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Enregistrement W2532528872 · doi:10.1182/blood.v118.21.2791.2791

Initial Transfusion Rate Predicts Survival in MDS

2011· article· en· W2532528872 sur OpenAlexaffabout
Lap Shu Alan Chan, Roman M. Shapiro, Rena Buckstein, Yulia Lin, Jeannie Callum, Lisa Chodirker, Christina D. Lee, Adam Lam, Alexandre Mamedov, Richard A. Wells

Notice bibliographique

RevueBlood · 2011
Typearticle
Langueen
DomaineMedicine
ThématiqueHematological disorders and diagnostics
Établissements canadiensHealth Sciences CentreSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineInternal medicineBlood transfusionMyelodysplastic syndromesDiseaseInternational Prognostic Scoring SystemBone marrow

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 2791 Introduction: Most MDS patients require chronic red blood cell (RBC) transfusion. Despite the immediate benefit of transfusion, transfusion dependence in MDS is a negative prognostic factor for overall survival. It has been suggested that transfusional iron overload, which is linked to toxicity through oxidative stress, contributes to poorer disease outcome and even to the progression of MDS to acute leukaemia. Alternatively, transfusion requirements may merely reflect disease severity in MDS and hence inferior disease outcome. To date, the exact relationship between transfusion, disease severity and outcome remains unclear. Nevertheless, aside from dependency, there are other essential aspects in transfusion medicine such as transfusion rate and patterns. We therefore examined the transfusion history of MDS patients to explore possible pathophysiological and prognostic values of these parameters. Methods: We performed retrospective single institution study of 40 consecutive chronically transfused patients between May 1998 and May 2011in the MDS program at the Odette Cancer Centre of Sunnybrook Hospital, Ontario, Canada. Median follow-up was 60 months. Median age was 72 years (range 28–88). 25 patients were male. WHO diagnostic categories were: 5q=2, CMML1=2, MDS/MPD=2, RA=2, RARS=1, RCMD=9, RCMD-RS=4, T-MDS=1, Unclassified=4, CMML2=2, RAEB1=2, RAEB2=4, AML=5. IPSS risk groups were: No score=5, low-risk=6, int-1=15, int-2=4, high-risk=10. 11 patients received iron chelation therapy. 20 patients received active treatment beyond transfusions. Results: Overall survival (OS) at 100 weeks was 54.1%. IPSS category (low/int-1 vs. int-2/high-risk) was a significant predictor of OS according to the Cox proportional-hazards regression (P<0.005, HR=7.39, median survival = 49 weeks for int-2/high-risk patients with 33.3% survival at 100 weeks, 69.4% survival at 100 weeks for low-risk/int-1 patients). To examine the prognostic importance of initial transfusion rate (ITR) in MDS we analyzed the total number of PRBC units transfused in the first 10 weeks after each patient became transfusion dependent to derive the ITR (unit PRBC/week, u/wk). In this way the patients were separated into two groups: low ITR (<1 u/wk, N=24, 73.2% survival at 100 weeks) and high ITR (≥1 u/wk, N=13, median survival at 58 weeks and 27% survival at 100 weeks). At week 10, we observed a divergence of the average transfusion history curves between the low and high ITR groups (Figure 1). Multivariate analysis identified ITR (P<0.0001, HR=18.6), IPSS (P<0.005, HR=15.2) and iron chelation (P<0.05, HR=11.4) as statistically significant predictors of overall survival. When analysis was limited to only those patients with IPSS low/int-1 risk categories (Figure 2), Cox regression revealed ITR as the sole predictor of OS (N=14 for low ITR group, 65.5% survival at 100 weeks; N=11 for the high ITR group, median survival at 24 weeks; P<0.05, HR=78.1). To examine possible dose-response trend related to ITR, the patients were re-organized into 3 groups: <0.5 u/wk (N=10, 90% survival at 100 weeks), ≥0.5 to <1 u/wk (N=14, 59.2% survival at 100 weeks) and ≥1 u/wk (N=13, median survival at 58 weeks and 27% survival at 100 weeks). A statistically significant trend was identified using the Logrank test for trend (P<0.005). Subsequent multivariate analysis identified ITR (P<0.0001, HR=10.5), IPSS (P<0.001, HR=18.7) and iron chelation (P<0.05, HR=23.0) as predictors of OS. After patients with IPSS from int-2/high-risk were removed from the analysis, ITR is the only predictor of OS (P<0.05, HR=48.8). Conclusions: The initial rate of RBC transfusion after onset of transfusion dependence is a powerful predictor of outcome in MDS and appears to be independent of WHO category or IPSS. Patients with high transfusion requirement (more than 1 u/wk) can be rapidly identified after they become transfusion dependent (as soon as 10 weeks). Although the pathophysiological basis of the link between ITR and disease outcome remains to be determined, and there is a need to validate this observation in an independent cohort, this parameter can be included in prognostic scoring systems for MDS. Patients with high ITR are likely to require additional treatments such as bone marrow transplantation or experimental therapies as soon as they are identified. Disclosures: No relevant conflicts of interest to declare.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,056
Score d'incertitude au seuil0,476

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,051
Tête enseignante GPT0,276
Écart entre enseignants0,225 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2011
Routes d'admission2
Résumé présentoui

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