Patient-reported long-term quality of life after tisagenlecleucel in relapsed/refractory diffuse large B-cell lymphoma
Bibliographic record
Abstract
The JULIET phase 2 trial evaluated a single infusion of tisagenlecleucel in adult patients with relapsed/refractory (r/r) diffuse large B-cell lymphoma (DLBCL). The objective of the current analysis was to evaluate patient-reported health-related quality of life (HRQoL) with a median follow-up of 19.3 months among patients infused with a single dose of tisagenlecleucel. Patients enrolled were ≥18 years of age with r/r DLBCL after ≥2 lines of therapy and had either undergone a failed autologous stem cell transplant or were ineligible for the procedure. Two validated HRQoL instruments, Functional Assessment of Cancer Therapy-Lymphoma (FACT-Lym) and Short Form-36 (SF-36) Health Survey, were used to measure HRQoL at baseline and months 3, 6, 12, and 18. At data cutoff (21 May 2018), 115 patients had received tisagenlecleucel infusion. Among the 99 patients evaluated, overall response rate was 54%, and 40% of patients achieved complete response (CR). Initially, 108 patients completed the HRQoL assessments at baseline, including 57 patients who eventually achieved CR or partial response (PR). Further, 30 and 21 patients in clinical response who completed assessments at baseline also completed assessments at months 12 and 18, respectively. Patients who achieved CR or PR sustained HRQoL improvement in all FACT scores at all time points. SF-36 instruments showed improvement above the minimal clinically important differences on 5 of 8 subscales. Long-term follow-up in the phase 2 JULIET study demonstrated that patients with r/r DLBCL who respond to tisagenlecleucel therapy had sustained, clinically meaningful improvements in HRQoL. This trial was registered at www.clinicaltrials.gov as #NCT02445248.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".