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Record W4390904736 · doi:10.25251/skin.8.supp.317

Cost-per-Responder Analysis of Tralokinumab versus Dupilumab in Patients with Moderate-to-Severe Atopic Dermatitis in the US and Canada

2024· article· en· W4390904736 on OpenAlexaffabout
Jashin J. Wu, Sanjeev Balu, Nikolaj Birk Larsen, Ryan Pulleyblank, Liv Strømkjær, Aron Quah, Marni Wiseman

Bibliographic record

VenueSKIN The Journal of Cutaneous Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsUniversity of ManitobaUniversity of WinnipegGuenther Dermatology Research Centre
Fundersnot available
KeywordsDupilumabMedicineAtopic dermatitisEczema Area and Severity IndexDermatology

Abstract

fetched live from OpenAlex

Introduction and objective: Biologic treatments such as tralokinumab and dupilumab are therapeutic options for adult patients with moderate-to-severe atopic dermatitis (AD) who do not achieve adequate control with topical treatments or phototherapy. To date, no trials have been conducted to directly evaluate the relative efficacy of these biologic treatments. Applying indirect comparison of efficacy, we examined the cost-per-responder of tralokinumab compared to dupilumab in combination with topical corticosteroids (TCS) for the treatment of moderate-to-serve AD in the United States (US) and Canada. Method: A cost-per-responder analysis was undertaken considering the Eczema Area and Severity Index 75 (EASI-75) and Investigator’s Global Assessment (IGA-0/1) response criteria over a 32-week period. For each treatment, the cost-per-responder was computed by multiplying the treatment cost by the number needed to treat (NNT). Efficacy data were derived from an unanchored matching-adjusted indirect comparison (MAIC) utilizing patient-level data from ECZTRA-3 (tralokinumab) and aggregate data from LIBERTY AD CHRONOS (dupilumab). Treatment cost was defined as the drug cost of the biologic treatment with a duration corresponding to 32 weeks. TCS cost was not considered. Treatments were assumed to be administered every 2 weeks (Q2W). The costs were estimated based on Wholesale Acquisition Costs (WAC) from the US and ex-factory prices via the McKesson price list for Canada. All prices were converted to US dollars ($). Sensitivity analyses (SA) were conducted with every 4 week (Q4W) dosing beginning at week 16 for 10% and 20% of patients treated with tralokinumab. Results: For the US, the average cost-per-responder was $62,714 (Q4W SA: 10%: $61,239; 20%: $59,763) for tralokinumab versus $63,993 for dupilumab considering the EASI-75 response criteria, while the average cost-per-responder was $82,419 (Q4W SA: 10%: $80,480; 20%: $78,450) for tralokinumab versus $118,835 for dupilumab considering the IGA 0/1 response criteria. For Canada, the average cost-per-responder was $22,846 (Q4W SA: 10%: $22,308; 20%: $21,771) for tralokinumab versus $26,475 for dupilumab considering the EASI-75 response criteria, while the average cost-per-responder was $30,024 (Q4W SA: 10%: $29,317; 20%: $28,611) for tralokinumab versus $49,165 for dupilumab considering the IGA 0/1 response criteria. Conclusion: Assessing EASI-75 and IGA-0/1 response criteria at 32 weeks, this analysis indicates that tralokinumab in combination with TCS is associated with lower costs-per-responder compared with dupilumab in combination with TCS in the treatment of moderate-to-severe AD in the US and Canada.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.133
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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