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Estimating the Total Cost of Infused Iron Chelation Therapy.

2005· article· en· W2589976880 on OpenAlexaff
Marie‐Pierre Desrosiers, Krista Payne, Jean‐François Baladi

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsCanadian Association of Radiation Oncology
Fundersnot available
KeywordsMedicineDeferoxamineReimbursementClinical trialThalassemiaUnit costChelation therapyIntensive care medicineHealth careInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Patients suffering from β-thalassemia or sickle cell disease require on-going blood transfusions. Chronic transfusion, however, results in iron overload, which if not removed by iron chelation therapy (ICT), causes organ damage. Deferoxamine (DFO) is currently the standard of care for ICT, but many patients do not adhere to therapy possibly because of the need for almost daily infusions lasting 8 to 10 hours each. Rationale: While the impact of current care on clinical and patient outcomes is generally understood, less is known about the total cost of DFO therapy. Objectives: To identify a complete set of cost items to inform the development of an ICT related Resource Use Questionnaire (RUQ) for administration in an international cohort study of the actual cost of ICT in practice; and to obtain a preliminary, literature-based estimate of total annual per patient costs of ICT. Methods: A search of the literature (EMB Reviews; Scirus and Ovid Medline (1996+); PubMed (1995+) was performed using the following key words: thalassemia, sickle cell disease, myelodysplastic syndrome, cost, iron chelation, Desferal, deferoxamine, resource use, reimbursement and compliance. Cost items were extracted from eligible studies to create an aggregated, composite set of ICT-related variables to which unit costs (2004/2005 USD) were applied. Results: Of 396 abstracts obtained, all but 96 were excluded because ICT cost data were lacking. Of those retained, only 4 studies (1 Israël;1 US;2 UK) reported ICT-related costs (1 lifetime;3 annual). Cost variables differed markedly among studies each focusing on some specific aspect. The application of unit costs to the composite list of ICT-related variables and associated resource use profiles reveal that total annual per patient ICT costs may be as high as $7,487 to $15,836 (£4,191 to £8,865) depending on age. The cost of DFO accounts for only 16%–31% of these estimated total costs, with the balance accounted for by other annual ancillary expenditures such as equipment and supplies, monitoring, and home health care services. Total costs could well be underestimated given that component lifetime costs such as DFO treatment complications, the clinical sequelae of poor adherence to DFO, and the indirect costs of lost productivity were not included. Cost estimates will be supplemented and validated at the time of abstract presentation by the resource use and unit cost data generated by the RUQ employed in the aforementioned international cohort study. Conclusions: Estimated total costs of ICT are substantial and well exceed the cost of DFO alone. A paucity of published data related to the total costs of ICT underscores the need for additional ICT cost data from actual practice to better understand the economic impact of novel ICT agents.

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)0.009
metaresearch head score (Gemma)0.038
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0130.016
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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".

Quick stats

Citations3
Published2005
Admission routes1
Has abstractyes

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