Treatment preferences of patients with relapsed and refractory multiple myeloma: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Multiple myeloma is a haematological malignancy characterized by significant morbidity and mortality. This study sought to develop an in-depth understanding of patients' lived experiences of relapsed or refractory multiple myeloma (RRMM) and its treatment, and to identify which features of treatment were most important to them. METHODS: Qualitative interviews and focus groups (FGs) were conducted with 32 people living with RRMM across Canada. In Phase 1, interviews focused on participants' accounts of their experiences with the disease and its treatment and laid the groundwork for the FGs (Phase 2). The FGs developed a deeper understanding of patients' treatment priorities. Interview and FG transcripts were coded for emergent themes and patterns. RESULTS: The interviews identified important side effects that had significant impacts on patients' lives, including physical, cognitive, and psychological/emotional side effects. Participants also identified specific treatment features (attributes) that were important to them. These were compiled into a list and used in the FGs to understand patients' priorities. Higher prioritized attributes were: life expectancy, physical and cognitive side effects, and financial impact. Mode of administration, treatment intervals, psychological side effects, and sleep/mood effects were identified as lower priorities. CONCLUSIONS: RRMM and its treatments impact importantly on patients' quality-of-life across a range of domains. Patients prioritized treatment features that could enhance life expectancy, minimize side effects and offset financial burdens. IMPLICATIONS FOR CANCER SURVIVORS: A clear articulation of patient priorities can contribute to efforts to design treatment with patients' concerns in mind, thereby promoting a more patient-centered approach to care.
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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".