Feasibility of collecting longitudinal patient-reported outcomes in individuals with relapsed or refractory large B-cell lymphoma who received chimeric antigen receptor T-cell (CART) therapy
Bibliographic record
Abstract
PURPOSE: Chimeric antigen receptor T-cell (CART) therapy has shown clinical efficacy in refractory and relapsed large B-cell lymphomas, but is associated with serious acute and long-term toxicities. To understand the patient perspective, we measured a patient-reported outcome (PRO), specifically, health-related quality of life (HRQoL), at multiple time points over one year. METHODS: This was a prospective feasibility study of a cohort of patients who were eligible for standard of care CART therapy, tisagenlecleucel. Demographic data and disease characteristics were collected. HRQoL was measured using FACT-Lym at baseline, and months 1, 3, 6 and 12. FACT-Lym includes FACT-G (physical, social, emotional and functional well-being domains), plus a lymphoma subscale. RESULTS: Thirty-four of 35 patients approached, consented to participate. Two of them did not receive their infusion due to progressive disease. 50% were female and median age was 62 (23-77). Twenty-nine patients (91%) completed baseline FACT-Lym and 20 of 21 (95%) eligible patients completed 12-month FACT-Lym. 52% completed all 4 post-baseline FACT-Lym measures. Exploratory analyses for changes in FACT-Lym scores are reported. CONCLUSION: It is feasible to measure longitudinal PROs in patients who receive CART therapy. This study will inform future studies in evaluating the patient perspective on CART therapy.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".