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Enregistrement W2742432366 · doi:10.1182/blood.v128.22.2430.2430

Iron Overload Is Highly Prevalent in All Disease Severity States in Pyruvate Kinase Deficiency (PKD)

2016· article· en· W2742432366 sur OpenAlexaff
Eduard J. van Beers, Wilma Barcellini, Stefan Eber, Janet L. Kwiatkowski, Jennifer Rothman, Ellis J. Neufeld, Mukta Sharma, D. Holmes Morton, Bertil Glader, Nina Kollmar, Hassan M. Yaish, Jenny M. Despotovic, Christine Knoll, Yves Pastore, Kevin H.M. Kuo, Peter E. Newburger, Marcin W. Włodarski, Alexis A. Thompson, Yaddanapudi Ravindranath, Winfred C. Wang, Heng Wang, Joachim B. Kunz, Vicky R. Breakey, Melissa J. Rose, Melissa Rhodes, Heather A. Bradeen, Sujit Sheth, Dongjing Guo, Wendy B. London, Rachael F. Grace

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueErythrocyte Function and Pathophysiology
Établissements canadiensMcMaster UniversityUniversity of TorontoUniversity Health NetworkCentre Hospitalier Universitaire Sainte-Justine
Organismes subventionnairesnon disponible
Mots-clésMedicineFerritinInternal medicineGastroenterologyPyruvate kinase deficiencyAnemiaChelation therapyPyruvate kinaseThalassemiaGlycolysisMetabolism

Résumé

récupéré en direct d'OpenAlex

Abstract Background: PKD causes a defect in glycolysis resulting in a hereditary non-spherocytic hemolytic anemia. The prevalence of iron overload is not well described for PKD. Aim: We aim to describe the demographic features and prevalence of iron overload in transfusion dependent and transfusion independent patients with PKD. Methods: Between March 2014 and April 2016, 203 patients enrolled on the PKD Natural History Study at 29 IRB approved sites. All patients were confirmed to have two compound heterozygous or homozygous mutations in the PKLR gene. Children < 1 year of age (n=9) were excluded from this analysis, because elevated ferritin levels are less reliably related to iron overload. Patients were designated with iron overload at the time of enrollment if the plasma ferritin was >1000 ng/mL or the patient was on chelation therapy at any time during the prior 12 months. Patients were designated with having had iron overload if a MRI ever showed liver iron content (LIC) >3 mg/g dry weight or if they had ever received chelation therapy. Tests of association were performed using Fisher's exact test (categorical) and Wilcoxon rank sum test (continuous). Linear associations between variables were measured by Pearson correlation coefficient. P-values <0.05 were considered statistically significant. Results: Of the 194 patients, 111 (57%) were adults ≥18 years and 83 (43%) were children. The median age of enrollment was 20.6 y (range: 1.3-69.9). Splenectomy had been performed in 65% (126/194). Screening ferritin levels were available for 72% (140/194) and LIC for 32% (62/194). At enrollment, 48% (70/147) had iron overload as defined by ferritin and/or current chelation. Using the LIC criterion, iron overload had been present at some point in 86% (95/110) of patients. Ferritin positively correlated with LIC (n=45); r=0.62, p<0.0001. However, of 29 patients with an LIC measurement and a mean ferritin <1000 ng/mL, 15 (52%) had a LIC >3 mg/g DW. Baseline characteristics in patients with and without iron overload are shown in the Table. Notably, even in patients that were never regularly transfused and had a hemoglobin (Hb) >8.7 g/dl, the prevalence of iron overload was 26% (8/31). The frequency of iron overload was significantly higher in patients who had a prior splenectomy (p<0.0001), even after controlling for transfusion history (p<0.0001). Age was associated with iron overload (p=0.046); although, the age range of patients with iron overload was broad (1.3-69.9 years). The frequency of iron overload was significantly higher in those with a lower baselineHb(p=0.004) and higher bilirubin (p=0.03). Data on cardiac iron status was available for 66 patients.Only 2 had cardiac iron overload (defined as T2*<20ms); they were age 5 (T2* 17.8ms, LIC 5 mg/g) and 22 years (T2* 19.7ms, LIC 14 mg/g) at the time of the MRI. Of the 194 patients, 52 (27%) were from the Pennsylvania Amish community. These patients were managed differently than the non-Amish, in that only 2% of the Amish patients were on iron chelation therapy in the 12 months prior to enrollment compared with 43% among the non-Amish cohort. In addition, the Amish had a significant higher prevalence of splenectomy (96% vs 52%, p<0.0001) and proportion who had been historically transfused (79% vs 32%, p<0.0001). Despite these differences, the Amish patients had a lower prevalence of iron overload (34% vs. 51%). There was no significant difference inHbor enrollment age between the Amish and non-Amish cohorts. Conclusion: Iron overload is a common, serious complication in PKD, regardless of age, disease severity, or transfusion status. Although ferritin correlates with LIC for the PKD population overall, at the individual patient level, ferritin is not a good predictor of LIC and a ferritin <1000 ng/ml does not exclude hepatic iron overload. Therefore, we recommend that all patients with PKD starting at age 1 year should be screened annually for iron overload using ferritin and, at least once, using MRI. Disclosures Barcellini: Agios: Consultancy. Neufeld:Novartis: Consultancy. Morton:Agios Pharmaceuticals: Research Funding. Yaish:Octapharma: Other: Study investigator. Kuo:Agios Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alexion: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Apotex: Other: unrestricted educational grant; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Thompson:bluebird bio: Consultancy, Research Funding; Eli Lily: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mast: Research Funding; Baxalta (now part of Shire): Research Funding; ApoPharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Amgen: Research Funding. Grace:Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, 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 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 enseignants0,145
Score d'incertitude au seuil0,420

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 Opus0,018
Tête enseignante GPT0,261
Écart entre enseignants0,243 · 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

Citations3
Publié2016
Routes d'admission1
Résumé présentoui

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