Transarterial Radioembolisation with Y90 Resin Microspheres and the Effect of Reimbursement Criteria in France: Final Results of the CIRT-FR Prospective Observational Study
Bibliographic record
Abstract
PURPOSE: This analysis of the CIRSE Registry for SIR-Spheres Therapy in France, CIRT-FR, reports on real-world outcomes of transarterial radioembolisation (TARE) with Y90 resin microspheres for hepatocellular carcinoma (HCC) and colorectal cancer liver metastases (CRLM) patients in France, focusing on safety, effectiveness and health-related quality of life (HRQoL). Results on patients treated based on national reimbursement criteria are discussed here. METHODS: Prospective, multicentre, observational study of HCC and CRLM patients treated between August 2017 and July 2020 with TARE Y90 resin microspheres. Patients were assigned to different analysis groups based on reimbursement recommendations. Follow-up period was at least 24 months with patient data collected every 3 months. RESULTS: In total, 252 (193 HCC, 59 CRLM) patients of CIRT-FR were included in the analysis. No differences in effectiveness, safety and HRQoL were found between analysis groups based on reimbursement recommendations. Median overall survival for HCC and CRLM was 19.0 (95% CI, 16.1-22.4) and 10.8 (95% CI, 8.0-13.5) months, respectively. Serious procedure-related adverse events occurred in 13% of the patients. HRQoL generally remained stable, with some fluctuations in function scores and symptoms. CONCLUSION: In our cohorts, patients performed similarly regarding clinical outcomes irrespective of their analysis group based on reimbursement recommendations. Our results suggest that instead of restrictive reimbursement criteria, more decision-making power in selecting suitable patient groups could be given to multidisciplinary tumour boards. Results confirm that TARE with Y90 resin microspheres is an effective and safe treatment for liver cancer, with maintained HRQoL in most patients.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".