-month post HCT had a significant impact on the OS, EFS and NRM. HCT-CI >3 had significant impact on NRM. Conclusion: Age had a significant impact on hospitalization period during HCT. Age >70 had significant impact on EFS and trend toward higher NRM. HCT-CI, acute and chronic-GVHD and readmission in first 6-month post-HCT were significant risk factors. Readmission in the first 6 months correlated with lower OS, EFS and higher NRM. Acute GVHD III-IV or moderate-severe chronic GVHD associated with poor outcomes. Selecting patients based on HCT-CI, and good management of GVHD and post-HCT complication may improve the clinical outcome. Figure 1 Figure 1. Disclosures Law: Novartis: Consultancy; Actinium Pharmaceuticals: Research Funding. Kim: Bristol-Meier Squibb: Research Funding; Pfizer: Honoraria; Paladin: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Lipton: Bristol Myers Squibb, Ariad, Pfizer, Novartis: 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 | 0,001 |
| 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) | 0,002 | 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 ».