Feasibility and efficacy of CD19-targeted CAR T cells with concurrent ibrutinib for CLL after ibrutinib failure
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Bibliographic record
Abstract
We previously reported durable responses in relapsed or refractory (R/R) chronic lymphocytic leukemia (CLL) patients treated with CD19-targeted chimeric antigen receptor-engineered (CD19 CAR) T-cell immunotherapy after ibrutinib failure. Because preclinical studies showed that ibrutinib could improve CAR T cell-antitumor efficacy and reduce cytokine release syndrome (CRS), we conducted a pilot study to evaluate the safety and feasibility of administering ibrutinib concurrently with CD19 CAR T-cell immunotherapy. Nineteen CLL patients were included. The median number of prior therapies was 5, and 17 patients (89%) had high-risk cytogenetics (17p deletion and/or complex karyotype). Ibrutinib was scheduled to begin ≥2 weeks before leukapheresis and continue for ≥3 months after CAR T-cell infusion. CD19 CAR T-cell therapy with concurrent ibrutinib was well tolerated; 13 patients (68%) received ibrutinib as planned without dose reduction. The 4-week overall response rate using 2018 International Workshop on CLL (iwCLL) criteria was 83%, and 61% achieved a minimal residual disease (MRD)-negative marrow response by IGH sequencing. In this subset, the 1-year overall survival and progression-free survival (PFS) probabilities were 86% and 59%, respectively. Compared with CLL patients treated with CAR T cells without ibrutinib, CAR T cells with concurrent ibrutinib were associated with lower CRS severity and lower serum concentrations of CRS-associated cytokines, despite equivalent in vivo CAR T-cell expansion. The 1-year PFS probabilities in all evaluable patients were 38% and 50% after CD19 CAR T-cell therapy, with and without concurrent ibrutinib, respectively (P = .91). CD19 CAR T cells with concurrent ibrutinib for R/R CLL were well tolerated, with low CRS severity, and led to high rates of MRD-negative response by IGH sequencing.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it