Serum BCMA levels predict outcomes in MGUS and smoldering myeloma patients
Bibliographic record
Abstract
Soluble BCMA (sBCMA) levels are elevated in monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). However, the association between sBCMA levels and prognosis in MGUS and SMM has not been studied. We retrospectively analyzed sBCMA levels in stored samples from 99 MGUS and 184 SMM patients. Baseline sBCMA levels were significantly higher in MGUS and SMM patients progressing to MM during clinical follow up. When stratified according to the median baseline sBCMA level for each cohort, higher levels were associated with a shorter PFS for MGUS (HR 3.44 comparing sBCMA ≥77 vs <77 ng/mL [95% CI 2.07-5.73, p < 0.001] and SMM (HR 2.0 comparing sBCMA ≥128 vs <128 ng/mL, 95% 1.45-2.76, p < 0.001) patients. The effect of sBCMA on PFS was similar even after adjusting for the baseline MGUS or SMM risk stratification. We evaluated paired serum samples and found that sBCMA increased significantly in MGUS and SMM patients who eventually progressed to MM, whereas among MGUS non-progressors the sBCMA level remained stable. While our results require independent validation, they suggest that sBCMA may be a useful biomarker to identify MGUS and SMM patients at increased risk of progression to MM independent of the established risk models.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".