Evidence map›Paper›PMID 35199367›Full record

ArticleBritish journal of clinical pharmacology2022

Characterisation of individual ferritin response in patients receiving chelation therapy.

Elisa Borella, Sean Oosterholt, Paolo Magni, Oscar Della Pasqua

Open access · hybridAbstract read
In one paragraph

Article in British journal of clinical pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Emerging Roles of the Iron Chelators in Inflammation.International journal of molecular sciences · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 3 countries.

Elisa BorellaDepartment of Industrial Engineering and Informatics, Università degli Studi di Pavia, Pavia, Italy.
Sean OosterholtClinical Pharmacology & Therapeutics Group, University College London, London, UK.
Paolo MagniDepartment of Industrial Engineering and Informatics, Università degli Studi di Pavia, Pavia, Italy.
Oscar Della PasquaClinical Pharmacology & Therapeutics Group, University College London, London, UK.ORCID 0000-0002-6211-1430
University of Pavia · ITGlaxoSmithKline (United Kingdom) · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo develop a drug-disease model describing iron overload and its effect on ferritin response in patients affected by transfusion-dependent haemoglobinopathies and investigate the contribution of interindividual differences in demographic and clinical factors on chelation therapy with deferiprone or deferasirox.

methodsIndividual and mean serum ferritin data were retrieved from 13 published studies in patients affected by haemoglobinopathies receiving deferiprone or deferasirox. A nonlinear mixed effects modelling approach was used to characterise iron homeostasis and serum ferritin production taking into account annual blood consumption, baseline demographic and clinical characteristics. The effect of chelation therapy was parameterised as an increase in the iron elimination rate. Internal and external validation procedures were used to assess model performance across different study populations.

resultsAn indirect response model was identified, including baseline ferritin concentrations and annual blood consumption as covariates. The effect of chelation on iron elimination rate was characterised by a linear function, with different slopes for each drug (0.0109 [90% CI: 0.0079-0.0131] vs. 0.0013 [90% CI: 0.0008-0.0018] L/mg mo). In addition to drug-specific differences in the magnitude of the ferritin response, simulation scenarios indicate that ferritin elimination rates depend on ferritin concentrations at baseline.

conclusionModelling of serum ferritin following chronic blood transfusion enabled the evaluation of drug-induced changes in iron elimination rate and ferritin production. The use of a semi-mechanistic parameterisation allowed us to disentangle disease-specific factors from drug-specific properties. Despite comparable chelation mechanisms, deferiprone appears to have a significantly larger effect on the iron elimination rate than deferasirox.

Indexed as

Chelation TherapyHemoglobinopathiesBenzoatesDeferasiroxDeferiproneDeferoxamineFerritinsHumansIronIron Chelating AgentsPyridonesTriazolesBenzoatesDeferasiroxDeferiproneDeferoxamineFerritinsIronIron Chelating AgentsPyridonesTriazoleschelating agentsdeferasiroxdeferipronedisease modellingferritinpharmacokinetic-pharmacodynamic relationshipsthalassaemia

Identifiers

PMID35199367
PMCPMC9544664
OpenAlexW4213449852

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.