Post Allogeneic Stem Cell Transplant Outcomes Following Response to Hypomethylating Agent Therapy in Myelodysplastic Syndromes Are Predicted By Persistent International Prognostic Scoring System-Molecular Risk
Notice bibliographique
Résumé
Introduction: The International Prognostic Scoring System-Molecular (IPSS-M) ( Bernard NEJM Evidence 2022) and the 2023 International Working Group (IWG) response criteria for myelodysplastic syndrome (MDS) ( Zeidan Blood 2023) are used to more accurately assess prognosis and therapeutic response in MDS. However, it is unknown if these tools can be used to predict outcomes post-allogeneic hematopoietic stem cell transplant (HCT). We sought to understand the impact of pre-HCT IPSS-M on post-HCT outcomes in patients (pts) with MDS who responded to hypomethylating agent (HMA) therapy. Methods: Pts with MDS treated with HMA (azacitidine or decitabine) who received an HCT post-HMA at Dana-Farber Cancer Institute from January 2014 to December 2020 were included. Response to HMA was assessed by 2023 IWG response criteria and was defined as complete remission (CR) + CR with bi-lineage blood count recovery (CRbi) + CR with uni-lineage blood count recovery (Cruni) + CR with partial hematological recovery (CRh). Combined clinical and molecular risk was assessed by IPSS-M at times of diagnosis and of HCT, the latter using the bone marrow biopsy and sequencing data collected closest to HCT. High risk was defined as IPSS-M moderately high, high, and very high, whereas low risk was defined as IPSS-M very low, low, and moderately low. Results: A total of 148 pts with MDS who received HMA and underwent subsequent HCT were included. Median age was 64 years (range 26-79) and 61.5% were men. Pts were diagnosed with MDS-EB1 (26.4%), MDS-EB2 (45.3%), and other MDS subtypes (28.3%). IPSS-M at time of diagnosis was very low (2%), low (10.1%), moderate low (6.1%), moderate high (8.8%), high (31.8%), and very high (22.3%). IPSS-M pre-HCT was very low (12.8%), low (8.8%), moderate low (10.8%), moderate high (12.8%), high (20.3%), and very high (10.8%). IPSS-M at diagnosis and pre-HCT could not be calculated because of missing molecular data in 18.9% and 23.6% of pts, respectively. Pts received a median of 4 HMA cycles (range 1-20) and were treated with azacitidine for 7 days (54.1%), decitabine for 5 days (39.2%), and other schedules (6.7%). Prior to HCT, IWG 2023 responses were: CR (15.5%), CRbi (14.9%), CRuni (19.6%), CRh (0.7%), partial remission (PR: 1.4%), hematological improvement (HI: 9.5%), and no response (38.5%). Most pts received HCT from either a matched unrelated (60.8%) or matched related donor (18.2%) with reduced intensity conditioning (74.3%). Pts received graft versus host disease prophylaxis with tacrolimus (tac)/methotrexate (MTX) (54.7%), tac/MTX/sirolimus (19.6%), post-transplant cyclophosphamide/mycophenolate mofetil/tac (15.5%), tac/sirolimus (8.1%), other (2%). Median HCT-comorbidity index (CI) was 2 (range 0-13) and 48.6% pts had HCT-CI ≥ 3. For the entire cohort, the median follow-up time among ongoing survivors was 48.3 months (range 5.5-101.3). Among pts who responded to HMA per IWG 2023 criteria (CR/CRbi/CRuni/CRh), those who had high risk by IPSS-M prior to HCT had significantly shorter median overall survival (OS) (27 months; 95% CI 7.5-51) compared to pts with a low risk by IPSS-M (not reached; p=0.016) ( Figure A). Cumulative incidence of relapse (CIR) at 4 years was 66% for pts with high risk and 31% for low risk (p=0.034) ( Figure B). Pts with response to HMA with high risk by IPSS-M had lower OS (4-year OS: 27% versus 53%; p=0.016) and progression-free survival (4-year PFS: 19% versus 50%; p=0.018) but similar non-relapse mortality (NRM) (4-year NRM: 16% vs. 19%; p=0.66) post-HCT compared to pts with low risk at time of HCT. Conclusion: For pts with MDS who achieve a response to HMA prior to HCT, combined clinical/molecular risk, as assessed by IPSS-M, has an important prognostic impact on post-HCT outcomes. Pre-HCT risk should be evaluated for prognostication and to guide patient care, including future prospective studies evaluating novel agents for post-HCT therapy.
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 ».