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Enregistrement W2559918862 · doi:10.1182/blood.v128.22.1267.1267

Erythropoiesis-Stimulating Agents in Elderly Patients with Anemia of Unknown Etiology: Treatment Response and Cardiovascular Outcomes

2016· article· en· W2559918862 sur OpenAlexaff
Zachary Gowanlock, Swetha Sriram, Alison Martin, Anargyros Xenocostas, Alejandro Lazo‐Langner

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueErythropoietin and Anemia Treatment
Établissements canadiensLondon Health Sciences CentreWestern University
Organismes subventionnairesnon disponible
Mots-clésMedicineEtiologyAnemiaCohortMyelodysplastic syndromesErythropoietinErythropoiesisInternal medicineRetrospective cohort studyHemoglobinPediatricsDiseaseIntensive care medicineBone marrow

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Anemia of unknown etiology (AUE) is a common category of anemia in the elderly where investigations cannot identify a specific cause. We have previously shown that AUE patients exhibit lower erythropoietin (EPO) levels which may be associated with either decreased EPO production or a blunted EPO response to anemia. Erythropoiesis-stimulating agents (ESAs) mimic the effect of endogenous EPO and may play a role in treating AUE. In this study, we investigated the response to ESA treatment in patients with AUE compared to other causes of anemia. We also examined the effect of ESAs on cardiovascular outcomes in our cohort. To our knowledge, no previous study has specifically assessed ESAs in AUE. Patients and methods: We conducted a retrospective cohort study including all consecutive hematology patients referred to our centre and who had EPO levels determined between 2005 and 2013. We included patients 60 years or older who met the World Health Organization criteria for anemia (hemoglobin [Hb] <130 g/L in men, <120 g/L in women) excluding patients with insufficient electronic medical records. The cohort was subdivided into a group treated with ESAs and an untreated group. Three reviewers independently adjudicated each patient's anemia to one of four diagnostic groups: chronic kidney disease (CKD), myelodysplastic syndrome (MDS), AUE, or other miscellaneous etiologies. The etiology reported by at least two of the three reviewers was used in the analysis, with differences resolved by consensus. Inter-observer agreement was assessed using Fleiss' Kappa statistic. Treatment response was defined by at least a 15 g/L increase in the Hb level from baseline, or a decrease of at least 4 transfusions over 8 weeks, compared to pretreatment. We performed logistic regression to measure the association between the anemia etiology and treatment response while controlling for the following potential confounders: sex, age, weight, Charlson's comorbidity index, Hb, EPO level, estimated glomerular filtration rate (eGFR), and the presence of additional cytopenias. To evaluate safety we identified each documented cardiovascular event in the cohort including ischemic stroke, myocardial infarction, pulmonary embolism, deep vein thrombosis or portal vein thrombosis. We generated Kaplan-Meier curves comparing cardiovascular events and cardiovascular event-free survival between the treated and untreated groups. Hazard ratios were calculated using Cox regression analysis. Results: The inclusion criteria were met by 570 of 1511 potentially eligible patients. Of the 113 patients treated with an ESA, data was adequate to assess treatment response in 101 patients. Of the patients treated with an ESA, the mean age was 75.1 years and 60% were male. The mean pretreatment hemoglobin was 88.5 g/L. Inter-observer agreement for diagnostic categories was adequate. Eighty-two patients were treated with epoetin alfa and 19 patients received darbepoetin alfa. Treatment response was better in the CKD and AUE groups (54% and 47%, respectively) compared to the other groups. Compared to the group of other etiologies logistic regression analysis showed a 3.6 and 3.3 adjusted odds ratio (OR) for response for CKD and AUE respectively, although this was not statistically significant (Table 1). A baseline EPO level <200 IU/L was associated with a response to ESAs (OR 9.3; 95% CI 1.1-75.4). There was no significant difference in cardiovascular events or cardiovascular event-free survival between the treated and untreated groups, even after adjusting for confounders (Table 2). Conclusion: Our results suggest that ESAs can be used to treat anemia of unknown etiology, and responses may be similar to those in chronic kidney disease. This supports the notion that a relative EPO deficiency is probably related to the pathogenesis of AUE. Although treatment may be associated with increased cardiovascular events, this was not found to be significant in our cohort. Limitations of this study include its retrospective nature and a relatively small sample size. Further studies exploring the safety and efficacy of ESAs in the treatment of AUE are warranted. Table 1 Odds ratio of treatment response in unadjusted and adjusted logistic regression models Table 1. Odds ratio of treatment response in unadjusted and adjusted logistic regression models Table 2 Hazard ratios for cardiovascular outcomes in patients receiving ESAs in unadjusted and adjusted Cox regression models Table 2. Hazard ratios for cardiovascular outcomes in patients receiving ESAs in unadjusted and adjusted Cox regression models Disclosures Xenocostas: Janssen Inc.: Research Funding. Lazo-Langner:Daiichi Sankyo: Research Funding; Pfizer: Honoraria; Bayer: Honoraria.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,001
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
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)0,0010,000

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 Opus0,017
Tête enseignante GPT0,261
Écart entre enseignants0,244 · 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 source (Gemma direct ou Codex distillé), 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

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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