Decision-making factors for an autologous stem cell transplant for older adults with newly diagnosed multiple myeloma: A qualitative analysis
Bibliographic record
Abstract
Purpose: A utologous stem cell transplant (ASCT) remains a standard of care among older adults (aged ≥65) with multiple myeloma (MM). However, heterogeneity in the eligibility and utilization of ASCT remains. We identified decision-making factors that influence ASCT eligibility and utilization among older adults with MM. Methods: A qualitative study across two academic and two community centres in Ontario was conducted between July 2019-July 2020. Older adults with MM (newly diagnosed MM aged 65-75 in whom a decision had been made about ASCT in <12 months) and treating oncologists completed a baseline survey and a subsequent interview, which was analyzed using thematic analysis. Results: Eighteen patients completed the survey and 9 follow-up interviews were conducted. Patients were happy with their treatment decision with "trust in their oncologist" and "wanting the best treatment" as the most important to proceed with ASCT. "Afraid of side effects" was the most common reason for declining ASCT. Fifteen oncologists completed the survey and 10 follow-up interviews were conducted. Most relied on the 'eye-ball' test for ASCT eligibility over geriatric screening tools. The lack of both high-quality evidence and local guidelines impacted decision-making. Both oncologists and patients felt that chronological age alone should not affect ASCT eligibility. Conclusion: While decision-making factors regarding ASCT can be variable, both oncologists and patients indicated that chronological age alone should not represent a barrier for ASCT among older adults. Future simplification and incorporation of ASCT eligibility geriatric assessment tools in studies as well as the inclusion of these tools in local guidelines may further improve ASCT decision-making.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".