Optimal infused CD34+ cell dose in multiple myeloma patients undergoing upfront autologous hematopoietic stem cell transplantation
Bibliographic record
Abstract
Abstract Autologous transplantation remains the standard of care for eligible multiple myeloma (MM) patients, yet optimal CD34+ cell dose remains unclear. We conducted a retrospective study on MM patients undergoing upfront transplant between 2005 and 2021 and divided them into low (≤2.5 × 106 cells/kg) and high (>2.5 × 106 cells/kg) CD34+ dose groups. We included 2479 patients, 95 in the low CD34+ group and 2384 in the high CD34+ group. Patients in the low CD34+ group were older (63.2 vs 61.1 years, p = 0.013), more often had R-ISS III (19% vs 9%, p = 0.014), received plerixafor (60% vs 35%, p < 0.001) and transplanted after 2009 (88% vs 80%, p = 0.047). Time to neutrophil and platelet recovery was longer in the low CD34+ group. Median PFS and OS were lower in the low CD34+ group (31.6 vs. 43.6 months, p = 0.011 and 76.4 vs. 108.2 months, p < 0.001, respectively). Evaluation of incrementally higher CD34+ dose did not show significant improvement in survival at thresholds >2.5 × 106 cells/kg. Multivariable analysis affirmed that CD34+ >2.5 × 106 cells/kg was associated with better PFS (HR 0.71, p = 0.008) and OS (0.59, p < 0.001). After propensity score matching, a CD34+ dose >2.5 × 106 cells/kg remained a predictor of better OS (0.42, p < 0.001). In conclusion, CD34+ dose >2.5 × 106 cells/kg was associated with improved survival, without any additional benefit at incrementally higher doses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".