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

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

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineEtiologyAnemiaCohortMyelodysplastic syndromesErythropoietinErythropoiesisInternal medicineRetrospective cohort studyHemoglobinPediatricsDiseaseIntensive care medicineBone marrow

Abstract

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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.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.261
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
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