Outcomes of Patients With Multiple Myeloma With deletion 1p Following Autologous Stem Cell Transplant
Bibliographic record
Abstract
BACKGROUND: Several studies have suggested that a deletion in the short arm of chromosome 1 (del(1p)) is an independent adverse prognostic factor in patients with multiple myeloma (MM). However, its impact on outcomes of patients undergoing autologous hematopoietic cell transplantation (autoHCT) and receiving contemporary anti-myeloma therapy remains unclear. STUDY DESIGN: A retrospective, single-center analysis of newly diagnosed MM (NDMM) patients with del(1p) who underwent upfront autoHCT between 2010 and 2021. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Propensity-matched comparisons were performed between del(1p) patients and a control group without del(1p) and with standard-risk cytogenetics. RESULTS: 55 patients were included in our analysis. With a median follow-up of 24.0 months (range 3.8-79.5), the median PFS was 30.2 months (95% CI 18.0-not reached [NR]) and the median OS was not reached (95% CI 41.1-NR). In multivariable analysis, female patients (hazard ratio [95% CI] 2.81 [1.14, 6.91], P = .025) and those with R2-ISS stage IV (compared with stage II 4.85 [1.01, 23.34], P = .049) had worse PFS, whereas patients who achieved CR as the best post-transplant response had better PFS (0.38 [0.16, 0.91], P = .029). Concomitant del(17p) was associated with a significantly worse OS (4.47 [1.18, 17.02], P = .028). Propensity score matching showed no significant differences in PFS (1.63 [0.86, 3.10], P = .13) or OS (1.77 [0.73, 4.32], P = .21) between del(1p) and control patients. CONCLUSIONS: In NDMM patients undergoing upfront autoHCT, del(1p) alone was not significantly associated with inferior outcomes. However, concurrent del(17p) and del(1p) was associated with worse survival.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".