Genomic Aberrations and Survival of Patients with Light-Chain-Only Multiple Myeloma Undergoing Autologous Stem Cell Transplantation
Bibliographic record
Abstract
The majority of patients with multiple myeloma (MM) have intact immunoglobulin, but in a subset of patients (∼15%), their tumors produce monoclonal light chains only (LCO). Although specific genomic aberrations have emerged as a major prognostic factor in MM, their incidence and prognostic impact on LCO myeloma patients are not clear. We therefore investigated a cohort of 86 LCO MM cases diagnosed and treated with autologous stem cell transplantation at our institution. Overall, genomic risk factors del(13q), del(17p), t(4;14), 1p loss, and 1q21 gain were detected by cytoplasmic fluorescence in situ hybridization (cIg-FISH) in 40.6%, 18.5%, 11.9%, 18.8%, and 25% of the cases, respectively. Patients with del(13q) and 1q gains had a significantly shorter overall survival (OS) (median 80.4 vs 56.2 months, P = .021; median 77.9 vs 26.9 months, P = .006, respectively) and shorter progression-free survival (PFS) (median 33.4 vs 15.8 months, P = .002; median 33.4 vs 19.1 months, P = .011, respectively) than those without the genetic abnormalities. In addition, 1p loss was significantly associated with shorter PFS (median 37.9 vs 18.2 months, P = .001). There was no significant difference in PFS or OS in patients with or without t(4;14) or del(17p). On multivariate analysis, del(13q) was an independent prognostic factor for PFS and OS.
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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 | 0.001 |
| 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".