Kinetics of response to first‐ and second‐line therapies in multiple myeloma: Assessment by both M‐spikes and light chains
Bibliographic record
Abstract
OBJECTIVES: The prognostic value of kinetics of response to multiple myeloma (MM) therapy is controversial. We aimed to expand the knowledge on this topic by reviewing the kinetics of response to both first- and second-line MM therapy, utilizing a homogeneously treated cohort and analyzing separately both M-spike and light chain (LC) responses for each patient. METHODS: We reviewed all patients who received first-line cyclophosphamide, bortezomib and dexamethasone induction followed by autologous transplant with melphalan and lenalidomide maintenance in our center between 2007 and 2019. RESULTS: Analyzing 360 patients, we observed no correlation between response kinetics to first- versus second-line therapy at the individual patient level. Time to best response to first-line therapy was not a predictor of outcome; however, longer time to best response was highly predictive of a favorable outcome in the second-line setting, independent of other factors. Patients with IgA-MM cleared their M-spike faster than IgG-MM, probably reflecting different half-lives of these isotypes rather than disease biology, as the clearance of LC in both subtypes was similar. CONCLUSIONS: Analyzing both M-spike and LC responses in a homogenously treated cohort, we identified important insights regarding the prognostic value of kinetic patterns. Prospective analysis may shed more light on unsolved questions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".