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Iron Chelation Therapy with Deferasirox (Exjade®, ICL670) or Deferoxamine Is Effective in Reducing Iron Overload in Patients with Advanced Fibrosis and Cirrhosis.

2005· article· en· W2582659172 on OpenAlexaff
Emanuele Angelucci, Bruno Turlin, Duran Canatan, A Mangiagli, Vincenzo De Sanctis, B. Meddeb, Christian Rosé, Denis Soulières, Melody J. Cunningham, Norbert Gattermann, C. Ressayre-Djaffer, B. Rabault, J. Ford

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsHôpital Notre-Dame
Fundersnot available
KeywordsDeferasiroxDeferoxamineChelation therapyCirrhosisMedicineDeferiproneGastroenterologyInternal medicineLiver biopsyThalassemiaFibrosisBiopsy

Abstract

fetched live from OpenAlex

Abstract Introduction: Although the direct measurement of iron from a liver biopsy is the reference standard method to determine liver iron concentration (LIC), results are highly unreliable in patients with advanced fibrosis and cirrhosis. As a result, chelation therapy is difficult to monitor in this patient population where effective chelation therapy may be critical. It is therefore important to assess parameters additional to LIC in order to accurately assess body iron in these patients. Aim: To analyze the efficacy of chelation with deferoxamine (DFO) and the investigational once-daily, oral iron chelator deferasirox (DSX) in patients with advanced fibrosis participating in DSX registration studies. Methods: A subgroup of patients from DSX Studies 0107 and 0108 were selected based on a staging result according to the Ischak scale of 5 (incomplete cirrhosis) or 6 (probable or definite cirrhosis), measured either at baseline or after 1 year of chelation therapy. The subgroup of patients with β-thalassemia participating in Study 0107 received DSX (n=26) or DFO (n=30). In Study 0108, the subgroup of patients with β-thalassemia unable to be treated with DFO (n=12) or patients with anemias other than β-thalassemia (n=7) were treated with DSX only. In both studies, patients received chelation therapy according to baseline LIC. Results: In Study 0107, treatment with DSX or DFO led to a decrease in semi-quantitative tissue iron score (TIS) and LIC, which were paralleled by changes in serum ferritin. TIS, LIC and serum ferritin in a subgroup of patients with advanced fibrosis and cirrhosis treated with DSX and DFO (Study 0107) TIS LIC, mg Fe/g dw Serum ferritin, ng/mL DSX (n=26) DFO (n=30) DSX (n=26) DFO (n=30) DSX (n=26) DFO (n=30) *Median (min, max) Baseline* 35.5 (4,39) 34 (10,52) 25.5 (2.4,45.9) 19.5 (3.9,55.1) 4195 (321,12646) 4144 (653,15283) Change from baseline* −2 (−43,20) −2 (−25,16) −9.4 (−42.2,13.1) −3.1 (−24.5,12.4) −1269 (−7082,3609) −951 (−8259,1264 Similarly, in Study 0108, DSX treatment produced a decrease in all 3 parameters in patients with β-thalassemia or rare anemia. TIS, LIC and serum ferritin in a subgroup of β-thalassemia and rare anemia patients with advanced fibrosis and cirrhosis (Study 0108) TIS LIC, mg Fe/g dw Serum ferritin, ng/mL β-thalassemia (n=12) Rare anemia (n=7) β-thalassemia (n=12) Rare anemia (n=7) -thalassemia β (n=12) Rare anemia (n=7) *Median (min, max) Baseline* 35 (4,48) 41 (32,49) 29.4 (3.8,37.4) 26.3 (15,51.3) 4813 (440,11698) 2385 (1553,9099) Change from baseline* 2 (−19,27) −3 (−20,1) −1.6 (−18,9.9) −10 (−13.9,8.8) −986 (−4453,2131) −1322 (−2609,1901) Conclusions: Chelation therapy with DSX or DFO is effective in reducing iron overload in patients with advanced fibrosis and cirrhosis. The trends observed in TIS and LIC were closely mirrored by changes in serum ferritin, highlighting the validity of this method for monitoring chelation therapy in this population.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.082
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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 teacher head, 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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Citations6
Published2005
Admission routes1
Has abstractyes

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