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Record W4405049650 · doi:10.1182/blood-2024-209470

Patient and Clinical Experience on Concizumab Clinical Trial: A Case Study

2024· article· en· W4405049650 on OpenAlexaff
Karen Strike, Mihir D. Bhatt, Nasrin Samji, Kay Decker, Rebecca Goldsmith, Anthony K.C. Chan

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsMcMaster UniversityHamilton Health SciencesMcMaster Children's Hospital
Fundersnot available
KeywordsMedicineClinical trialIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Background: The patient is an adolescent with severe hemophilia B who was enrolled in Novo Nordisk concizumab clinical trial NCT04082429 (explorer8) following completion of the non-interventional study NCT03741881 (explorer6). At the start of the non-interventional study, the patient had three reported target joints and one target joint remaining at the time of enrollment in the clinical trial. Annualized bleed rate (ABR) in the non-interventional study was 7.5 and 50.6 during the clinical trial. Of the total bleeds, over 23 anatomical areas were reported during the clinical trial, 28.6% of the bleeds came from the known target joint. The patient's physical activities changed during the non-interventional study due to the COVID-19 lockdown, and they were possibly less active during the study period with sport activity rated as low to moderate risk. During the clinical trial, the patient was physically active, engaging in ball hockey and cross-country running. Sport activity was rated as moderate risk and moderate to high risk at baseline and week 28 of the clinical trial respectively. The patient's concizumab dose was 0.25 mg/kg. The maintenance dose was initiated on week 4 based on a concizumab exposure of 97.9 ng/mL. Prior to explorer8, the patient was intensely treated with daily BeneFIX® and Rebinyn® prophylaxis during explorer6, but both FIX standard and extended half-life treatment failed to prevent bleeding episodes. Key Clinical Question: What factors should be considered when determining whether a patient should be withdrawn from a clinical trial? Clinical Approach: Throughout the clinical trial, the investigator discussed withdrawal from the study because of an increase in the number of bleeding episodes; however, the patient remained in the clinical trial as the patient and their family preferred concizumab over previous prophylaxis regimens. The patient reported on several occasions that they felt better despite the increased number of bleeding episodes. The patient reported that while on concizumab, the bleeding episodes were easier to treat, required shorter duration of treatment, and had less impact on the patient's daily life. The patient had concizumab plasma concentrations around or below 100 ng/mL except for the first measurement after initiating treatment with concizumab and had an increase in free TFPI over time. No response in thrombin generation was observed. It was not until a biological explanation behind the increase in bleeding episodes was available that the patient and family agreed to withdraw from the clinical trial. Conclusion: This case study demonstrates a patient who was difficult to treat with limited response to both FIX and concizumab. This case also raises several questions including: 1) Should the investigator have insisted that the patient be removed from the clinical trial before the biological data became available? 2) Is there something about concizumab that made it easier to treat bleeds? This case demonstrates that we may have more to learn from our patients on why they choose to participate and/or stay on clinical trials. Disclaimer: Novo Nordisk had no influence on the content of the abstract. The studies explorer6 and 8 are sponsored by Novo Nordisk.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.103
GPT teacher head0.445
Teacher spread0.342 · 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 designCase report
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

Citations0
Published2024
Admission routes1
Has abstractyes

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