The prevalence and outcomes of frail older adults in clinical trials in multiple myeloma: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multiple myeloma (MM) is an incurable blood cancer that primarily affects older adults. Several frailty tools have been developed to address the heterogeneity of aging in this population. Uptake of these measures has been variable, leading to a gap in knowledge regarding the proportion of enrolled trial participants considered frail and uncertainty in the treatment-related effects and outcomes among this high-risk population. We performed a systematic review of therapeutic interventional MM clinical trials reporting on frailty. We included 43 clinical trials (24 randomized controlled trials and 19 non-randomized trials) which met eligibility criteria. Frailty was increasingly incorporated in studies in more recent years with 41.9% of included studies being reported in the last two years. Commonly used frailty tools included the International Myeloma Working Group (IMWG) frailty index (41.8%), and the simplified frailty score (39.5%). Frailty status was categorized with 3 levels as (frail, intermediate fit, or fit) in 51.2% of the studies and dichotomized (frail, non-frail) in 18.6% of studies. Frailty prevalence greatly varied across trials ranging from 17.2% to 73.6% of the cohort. Of the included studies, 72.0% conducted subgroup analysis (planned or post-hoc) based on frailty status. Most studies demonstrated a consistent benefit of MM interventions among the frail and non-frail populations, however in general, frail patients had worse outcomes compared to the fit. Although frailty is increasingly being incorporated in MM clinical trials, due to the variation in both the definition and categorization of frailty, there remains heterogeneity in the prevalence of frailty and its potential associated impact on outcomes.
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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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it