Chimerism of Blood T-Cells and Leukemia Lineage Cells Following Myeloablative Hematopoietic Cell Transplantation Is a Risk Factor for Relapse and Chronic Graft-Versus-Host Disease
Bibliographic record
Abstract
Abstract Background: Mixed chimerism of blood leukemia lineage cells has been reported to be highly predictive of relapse (Mattsson J et al. Leukemia 2001), but the utility of T-cell chimerism is controversial. Methods: Chimerism of T-cells (CD3 +) and leukemic lineage cells (CD13 +/CD33 + for myeloid malignancies and CD19 + for B-lymphoid malignancies) was measured in the peripheral blood for 600 hematopoietic cell transplant (HCT) recipients at 3-months post-transplant. Conditioning was myeloablative (fludarabine+busulfan+4GyTBI) and GVHD prophylaxis was with ATG+CsA+MTX. Results: Mixed (<95% donor) chimerism was present in 6% of patients in the leukemic lineage and 16% of patients in T-cells. Compared to patients with complete chimerism (≥95%), mixed chimerism predicted a significantly greater incidence of relapse (52% vs. 27%, P=0.044), and surprisingly, also a greater incidence of cGVHD (43% vs. 23%, P=0.028). Patients with mixed leukemic lineage chimerism also had poorer cGRFS (7% vs. 39%, P<0.001) and OS (29% vs. 55%, P<0.001). Mixed T-cell chimerism predicted a significantly greater incidence of relapse (46% vs. 24%, P<0.001) and lower cGVHD incidence (9% vs. 31%), with no difference in cGRFS or OS. The sensitivity/specificity/positive predictive value (PPV)/negative predictive value (NPV) of mixed leukemic lineage and T-cell chimerism for relapse were 65%/55%/35%/81% and 66%/57%/60%/79%, respectively. Sensitivity/specificity/PPV/NPV was similarly poor for cGVHD. In patients with complete leukemic lineage chimerism at 3-months, a ≥5% drop in donor chimerism at any future timepoint had sensitivity/specificity/PPV/NPV of 82%/79%/79%/82% for subsequent relapse. Conclusion: In the setting of myeloablative conditioning and ATG-based GVHD prophylaxis, mixed chimerism at 3-months post-transplant is a risk factor for subsequent relapse. However, the utility of these measurements in guiding medical interventions may be limited by insufficient predictive values. Nevertheless, patients with mixed chimerism may be candidates for more intensive surveillance. Disclosures Storek: Atara Biotherapeutics: Other: Site PI, Research Funding.
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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) | 0.000 | 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".