Outcomes of Standard-Risk Multiple Myeloma Patients Who Undergo Upfront Autologous Hematopoietic Stem Cell Transplantation
Bibliographic record
Abstract
Patients with multiple myeloma (MM) without high-risk cytogenetic abnormalities are classified as having standard-risk MM (SRMM), and data focusing on their outcomes after autologous hematopoietic stem cell transplantation (autoHCT) are limited. We sought to evaluate survival outcomes for patients with SRMM receiving autoHCT, and to elucidate factors that impact these outcomes. This was a single-center retrospective analysis that included consecutive MM patients who received upfront autoHCT between 2013 and 2021, had available cytogenetic information and had no high-risk chromosomal abnormalities on fluorescence in situ hybridization, defined as t(4;14), t(14;16), del(17p) or 1q21 gain or amplification. A total of 1000 SRMM patients were included, with a median age of 61 years (range 25 to 83), and 61% were male (n = 612). The most common induction regimens were bortezomib/lenalidomide/dexamethasone (VRD; n = 398, 40%) and carfilzomib/lenalidomide/dexamethasone (KRD; n = 212, 21%), and the majority (87%) received single-agent melphalan as conditioning. After induction and before autoHCT, 16% and 57% achieved ≥complete response (CR) and ≥very good partial response (VGPR), respectively. At day 100 post autoHCT, 37% and 77% achieved ≥CR and ≥VGPR, respectively. Sixty-two percent and 89% of patients achieved ≥ CR and ≥VGPR as best response post-transplant. A minimal residual disease (MRD) negative response pre- and post-transplantation was achieved in 43% (401/936) and 64% (199/311) of patients, respectively. After a median follow-up of 42.1 months, the median progression-free survival (PFS) for the entire cohort was 68.3 months (95% CI 60.1 to 72.1), and the median overall survival (OS) was not reached (95% CI 102.3-not reached). The 5-year PFS and OS rates were 55% and 83%, respectively. In multivariable analysis, achieving MRD-negative CR prior to autoHCT (HR 0.65 [95% CI 0.44 to 0.97], P = .033) or as best response (0.52 [0.34 to 0.78], P = .002), and use of post-transplant maintenance (0.69 [0.52 to 0.93], P = .013) and lenalidomide-based combination maintenance (0.68 [0.48 to 0.96], P = .030) were associated with improved PFS, whereas use of an induction regimen other than KRD was associated with worse PFS (1.50 [1.04 to 2.17], P = .031). For OS, post-transplant maintenance (0.48 [0.32 to 0.70], P < .001) was associated with better survival in multivariable analysis, whereas R-ISS stage III, compared with stage I, (2.34 [1.01 to 5.43], P = .047) was associated with worse OS. Patients with SRMM who received upfront autoHCT had a median PFS of >5.5 years, and median OS was not reached. These results highlight the favorable outcomes with upfront autoHCT for patients with SRMM, serving as a benchmark for future therapeutic approaches in this subgroup of MM patients.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".