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Availability and financing of CAR-T cell therapies: A cross-country comparative analysis

2024· review· en· W4402492440 on OpenAlexaff
Yulia Litvinova, Sherry Merkur, Sara Allin, Ester Angulo-Pueyo, Daiga Behmane, Enrique Bernal‐Delgado, Miriam Dalmas, Antonio De Belvis, Nigel Edwards, Francisco Estupiñán‐Romero, Péter Gaál, Sophie Gerkens, Margaret Jamieson, Alisha Morsella, Dario Picecchi, Hilde Røshol, Ingrid Sperre Saunes, Terry Sullivan, Balázs Szécsényi-Nagy, Inneke van de Vijver, Ricciardi Walter, Димитра Пантели

Bibliographic record

VenueHealth Policy · 2024
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsInstitute of Health EconomicsInstitute for Work & Health
FundersEuropean Observatory on Health Systems and Policies
KeywordsBusinessFinance

Abstract

fetched live from OpenAlex

Chimeric antigen receptor T-cell therapies (CAR-T therapies) are a type of advanced therapy medicinal product (ATMP) that belong to a new generation of personalised cancer immunotherapies. This paper compares the approval, availability and financing of CAR-T cell therapies in ten countries. It also examines the implementation of this type of ATMP within the health care system, describing the organizational elements of CAR-T therapy delivery and the challenges of ensuring equitable access to all those in need, taking a more systems-oriented view. It finds that the availability of CAR-T therapies varies across countries, reflecting the heterogeneity in the organization and financing of specialised care, particularly oncology care. Countries have been cautious in designing reimbursement models for CAR-T cell therapies, establishing limited managed entry arrangements under public payers, either based on outcomes or as an evidence development scheme to allow for the study of real-world therapeutic efficacy. The delivery model of CAR-T therapies is concentrated around existing experienced cancer centres and highlights the need for high networking and referral capacity. Some countries have transparent and systematic eligibility criteria to help ensure more equitable access to therapies. Overall, as with other pharmaceuticals, there is limited transparency in pricing, eligibility criteria and budgeting decisions in this therapeutic area.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.139
GPT teacher head0.530
Teacher spread0.391 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2024
Admission routes1
Has abstractyes

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