Long-Duration Complete Remissions of Diffuse Large B Cell Lymphoma after Anti-CD19 Chimeric Antigen Receptor T Cell Therapy
Bibliographic record
Abstract
T cells expressing anti-CD19 chimeric antigen receptors (CARs) can induce complete remissions (CRs) of diffuse large B cell lymphoma (DLBCL). The long-term durability of these remissions is unknown. We administered anti-CD19 CAR T cells preceded by cyclophosphamide and fludarabine conditioning chemotherapy to patients with relapsed DLBCL. Five of the seven evaluable patients obtained CRs. Four of the five CRs had long-term durability with durations of remission of 56, 51, 44, and 38 months; to date, none of these four cases of lymphomas have relapsed. Importantly, CRs continued after recovery of non-malignant polyclonal B cells in three of four patients with long-term complete remissions. In these three patients, recovery of CD19 + polyclonal B cells took place 28, 38, and 28 months prior to the last follow-up, and each of these three patients remained in CR at the last follow-up. Non-malignant CD19 + B cell recovery with continuing CRs demonstrated that remissions of DLBCL can continue after the disappearance of functionally effective anti-CD19 CAR T cell populations. Patients had a low incidence of severe infections despite long periods of B cell depletion and hypogammaglobulinemia. Only one hospitalization for an infection occurred among the four patients with long-term CRs. Anti-CD19 CAR T cells caused long-term remissions of chemotherapy-refractory DLBCL without substantial chronic toxicities.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".