Comparison of the <scp>EORTC QLQ</scp>‐<scp>BM22</scp> and the <scp>BOMET‐QOL</scp> quality of life questionnaires in patients with bone metastases
Bibliographic record
Abstract
AIMS: Bone metastases are a common complication of advanced cancer and often result in a decrease in patients' quality of life. Very few specific modules have been created to accurately assess quality of life in this patient group. The purpose of this study was to compare two questionnaires, the European Organization for Research and Treatment of Cancer quality of life questionnaire for patients with bone metastases (EORTC QLQ-BM22) and the bone metastases quality of life questionnaire (BOMET-QOL. METHODS: A literature search was conducted in Medline, Health and Psychosocial Instruments, Embase and Embase Classic to identify studies that discussed the development, validation and reliability of the (EORTC) QLQ-BM22 and the BOMET-QOL. Studies that discussed the development and validity of the questionnaire along with studies using these tools were included. RESULTS: Both questionnaires were developed in collaboration with patients and health-care professionals. The QLQ-BM22 is over twice the length of the BOMET-QOL, with 22 questions as compared to 10. The QLQ-BM22 has four subscales while the BOMET-QOL has no subscales. The QLQ-BM22 gives a more in-depth analysis of symptoms and well-being and includes issues such as mobility, side effects, complications of treatment and dependency. The BOMET-QOL is shorter and gives an overall assessment of pain and mobility. Scoring, item format, organization and response options vary between the questionnaires but the recall period for both is the previous week. Both questionnaires have been determined valid and reliable. CONCLUSION: The QLQ-BM22 and the BOMET-QOL are designed specifically for patients with bone metastases and each has strengths and weaknesses. Use of one over the other is ultimately dependent on trial design and investigators' goals.
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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 | 0.011 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".