Minimal Clinically Important Differences in Pharmacological Trials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The concept of a minimal clinically important difference (MCID) is well established. Here, we review the evidence base and methods used to define MCIDs as well as their strengths and limitations. Most MCIDs in chronic obstructive pulmonary disease (COPD) are empirically derived estimates applying to populations of patients. Validated MCIDs are available for many commonly used outcomes in COPD, including lung function (100 ml for trough FEV1), dyspnea (improvement of ≥ 1 unit in the Transition Dyspnea Index total score or 5 units in the University of California, San Diego Shortness of Breath Questionnaire), health status (reduction of 4 units in the St George's Respiratory Questionnaire total score), and exercise capacity (47.5 m for the incremental shuttle walking test, 45-85 s for the endurance shuttle walking test, and 46-105 s for constant-load cycling endurance tests), but there is currently no validated MCID for exacerbations. In a clinical trial setting, many factors, including study duration, withdrawal rate, baseline severity, and Hawthorne effects, can influence the measured treatment effect and determine whether it reaches the MCID. We also address recent challenges presented by clinical trials that compare active treatments and suggest that MCIDs should be used to identify the additional proportion of patients who benefit, for example, when one drug is replaced by another or when a second drug is added to a first. We propose the term "minimum worthwhile incremental advantage" to describe this parameter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it