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Record W4229451358 · doi:10.2217/cer-2021-0278

Channeling effects in the prescription of new therapies: the case of emicizumab for hemophilia A

2022· article· en· W4229451358 on OpenAlex
Arash Mahajerin, Imi Faghmous, Peter Kuebler, Monet Howard, Tao Xu, Carlos Flores, Tiffany Chang, Francis Nissen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Comparative Effectiveness Research · 2022
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsRoche (Canada)
FundersF. Hoffmann-La Roche
KeywordsMedicineMedical prescriptionHealth insuranceHealth carePediatricsInternal medicinePharmacology

Abstract

fetched live from OpenAlex

Aim: To determine if emicizumab was channeled to clinically complex people with hemophilia A upon approval. Methods: Claims data (16 November 2017, through 31 December 2019) from US-based insurance databases were analyzed to compare the clinical complexity of people with hemophilia A initiating emicizumab with matched individuals receiving factor VIII (FVIII) episodically or prophylactically. People with hemophilia A with evidence of previous bypassing agent use (indicating FVIII inhibitors) were excluded. Outcomes included bleeding events, arthropathy, pain, comorbidities and healthcare costs. Results: A larger proportion of emicizumab users had bleeding events, comorbidities and arthropathy and greater healthcare costs in the year prior to starting emicizumab compared with FVIII users. Conclusion: Claims-based data limitations prevent an absolute conclusion. Nevertheless, emicizumab users appear more clinically complex than FVIII users, suggesting post-approval channeling.

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.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.163
GPT teacher head0.465
Teacher spread0.302 · 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