A Systematic Review and Meta-Analysis of the Effect of Iron Chelation Therapy on Survival in Patients with Lower Risk Myelodysplastic Syndrome
Notice bibliographique
Résumé
Abstract Background: Anemia is the most common cytopenia among patients with myelodysplastic syndromes (MDS) often necessitating regular red blood cell (RBC) transfusions. As a result, most patients develop iron overload (IO). RBC transfusion dependency and IO have been associated with worse clinical outcomes, including inferior overall survival (OS), in MDS patients. While iron chelation therapy (ICT) is recommended by most clinical guidelines and experts for select MDS patients, the use of ICT remains controversial in the absence of published, randomized controlled trials. To evaluate the impact of ICT on survival among lower risk MDS patients, we performed a systematic review and meta-analysis (SRMA) of the literature. Methods: We conducted an SRMA according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines. PubMed and Embase electronic databases were searched through October 2016 with search terms “MDS” OR “myelodysplastic syndrome” AND “iron chelation” OR “iron chelating” OR “iron overload” AND “survival” OR “death” AND “study” OR “trial.” Additionally, the Cochrane Library, the World Health Organization (WHO) International Clinical Trials Registry, and abstracts from recent American Society of Hematology annual meetings (years 2014-2016) were searched. One study, published in 2014, had an updated analysis in 2017 that was used for the current analysis. Information abstracted included data relating to study and patient characteristics, outcome measures (mortality and progression to acute myeloid leukemia [AML]), and measures of effect (calculated odds, hazard ratios [HRs], and confounding variables for adjustment). A Random Effects model was used to compute an adjusted HR (aHR) among the different studies. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of studies. Study heterogeneity was assessed using the Cochran Q and the I2 statistic. Publication bias was assessed through visual examination of a funnel plot and with the Egger's test for small-study effects. Results: Of the 331 records screened, 23 were assessed for eligibility, and 9 were included (Figure 1). Of these 9 studies, 6 were considered to be of high quality based on the NOS. All 9 were observational studies (4 prospective and 5 retrospective); 8 were identified as including patients with the International Prognostic Scoring System (IPSS)-defined low and intermediate-1 risk MDS. In these 8 studies, ICT was associated with an overall lower risk of mortality (aHR 0.43; 95% confidence interval [CI] 0.30-0.60; p Conclusions: This SRMA suggests a significant reduction in the adjusted risk of mortality among IPSS low and intermediate-1 risk MDS patients treated with ICT. Furthermore, our analysis suggests that ICT is associated with delayed progression to AML, although the causality of these associations cannot be established based on this study. Randomized controlled studies are needed to confirm these findings. Download : Download high-res image (132KB) Download : Download full-size image Disclosures Ballas: Novartis: Honoraria, Speakers Bureau. Zeidan: AbbVie, Otsuka, Pfizer, Gilead, Celgene, Ariad, Incyte: Consultancy, Honoraria; Takeda: Speakers Bureau; Otsuka: Consultancy.
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 | 0,013 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,017 | 0,034 |
| Bibliométrie | 0,007 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».