A Survey of Patient Experience in CML: American and Canadian Perspectives
Bibliographic record
Abstract
Purpose: With treatment, chronic myeloid leukemia (CML) has a favorable prognosis, however, individuals with CML experience impairment to their quality of life (QoL). The aim of this study was to examine the perspectives and experiences of individuals with CML and to understand their challenges communicating with their CML physician. Patients and Methods: An online survey in adults with CML (n=100) in the US and Canada assessed QoL, patient-provider relationships, treatment satisfaction, and understanding of CML and treatment goals via the MD Anderson Symptom Inventory, the Cancer Therapy Satisfaction Questionnaire and de novo survey questions. Participants were recruited via an external patient recruiter and CML Patient Groups. Results: Many participants reported hardships due to CML and its treatment. The main impacts were on the ability to work (21%), engage in personal activities (e.g., hobbies, 28%), and to enjoy sexual relations (median=2.00, IQR=8.50). A substantial proportion (21-39%) wished to discuss additional topics with their providers (e.g., management of CML and/or its impacts). While participants reported satisfaction with therapy overall (median=85.71, IQR=17.86), they indicated low to moderate treatment satisfaction with specific components, including concerns regarding side effects (median=43.75, IQR=43.75). Participants generally had a good understanding of CML (97%) and its treatment goals (92%). Conclusion: These findings advance our understanding of issues that need improvement to support QoL for individuals living with CML. Future work is needed to improve patient-provider relationships, address treatment-related side effects, and provide clinical information that is easier for patients to understand.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".