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Record W4285095408 · doi:10.1007/s40258-022-00737-w

Value and Price of Multi-indication Cancer Drugs in the USA, Germany, France, England, Canada, Australia, and Scotland

2022· article· en· W4285095408 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApplied Health Economics and Health Policy · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
FundersNovartis Pharmaceuticals UK Limited
KeywordsHealth economicsQuality of Life ResearchPublic healthValue (mathematics)Health administrationNew englandMedicineGeographyDemographyPolitical scienceSociologyLawStatistics

Abstract

fetched live from OpenAlex

PURPOSE: Oncology drugs are often approved for multiple indications, for which their clinical benefit varies. Aligning a single price to this differing value remains a challenge. This study examines the clinical and economic value, price, and reimbursement of multi-indication cancer drugs across seven countries, representing different approaches to value assessment, pricing, and coverage decisions: the USA, Germany, France, England, Canada, Australia, and Scotland. METHODS: Twenty-five multi-indication cancer drugs across 100 indications were identified with US Food and Drug Administration (FDA) approval between 2009 and 2019. For each indication data on Health Technology Assessment (HTA) recommendations, disease prevalence, and drug prices were obtained. Quality-adjusted life years (QALYs) gained, disease prevalence, list prices, and HTA outcomes were then compared across indications and regions. RESULTS: First approved indications provide a higher clinical benefit whilst targeting a smaller patient group than indication extensions. Quality-adjusted life year gains were higher for first (0.99, 95% CI 0.05-3.25) compared to second (0.51, 95% CI 0.02-1.63, p < 0.001) and third (0.58, 95% CI 0.05-2.07, p < 0.01) approved indications. Disease prevalence per 100,000 inhabitants was 20.7 (95% CI 0.2-63.3) for first compared to 27.1 (95% CI 1.5-109.6, p = 0.907) for second and 128.3 (95% CI 3.1-720.1, p < 0.001) for third approved indications. With each approved indication drug prices declined in Germany and France, remained constant in the UK, Canada, and Australia, whilst they increased in the USA. Negative HTA outcomes, clinical restrictions, and managed entry agreements (MEAs) were more frequently observed for indication extensions. CONCLUSIONS: Results suggest that indication development is prioritised according to clinical value and disease prevalence. Countries employ different mechanisms to account for each indication's differential benefit, e.g., weighted-average prices (Germany, France, Australia), differential discounts (England, Scotland), clinical restrictions, and MEAs (England, Scotland, Australia, Canada). Value-based indication-specific pricing can help to align the benefit and price for multi-indication cancer drugs.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.322
Teacher spread0.274 · 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