A randomized phase 3b/4 study to evaluate concomitant use of topical ivermectin 1% cream and doxycycline 40-mg modified-release capsules, versus topical ivermectin 1% cream and placebo in the treatment of severe rosacea
Bibliographic record
Abstract
BACKGROUND: Randomized controlled studies of combination therapies in rosacea are limited. OBJECTIVE: Evaluate the efficacy and safety of combining ivermectin 1% cream (IVM) and doxycycline 40-mg modified-release capsules (ie, 30-mg immediate-release and 10-mg delayed-release beads) (DMR) versus IVM and placebo for treatment of severe rosacea. METHODS: This 12-week, multicenter, randomized, investigator-blinded, parallel-group comparative study randomized adult subjects with severe rosacea (Investigator's Global Assessment [IGA] score, 4) to receive either IVM and DMR (combination arm) or IVM and placebo (monotherapy). RESULTS: A total of 273 subjects participated. IVM and DMR displayed superior efficacy in reduction of inflammatory lesions (-80.3% vs -73.6% for monotherapy [P = .032]) and IGA score (P = .032). Combination therapy had a faster onset of action as of week 4; it significantly increased the number of subjects achieving an IGA score of 0 (11.9% vs 5.1% [P = .043]) and 100% lesion reduction (17.8% vs 7.2% [P = .006]) at week 12. Both treatments reduced the Clinician's Erythema Assessment score, stinging/burning, flushing episodes, Dermatology Life Quality Index score, and ocular signs/symptoms and were well tolerated. LIMITATIONS: The duration of the study prevented evaluation of potential recurrences or further improvements. CONCLUSION: Combining IVM and DMR can produce faster responses, improve response rates, and increase patient satisfaction in cases of severe rosacea.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".