Interpreting clinically significant changes in patient‐reported outcomes
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The goal of this study was to determine what magnitude of change in a patient-reported outcome score is clinically meaningful, so a clinicians' guide may be provided for estimating the minimal important difference (MID) when empiric estimates are not available. METHODS: Consecutive laryngeal cancer patients (n = 98) rated their quality of life (QOL) relative to other patients. These comparisons were contrasted with arithmetic differences in scores on the Functional Assessment of Cancer Therapy-Head and Neck (FACT-H&N) scale, Functional Assessment of Cancer Therapy-General (FACT-G) scale, 2 utility measures (the time tradeoff [TTO] and Daily Active Time Exchange [DATE]), and performance status (Karnofsky) scores. RESULTS: The FACT-H&N score needed to differ by 4% for average patients to rate themselves as "a little bit better" relative to other patients (95% CI, 1%-8%) and by 9% to rate themselves as "a little bit worse" relative to others (95% CI, 4%-13%). The corresponding values for other measures were FACT-G 4% (1%-7%) and 8% (95% CI, 5%-11%); TTO 5% (95% CI, 0%-11%) and 6% (95% CI, 0%-10%); DATE 5% (95%CI, 2%-9%) and 14% (95% CI, 0%-5%); Karnofsky 4% (95% CI, 1%-6%) and 10% (95% CI, 7%-13%). In each case, the minimal important difference (MID) was about 5% to 10% of the instrument range. CONCLUSIONS. One rule of thumb for interpreting a difference in QOL scores is a benchmark of about 10% of the instrument range. Patients appear to be more sensitive to favorable differences, so an improvement of 5% may be meaningful. This simple benchmark may be useful as a rough guide to meaningful change.
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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 it