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Record W4405040930 · doi:10.1182/blood-2024-208943

Global Access to Chimeric Antigen Receptor (CAR) T-Cell Therapies: Health Technology Assessment (HTA) of CAR T in G7 Countries and Australia

2024· article· en· W4405040930 on OpenAlexaboutno aff
Alex Y. Ge, William B. Feldman, Martin Kaiser, Kai Rejeski, Gloria Iacoboni, Michael Dickinson, Aaron S. Kesselheim, Edward R. Scheffer Cliff

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsReimbursementChimeric antigen receptorHealth technologyMedicineHealth careCancerImmunotherapyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

Introduction CAR T-cells represent a major treatment advance for certain patients with hematologic malignancies. Barriers to accessing this technology include its prohibitive cost, the autologous nature of CAR T-cells (which necessitates a delay between apheresis and infusion), and the need for a specialized manufacturing process requiring a sophisticated logistical infrastructure. In countries outside the US, decisions to reimburse therapies depend on formal evaluations by health technology assessment (HTA) bodies, which account for factors including clinical benefits and comparative effectiveness. Cost-effectiveness studies of CAR T-cells have found mixed results. Given the high price of CAR T-cell therapies, we hypothesized that their variable efficacy and cost-effectiveness would affect HTA decision-making and reimbursement decisions. We also hypothesized that reimbursement decisions would differ between clinical settings for which there is demonstrated curative potential (e.g., DLBCL) versus those for which the therapy does not yet appear to be curative (e.g., myeloma). Methods To address these questions, we performed a cross-sectional analysis of reimbursement decisions made by HTA bodies of the G7 countries and Australia for all CAR T-cell indications approved in the US through January 1, 2024. We used the FDA and National Comprehensive Cancer Network websites to define the full set of drug-indication pairs and obtained corresponding full-form HTA reports from the websites of each HTA body. From each report, we abstracted (1) the CAR T-cell product and indication for use, (2) final reimbursement decision, and (3) factors used to justify HTA decision-making. For drug-indication pairs with multiple HTA evaluations, the most recent HTA decision prior to January 1, 2024 was used to determine reimbursement status. For Germany and Japan, where HTA bodies are utilized for price negotiations following drug approval and do not provide reimbursement recommendations per se, drug approval was used to infer reimbursement status. Drugs recommended with conditional clinical requirements were considered reimbursed. Results We identified 6 CAR T-cell products linked to 12 indications approved by the FDA through January 1, 2024. Of the 84 drug-indication pairs across countries (excluding the US), 59 (70%) were recommended for reimbursement, 8 (10%) were not recommended for reimbursement following an HTA evaluation, and 17 (20%) were non-reimbursed for other reasons (e.g., an application was never submitted). Countries with the most recommendations for funding were France and Germany (11, 92%). Japan recommended reimbursement for 9 (75%) indications, while Italy and Canada did for 8 (67%). Countries with the fewest reimbursed indications included England (6, 50%) and Australia (4, 33%). The most recommended drug-indication pair was axicabtagene ciloleucel (axi-cel) for DLBCL after two or more lines of systemic therapy, the only drug-indication pair to be approved in all countries. The fewest recommendations were linked to idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel) for myeloma as fifth or later line treatment, and lisocabtagene maraleucel for DLBCL relapsed or refractory to first-line therapy. For HTA bodies that provided rationale for drug reimbursement decisions, an analysis identified (1) inadequate comparator arms, (2) a lack of long-term survival data, (3) uncertainty regarding the true magnitude of clinical benefit, and (4) cost-effectiveness as common themes for recommendation against reimbursement. Discussion Despite cited concerns regarding cost-effectiveness and disparities in access, we find that the majority of CAR T-cell indications were recommended for reimbursement in this sample of the highest-income countries (HICs) globally. Among the CAR-Ts, HICs most frequently provided reimbursement for axi-cel for DLBCL (the only indication with demonstrated overall survival benefit) and least often provided reimbursement for ide-cel and cilta-cel for myeloma (for which CAR-T cells do not yet appear to have curative potential, though this may be one of multiple reasons). Our results demonstrate that HTA decisions are not necessarily the bottleneck in the HICs for access to CAR-T among patients for which the data indicate the greatest therapeutic potential, and that approaches are heterogeneous between jurisdictions.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.031
GPT teacher head0.373
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 teacher head, 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

Citations3
Published2024
Admission routes1
Has abstractyes

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