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PB2247 ADJUSTED INDIRECT COMPARISON OF ELTROMBOPAG RELATIVE TO RITUXIMAB OR SPLENECTOMY IN SECOND LINE TREATMENT FOR CHRONIC IMMUNE THROMBOCYTOPENIC PURPURA

2019· article· en· W2949128311 on OpenAlexaff
Jorge José Félix, V. Andreozzi, B. Vandewalle

Bibliographic record

VenueHemaSphere · 2019
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsInstitute of Health Economics
Fundersnot available
KeywordsEltrombopagSplenectomyMedicineRomiplostimRituximabThrombocytopenic purpuraInternal medicineThrombopoietinImmune thrombocytopeniaSurgeryGastroenterologyPlateletLymphomaSpleen

Abstract

fetched live from OpenAlex

Background: Current guidelines recommend thrombopoietin receptor agonists (TPO‐RAs: eltrombopag and romiplostim), splenectomy and rituximab as second‐line treatment options for chronic immune thrombocytopenic purpura (ITP). To date no head‐to‐head randomized trial exists comparing these therapies. There is some sparse evidence for indirect comparison between eltrombopag and romiplostim, but no indirect comparison of TPO‐RAs with splenectomy or rituximab for ITP patients eligible to splenectomy. This is because evidence for the effect of rituximab and splenectomy in ITP comes from single arms trials and from observational studies or case series, respectively. Aims: To apply indirect adjusted comparison methods to assess the relative efficacy of eltrombopag in comparison to rituximab or splenectomy in second line treatment of ITP in patients eligible for splenectomy. Methods: A subset of 84 patients treated with eltrombopag but not subject to splenectomy in the randomised, phase 3 study RAISE (PMID: 20739054) were indirectly compared with the 60 adult splenectomy candidates with ITP treated with rituximab and included in the prospective multicentre phase 2 study by Godeau et al (PMID:18463354), and a large retrospective cohort of patients (n = 233) who underwent splenectomy for ITP in the study by Vianelli et al (PMID:23144195). After controlling for covariates, we estimate that the odds of response (platelet count >50 000 per μL) to eltrombopag is significantly higher than rituximab (OR = 4.6; 95%CI: 1.9 to 10.0). An adjusted response rate (platelet count >30 000 per μL) of 83.3% for eltrombopag treatment in ITP was estimate relative to 73.2% for splenectomy (OR = 2.8; 95%CI: 0.7 to 11.1). Results: A subset of 84 patients treated with eltrombopag but not subject to splenectomy in the randomised, phase 3 study RAISE (PMID: 20739054) were indirectly compared with the 60 adult splenectomy candidates with ITP included in the prospective multicentre phase 2 study by Godeau et al (PMID:18463354), and a large retrospective cohort of patients (n = 233) who underwent splenectomy for ITP in the study by Vianelli et al (PMID:23144195). After controlling for covariates, we estimate that the odds of response (platelet count >50 000 per μL) to eltrombopag is significantly higher than rituximab (OR = 4.6; 95%CI: 1.9 to 10.0). An adjusted response rate (platelet count >30 000 per μL) of 83.3% for eltrombopag treatment in ITP was estimate relative to 73.2% for splenectomy (OR = 2.8; 95%CI: 0.7 to 11.1). Summary/Conclusion: Adjusted indirect comparisons is a useful resource for evidence‐based decision‐making when no head‐to‐head data exists between alternative treatment options. Within the limits of the available data and of the methodology, eltrombopag is estimated to be the most effective second line treatment for the management of chronic immune thrombocytopenia patients candidates to splenectomy. Head‐to‐head clinical trials are needed to support these findings.

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)0.014
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.011
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.049
GPT teacher head0.341
Teacher spread0.292 · 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 designMeta-analysis
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
Published2019
Admission routes1
Has abstractyes

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