Efficacy and safety of follow-up field treatment of actinic keratosis with ingenol mebutate 0·015% gel: a randomized, controlled 12-month study
Bibliographic record
Abstract
BACKGROUND: Ingenol mebutate (IngMeb) is a novel patient-applied topical field therapy for actinic keratosis. OBJECTIVES: To demonstrate the efficacy and safety of follow-up IngMeb field treatment of actinic keratoses (AKs) present at 8 weeks after initial treatment or emerging in a previously cleared field. METHODS: In this phase III, randomized, double-blind study in patients with 4-8 clinically visible AKs within a contiguous 25-cm(2) treatment area on the face or scalp, all patients were treated initially with IngMeb 0·015% gel for three consecutive days. If lesions were present in the field at 8 weeks, or emerged at weeks 26 or 44, patients were randomized (2 : 1) to follow-up IngMeb or vehicle gel for three consecutive days. The main outcome was complete clearance rates of AKs 8 weeks after randomization. RESULTS: Of 450 patients who received initial treatment with IngMeb, 61·6% demonstrated complete clearance at 8 weeks. Patients with AKs present at 8 weeks or emerging at weeks 26 or 44 were randomized to IngMeb (n = 134) or vehicle (n = 69). IngMeb achieved a higher complete clearance rate than vehicle 8 weeks after randomization in AKs present at 8 weeks (46·7% vs. 18·4%; P < 0·01) and in emergent AKs (59·5% vs. 25·0%; P = 0·01). Based on those who completed 12 months of follow-up (n = 340), the overall 12-month clearance rate was estimated at 50·0%. Follow-up IngMeb treatment was well tolerated. CONCLUSIONS: This study demonstrated the long-term benefit of IngMeb 0·015% gel for initial and follow-up therapy of AKs.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".