Added value of health-related quality of life measurement in cancer clinical trials: the experience of the NCIC CTG
Bibliographic record
Abstract
Health-related quality-of-life (HRQoL) data are often included in Phase III clinical trials. We evaluate and classify the value added to Phase III trials by HRQoL outcomes, through a review of the National Cancer Institute of Canada Clinical Trials Group clinical trials experience within various cancer patient populations. HRQoL may add value in a variety of ways, including the provision of data that may contrast with or may support the primary study outcome; or that assess a unique perspective or subgroup, not addressed by the primary outcome. Thus, HRQoL data may change the study's interpretation. Even in situations where HRQoL measurement does not alter the clinical interpretation of a trial, important methodologic advances can be made. A classification of the added value of HRQoL information is provided, which may assist in choosing trials for which measurement of HRQoL outcomes will be beneficial.
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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 | 0.424 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".