Comparable outcome of stem cell transplant versus bortezomib-based consolidation in myeloma patients after major response to induction
Bibliographic record
Abstract
High-dose therapy with autologous stem cell transplant (ASCT) has been established as standard treatment for eligible patients with myeloma. However, whether this approach is still beneficial with new therapy is yet to be determined. Consolidation of effective therapy may be an alternative to ASCT following major response to initial induction. This retrospective case-series analysis included a total of 48 patients with newly diagnosed myeloma. All these patients achieved complete response or very good partial response to bortezomib-based induction and were eligible for ASCT; 24 of these patients proceeded with ASCT, and other 24 patients opted out of ASCT and received two additional cycles of bortezomib therapy as consolidation. With a median follow-up of 28.5 months in ASCT group and 29 months in non-ASCT group, no significant difference was seen in progression-free survival, 39 versus 32 months, P = 0.82. Median overall survival had not been reached, and the estimated 3-year overall survival rates were 87.5 and 67.5% in ASCT and non-ASCT, respectively, P = 0.97. This study provides an initial assessment of survival outcome of ASCT in comparison with non-ASCT consolidation. The additional study is required to establish the efficacy of non-ASCT consolidation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".