Comparison of therapeutic agents' short‐term effects on facial and scalp actinic keratosis: A network meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Care for actinic keratosis (AK) can be improved with more knowledge on the relative of effect of indicated therapies. OBJECTIVES: Using network meta-analyses, we quantitatively determined the comparative "short-term" effects of interventions in adults with facial and scalp AK. METHODS: On February 28, 2023, evidence from the peer-reviewed literature was systematically obtained from OVID, the Cochrane Central Register of Controlled Trials and ClinicalTrials.gov. We analyzed data from studies published in English, of a trial design, and investigating the effect of an actinic keratosis monotherapy. Patient complete clearance, patient partial clearance or lesion-specific clearance across adults were analyzed at 8-12 weeks after therapy. Patient complete clearance pertained to proportion of participants who experienced complete clearance of actinic keratosis lesions; patient partial clearance corresponded to percentage of subjects who achieved at least 75% clearance of actinic keratosis lesions; lesion-specific clearance represented the percentage of all lesions that were cleared. In the main (i.e., base) analyses, nodes were analyzed only at the level of the agent. RESULTS: Data from a total of 84 studies were used-across which 22 active agents were identified. Estimates of interventions' surface under the cumulative ranking curve rankings and (pairwise) relative effects were estimated. Across the three outcomes, fluorouracil 5% was ranked the most effective. CONCLUSIONS: Our work is the first to provide information on covariate-adjusted relative effects of actinic keratosis therapies- including the more recently reported treatments-for the face and scalp; this knowledge may help physicians and patients make more informed decisions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".