Kinetics of Autologous Stem Cell Mobilization Failure: Comparison of AMD3100/G-CSF, G-CSF, GM-/G-CSF, and Chemotherapy/G-CSF on Remobilization Success.
Bibliographic record
Abstract
Abstract Background: No standard approach for the mobilization of peripheral hematologic stem and progenitor cells (HSPCs) has been established. High levels of circulating CD34+ cells, a surrogate marker for mobilization efficiency, are associated with less apheresis days. A higher dose of CD34+ cell transfused after high-dose chemotherapy decreases time to hematologic recovery. Consequently, a better understanding of variables associated with mobilization kinetics may further optimize stem cell collection and reduce complications associated with autologous stem cell transplants. Methods: The Washington University (St. Louis, MO) transplantation database includes clinical parameters from 407 multiple myeloma (MM), 567 non-Hodgkin’s Lymphoma (NHL), and 164 Hodgkin’s disease (HD) pts who received an ASCT between 1995 and 2006. A retrospective analysis of this large pt population was conducted to determine factors associated with the mobilization kinetics of CD34+ cells. Results: Figure 1 summarizes the mobilization kinetics as defined by number of days to reach a target of 2 × 10^6 CD34+ cells/kg. Overall, the median number of aphereses to reach the target were 1, 2, and 2 in MM, NHL, and HD, respectively. Daily median CD34+ yields in MM pts were 3.8, 1.2, and 0.5 × 10^6 on day 1–3, respectively. In NHL pts, yields were 1.4, 0.8, and 0.4 × 10^6 on day 1–3. In HD pts, yields were 1.8, 0.8, and 0.3 × 10^6 on day 1–3, respectively. The addition of chemotherapy increased the % of pts requiring only a single apheresis to reach the mobilization target. Figure 2 summarizes the mobilization kinetics for each re-mobilization regimen. In general, a limited number of cells was collected with each aphereses; >70% of pts failed to mobilize 2 × 10^6 CD34+ cells/kg. In contrast, remobilization with AMD3100 allowed the collection of sufficient CD34+ cells in 67% of pts; median number of apheresis to reach the target was 3. Conclusions: Factors associated with mobilization kinetics of CD34+ cells include disease state and mobilization regimen. Re-mobilization is associated with high failure rates, re-mobilization regimens including AMD3100 are more successful. Figure 1: Mobilization kinetics by disease state Figure 1:. Mobilization kinetics by disease state Figure 2: Mobilization kinetics by re-mobilization regimen Figure 2:. Mobilization kinetics by re-mobilization regimen
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| 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".