The French Experience of Pharmacists and CAR T‐Cells: A Study of the French Society of Oncology Pharmacy (SFPO)
Bibliographic record
Abstract
The aim of this study was to describe the initial 3-year experience in vein-to-vein time for axi-cel therapy and the role of pharmacists in the first recruiting French centers. Retrospective observational data were collected for vein-to-vein time for commercial axi-cel after ≥ 2 lines of systemic therapy between January 2019 and December 2021 in the first 12 authorized French centers. Hospital pharmacists used a circuit database to ensure the prospective traceability at all steps. Totally 501 of the 562 intention-to-treat registrations on the database for cytapheresis (89,1%) led to the infusion of axi-cel. Median vein-to-vein time was shortened by 4 days. This was mainly due to tightening the interval from apheresis to release. The 36-day median vein-to-vein time achieved after 3 years' experience should be compared to the 29-34 days reported in Canada, the USA and Israel, where manufacturing sites are geographically closer to hospital centers than they are in France. The top 5 recruiting centers had the shortest vein-to-vein times. This French experience may serve as a model for other European centers, notably as regards deployment of pharmacists to improve the patient pathway with CAR T-cells and other gene and cellular therapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".