The impact of age on survival and excess mortality after autologous hematopoietic cell transplantation in newly diagnosed multiple myeloma patients
Bibliographic record
Abstract
Despite the availability of novel agents, autologous hematopoietic cell transplantation (auto-HCT) remains the standard of care in newly diagnosed multiple myeloma (MM) patients. The impact of age on overall survival (OS), progression-free survival (PFS), relapse incidence, non-relapse mortality (NRM), and excess mortality (taking account of general population mortality) was investigated using information on 61,797 MM patients transplanted between 2013 and 2017. The median age at auto-HCT was 60.8 (range, 18.1-83.2) years of whom 2.0% were 18-39 years, 68.9% 40-64 years, 21.8% 65-69 years, 6.5% 70-74 years, and 0.8% ≥75 years of age, respectively. The corresponding OS probabilities at 3 years were 85.9%, 82.8%, 81.1%, 78.4%, and 74.8%, respectively (P<0.001). Excess mortality cumulative incidences were 13.1%, 15.0%, 14.6%, 15.0%, and 14.1% at 3 years, respectively (P=0.67). In multivariable analyses, older age was a significant risk factor for OS, PFS, and NRM but not for excess mortality or relapse risk. Our results indicate that advanced age alone should not preclude the use of auto- HCT in patients with MM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".