Outcomes after biochemical or clinical progression in patients with multiple myeloma
Bibliographic record
Abstract
Almost all patients with multiple myeloma (MM) eventually relapse, either asymptomatically or with end-organ damage. However, it remains unclear whether initiating therapy at the time of biochemical progression (BP) improves the outcomes compared with initiating therapy at the clinical progression (CP) stage. Here, we retrospectively assessed 1347 patients with relapsed MM. Most progressions were BP (60.4%); 39.6% had CP. The most prevalent symptoms at relapse were new or evolving bone disease (80.9%), anemia (38.0%), and renal failure (12.7%). Patients with BP had longer median time from second-line treatment to the next treatment compared with patients who had CP (17.0 vs 9.6 months; P < .001) as well as longer median overall survival from first relapse (59.4 vs 26.2 months; P < .001). Male sex (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.02-2.18; P = .04), plasma cell labeling index ≥2% (OR, 1.58; 95% CI, 1.02-2.45; P = .04), and extramedullary disease at diagnosis (OR, 1.84; 95% CI, 1.08-3.13; P = .03) were associated with higher risk of CP, whereas very good partial remission or better had decreased risk of CP (OR, 0.62; 95% CI, 0.43-0.91; P = .02). To conclude, patients with CP have inferior postprogression outcomes compared with patients who have BP. Patients with deeper response to first-line therapy are less likely to develop CP. The presence of a specific CRAB (C, hypercalcemia; R, renal failure; A, anemia; B, bone disease) symptom at diagnosis predicts for the development of similar CRAB symptoms at relapse.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".