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Use of Intravenous Immune Globulin in Patients with Immune Thrombocytopenia Before and After Romiplostim: Real-World Experience

2012· article· en· W2596014825 on OpenAlexaffabout
Korinne Hamilton, Lisa J. Toltl, Grace Wang, Naushin S. Sholapur, Julie Carruthers, Cyrus C. Hsia, Caroline Hamm, Normand Blais, Catherine Girard-Desbiens, Marc-André Pearson, Nancy M. Heddle, Donald M. Arnold

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of WindsorCentre Hospitalier de l’Université de MontréalVictoria HospitalWestern UniversityHamilton Health SciencesHôpital Notre-DameLondon Health Sciences CentreMcMaster University
Fundersnot available
KeywordsRomiplostimMedicineInterquartile rangeThrombopoietinImmune thrombocytopeniaInternal medicinePlateletPediatrics

Abstract

fetched live from OpenAlex

Abstract Abstract 4641 Background: Thrombopoietin receptor agonists such as romiplostim have been shown to increase platelet counts in patients with immune thrombocytopenia (ITP) and reduce the need for concomitant therapies. However, their effect on the utilization of intravenous immune globulin (IVIG) has not been examined in the post-marketing or ‘real world’ setting. The objective of this before-after study was to determine the effect of romiplostim on the utilization of IVIG outside of clinical trials. We determined the completeness of our dataset in this multi-center retrospective study. Methods: The charts of patients with ITP from 4 sites in Canada who had received romiplostim were reviewed until January 31, 2012. Patients were 18 years or older, had ITP according to ASH criteria and had at least 1 full year of data available prior to the first dose of romiplostim. A web-based electronic data capture system was used to collect platelet counts, IVIG use, bleeding as assessed by site and severity using an ITP-specific bleeding assessment tool, treatments and hospitalizations before and after the start of romiplostim treatment. IVIG use was compared after normalizing for the duration of time in observation. A pilot exercise was performed to optimize the quality of data extraction from charts. Results: Twenty-nine patients with ITP were included (15 females; median age 54 years, interquartile range [IQR] 45 – 63). Median platelet counts increased from 28 x109/L (IQR, 12 – 58) before romiplostim to 124 x109/L (IQR, 79 – 182) after romiplostim. The proportion of patients requiring other ITP treatments decreased from 25/29 (86%) to 17/29 (59%); the proportion of patients with any bleeding decreased from 24/29 (83%) to 11/29 (38%); and the proportion of patients with grade 2 or higher bleeding decreased from 13/29 (45%) to 6/29 (21%) after romiplostim. Of 29 patients, 16 (55%) had received IVIG before receiving romiplostim. IVIG use over time decreased in 14 of 16 (88%) patients, including 4 (25%) who did not require any IVIG after romiplostim administration. Two splenectomized patients with refractory ITP had received more IVIG in the period after romiplostim was initiated: One patient had discontinued romiplostim because of no platelet count response and subsequently developed intra-cerebral hemorrhage requiring multiple IVIG treatments; the other patient developed cyclical thrombocytopenia. Three additional patients received 1–3 infusions of IVIG only during the period after romiplostim. Of 128 IVIG infusion episodes, 106 were considered to have sufficient documentation since the dose, date of administration and preceding platelet count (within 1 week) were recorded in the chart. Conclusion: In this real-world cohort of patients with ITP, the proportion of patients who required IVIG decreased after starting romiplostim. A few refractory patients required more IVIG in the period after romiplostim. Retrospective data collection of treatment start and end dates and bleeding severity was limited. Disclosures: Arnold: Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hoffman-LaRoche: Research Funding.

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)0.001
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.236
Teacher spread0.226 · 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".

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Citations0
Published2012
Admission routes2
Has abstractyes

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