QoL Data in CAR-T Cost-Effectiveness Analysis (CEA) in France: What to Use?

OBJECTIVES: Cost-effectiveness analyses (CEAs) assessing CAR-T cell therapies were required by the French HTA since 2018 as they fulfilled the eligibility criteria of financial revenue threshold and since 2022 given their innovative character. Selection of quality of life (QoL) data considered in the CEAs submitted has been challenging and the level of acceptability evolving over time. Objectives of this analysis were to review choices made to document QoL in the previously assessed CEAs and to trace evolution of choices made and their level of acceptability over time.

METHODS: Available French efficiency opinions of CAR-T cell therapies in oncology were reviewed. Approaches to document QoL were identified and enriched with French HTA requests. Evolution of approaches changing and acceptability level over time were tracked.

RESULTS: Nine efficiency opinions assessing CAR-T cell therapies were released in France since January 2019. QoL data were generally documented using data collected during pivot clinical trials. The review showed the following trends: 1) while mapping QoL data using foreigner tariffs used to be accepted, only French tariffs are currently accepted, 2) use of QoL data estimated in clinical trials did not raise major reservations even when lacking robustness being estimated on very small sample sizes, 3) utility scores estimated using EQ-5D-3L questionnaire were lower hence consistent with the general population’s utility scores while those estimated using EQ-5D-5L questionnaire were almost equal to the general population’s 4) importance of assigning utility decrements to CAR-T specific adverse events is increasing.

CONCLUSIONS: Documenting QoL in CEAs in France evolved over time showing willingness of manufacturers to use robust methods. Use of QoL data estimated in clinical trials seems to be the most accepted approach. QoL data collection should be a focus point since the clinical trial’s conception. Further guidelines specific to innovative therapies could also leverage uncertainty related with QoL data selection.