Critical review of the manner in which the efficacy of therapies for rosacea are evaluated
Bibliographic record
Abstract
BACKGROUND: Rosacea is a relatively common disorder that may affect individuals of all races, particularly those of northern European decent. Its onset generally occurs in individuals between the ages of 20 and 50 years. Rosacea may be classified into four subtypes and one variant. Although individuals with rosacea may not pass through all of the stages, the primary features of the disorder include frequent flushing and blushing, nontransient erythema, the presence of papules and pustules, and telangiectasia. Many agents have been used to treat rosacea stigmata, especially because none of these is uniformly effective. AIM: To identify the parameters that are used to evaluate the response to therapy when different agents are used to treat rosacea. For a given parameter, to determine whether the different trials are consistent in the manner in which this variable is measured. METHODS: The reports on the efficacy and safety of the different drug therapies used to treat rosacea were identified. We searched MEDLINE (1966 to June 2002) for studies where rosacea was treated. The parameters used to evaluate the efficacy of therapy were determined. For each parameter, the ways in which it has been measured were identified. RESULTS: Efficacy of treatment is generally judged by evaluating the effect of the intervention on papules and pustules, erythema, and telangiectasia. Manual lesional counts of papules and pustules are usually performed. There is, however, substantial variation in the methodology chosen for comparison of erythema and telangiectasias. Color scales are popular for erythema and telangiectasia, while grading scales are most commonly used for physician and patient evaluations. CONCLUSIONS: For each of the parameters that are commonly used to measure the efficacy of treatments for rosacea, the different approaches by which it has been measured in the various trials have been highlighted; these dissimilarities can make it problematic to compare between clinical trials. A greater degree of uniformity in the manner in which the various parameters are evaluated would enable a more objective comparison between the studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".