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Record W2729419377 · doi:10.1177/2054358117716461

Costs Associated With Intravenous Darbepoetin Versus Epoetin Therapy in Hemodialysis Patients: A Randomized Controlled Trial

2017· article· en· W2729419377 on OpenAlexaffabout
Andrea Lynn Woodland, S. Murphy, Bryan M. Curtis, Brendan J. Barrett

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2017
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsMemorial University of NewfoundlandSt. John’s Health Sciences Centre
Fundersnot available
KeywordsMedicineHemodialysisRandomized controlled trialIntensive care medicineDarbepoetin alfaIntravenous ironKidney diseaseEpoetin alfaInternal medicineNephrologyErythropoietinAnemiaIron deficiency

Abstract

fetched live from OpenAlex

BACKGROUND: Anemia of chronic kidney disease is associated with adverse outcomes and a reduced quality of life. Erythropoiesis-stimulating agents (ESAs) have improved anemia management, and 2 agents are available in Canada, epoetin alfa (EPO) and darbepoetin alfa (DA). EPO and DA are considered equally effective in achieving target hemoglobin (Hb), but it is not clear whether there is a cost difference. There have been few head-to-head comparisons; most published studies are observational switch studies. OBJECTIVE: To compare the cost of DA and EPO and to determine the dose conversion ratio over a 12-month period. DESIGN: Randomized controlled trial. SETTING: Canadian outpatient hemodialysis center. PATIENTS: Eligible patients were adult hemodialysis patients requiring ESA therapy. MEASUREMENTS: The primary outcome was ESA cost (Can$) per patient over 12 months. Secondary outcomes included the dose conversion ratio, deviation from target ranges in anemia indices, iron dose and cost, and time and number of dose changes. METHODS: An open-label randomized controlled trial of intravenous (IV) DA versus EPO was conducted in 50 hemodialysis patients. Participants underwent a minimum 6-week run-in phase followed by a 12-month active study phase. ESA and iron were dosed using a study algorithm. RESULTS: = .02). The dose conversion ratio was 280:1 (95% confidence interval [CI]: 197-362:1) at the end of the run-in phase, 360:1 (95% CI: 262-457:1) at the 3-month point of the active phase, and 382:1 (95% CI: 235-529:1) at the 6-month point of the active phase. There were no significant differences between the 2 groups in weekly iron dose, Hb, serum ferritin, or transferrin saturation. The number of dose changes and the time to Hb stability were similar. LIMITATIONS: Results may not be generalizable to hemodialysis units without algorithm-based anemia management, with subcutaneous ESA administration, or to the nondialysis chronic kidney disease population. The effective conversion ratio between EPO and DA is known to increase at higher doses; the Hb targets used in the study were slightly higher than those recommended today so it is possible that the doses used were also higher. Because of this, the cost savings estimated for DA could differ somewhat from the savings realizable in current practice. CONCLUSIONS: In this study of hemodialysis patients with comparable anemia management, IV DA cost $1876 less per year per patient than IV EPO. The dose conversion ratio was greater than 350:1 by the 3-month point. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02817555).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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 designRandomized trial
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".

Quick stats

Citations7
Published2017
Admission routes2
Has abstractyes

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