Patient-reported outcomes in patients with hematologic malignancies treated with CAR T-cell therapy in Europe
Bibliographic record
Abstract
ABSTRACT: Patient-reported outcomes (PROs) give direct insights into the treatment's impact on patient's life and complement clinical outcomes. However, since the advent of chimeric antigen receptor T-cell therapy (CAR-T), PROs have been underreported. Particularly, little is known about long-term health-related quality of life (HRQoL) and dimensions such as mental- and social well-being, working life, and financial burden. Therefore, we evaluated multidimensional PROs in a cross-sectional study among European patients who received CAR-T for hematologic malignancies. Patients completed validated questionnaires (EQ-5D-5L/EORTC-QLQ-C30/PCL-5/modified-iPCQ) and ad hoc items on treatment experiences, unmet care needs, and HRQoL. The survey was available online (January-October 2023) in 7 languages. Outcomes were compared with the European general population, a matched CAR-T-naive cohort with hematologic malignancies and across subgroups, using established thresholds for clinically important differences/problems and regression models. From 10 European countries, 389 patients participated (>1 year post-CAR-T: 56%). Mean EQ-VAS was 73.1 (standard deviation, 18.5). HRQoL was similar or better than reference cohorts, except for role-, social-, and cognitive-functioning. Physical-functioning problems were most frequently reported (41%), particularly by women, older individuals, and those who experienced neurotoxicity. The latter subgroup also reported more cognitive- and social-functioning problems. Anxiety regarding disease recurrence (76%), infections (66%) and long-term side effects (59%) was common. Among working-age patients, 72% could continue paid work after CAR-T. Younger patients (32%) reported more financial difficulties than older patients (9%). This study shows favorable general HRQoL after CAR-T compared with reference cohorts. However, a notable proportion of patients experienced problems in physical-, mental- and social well-being. We identified high-risk subgroups and care needs that should be addressed during follow-up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".