Impact of Bone Marrow Fibrosis in MDS Patients Treated with Azacitidine
Notice bibliographique
Résumé
Abstract Background: Myelofibrosis (MF) in primary myelodysplastic syndromes (MDS) is a distinct clinicopathological entity from primary myelofibrosis. In the absence of therapy, it has been shown to be an independent predictor of worse overall survival (OS) and leukemia-free survival (LFS) in both low and high risk MDS (Della Porta, J. Clin. Oncol, 2009). However, there are conflicting reports as to whether this applies to higher-risk patients treated with azacitidine, the recommended first line therapy in this group (Fu, Mod. Pathol, 2014). Methods: 93 consecutive patients from our centre treated with azacitidine for MDS or CMML between 2008 and present were identified from a national prospective MDS registry. The pre-treatment marrows of 53 patients were available for independent and retrospective MF scoring by a hematopathologist (MJ) using both the European Consensus and Bauermeister criteriafor myelofibrosis grading. Qualitative fibrosis status of either none/mild or increased/marked were extracted from original reports in 8 additonal patients for which marrows were not available for hematopathologic review. The remaining patients were excluded due to: >20% blasts pre-treatment (1), lack of pre-treatment bone marrows (20), lack of fibrosis status indicated in original report and marrow not available for review (10), and lack of response data (1). Those with European Consensus MF <2 or qualitatively mild/none were compared to those with MF >or= 2 or qualitatively increased/marked. Patients were also compared as Bauermeister grades 1-2 or mild/none vs. Bauermeister grades 3-4 or increased/marked. Results: Median age of the 61 patients was 72 years and 74% were male. According to WHO classification, 2 had del(5q) syndrome, 5 RARS, 8 RCMD, 16 RAEB-1, 23 RAEB-2, 2 CMML1, 4 CMML2 and 1 MDS/MPN. Median hemoglobin level, neutrophil count, platelet count, LDH, ferritin, and marrow blast count were 91 g/L (range 64-136), 1 x109/L (0-46), 51 x109/L (2-459), 263 U/L (110-1442), 746 mcg/L (56-7983) and 7% (2-18), respectively. 58% were transfusion dependent at start of treatment. IPSS was High, Int-2, Int-1, and Low in 9%, 46%, 33%, and 4% of patients. 32 patients (53%) had European Consensus MF grades >or=2 or increased/marked fibrosis, and this was significantly (p=0.011) associated with higher pre-treatment ferritin levels (1110 vs. 532mcg/L). The increased MF group also showed trends towards younger age (68 vs 72 years), longer time from diagnosis until treatment (18.3 vs. 7.1 mos), greater transfusion dependence (69 vs. 45%), and pre-treatment LDH >250 U/L (61 vs. 42%), which did not meet statistical significance given limited sample size. Otherwise there were no significant relationships between MF score and WHO classification, IPSS/IPSSR, karyotype/cytogenetics, or other covariates. The results were similar when comparing groups by the alternative Bauermeister criteria, with increased fibrosis associated with a ferritin of >1000 mcg/L (p=0.038). After a median of 9 cycles (1-62) of azacitidine,complete remission (CR), marrow CR, and hematologic improvement (HI) was achieved in 9 (15%), 5 (8%), and 27 (44%) patients, respectively. Stable disease was seen in 29 (48%) patients. After a median follow-up of 3 years, median OS by Kaplan-Meier survival curve was 3.6 years in all treated patients and 2.7 years in IPSS Int-2/High patients. Regardless of which fibrosis grading system was used to compare patients, there were no significant differences in time to achieve best response, response rates, OS, or LFS based on pre-treatment MF grades (Figure 1). Conclusion: In this prospective registry series of azacitidine treated MDS with retrospective, pathology reviewed semi-quantitative MF grading, the degree of myelofibrosis did not significantly impact response to azacitidine, progression to leukemia, or overall survival. However, increased fibrosis was significantly associated with higher pre-treatment ferritin values and resulted in a non-significant trend towards younger age, longer time to treatment, transfusion dependence, and higher pre-treatment LDH levels. Figure 1 Overall Survival by MF Grade Figure 1. Overall Survival by MF Grade Disclosures Wells: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees. Buckstein:Novartis: Honoraria; Celgene: Honoraria, 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) | 0,002 | 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 ».