Outcomes of T-Cell Depleted Haploidentical Peripheral Blood Stem Cell Transplantation for Adult Acute Leukemia: A Meta-Analysis
Bibliographic record
Abstract
Abstract Background: Ex-vivo T-cell-depleted graft is used to prevent acute and chronic GVHD for haploidentical hematopoietic SCT (HSCT). We conducted a systematic review and meta-analysis to evaluate the outcomes of T-cell-depleted grafts for peripheral blood haploidentical stem cell transplantation in patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). Method: A comprehensive literature search on PubMed, Embase, Cochrane and Web of Science was conducted up to July 25, 2018. Two independent reviewers screened the literature and extracted data. The methodological quality was assessed using modified Newcastle-Ottawa Scale. CMA software v.3 was used for the analysis. Heterogeneity among studies was assessed using the I2 test. Random-effect model was applied. Results: The search strategy identified over 550 articles; three studies (n = 404 patients; 1 prospective; 1 multi-center) were selected for this meta-analysis. The sample size of the studies varied between 34 and 266 patients. The median follow-up ranged from 6 to 47 months. Two studies (Aversa, F. et al. 2005)(n=104 patients); (Ciceri, F. et al. 2008)(n=266 patients) used CD34+ selected cells and other study used TCR-αβ depleted PBSC graft (Kaynar, L. et al. 2016) (n=34). All studies used myeloablative (MA) conditioning. In vivo T-cell-depletion by ATG was used in two studies. Two studies using mega-dose of CD34+ did not use GVHD prophylaxis and other study with αβ T-cell depleted graft used mycophenolate mofetil (MMF). Engraftment rates ranged from 91% to 98%. Pooled rates (95%CI) of grade II-IV, III-IV aGVHD and chronic GVHD were 9% (4-20; I2=82%), 4.8% (1.7-13.1; I2=78%) and 10.7% (6.3-17.6; I2=64%), respectively. The pooled estimates (95%CI) showed a 2-year disease-free survival (DFS) rate of 30.8% (24.2-38.3; I2=54%), 2-year relapse incidence of 21.5% (17.4-26.2; I2=85%). The results are shown in figure 1. Conclusion: T-cell-depleted peripheral blood stem cell graft for haploidentical transplantation in acute leukemia may be an alternative treatment option. Larger prospective studies are needed to evaluate the outcomes of different manipulation techniques. Disclosures No relevant conflicts of interest to declare.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.057 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".