Safety and Efficacy of Photodynamic Therapy with ALA 10% Topical Gel Activated by Red Light versus ALA 20% Topical Solution Activated by Blue Light for the Treatment of Actinic Keratosis on the Upper Extremities: A Blinded Randomized Study
Bibliographic record
Abstract
Background: Actinic keratosis (AKs) is a pre-cancerous skin neoplasm that can appear as erythematous to pink scaly plaques at sites of ultraviolet light damage. Photodynamic therapy (PDT) using aminolaevulinic acid (ALA) 10% gel activated by red light is approved by the FDA for the treatment of AKs on the face and scalp, and ALA 20% solution activated by blue light is approved for PDT treatment of AKs on the face, scalp, and upper extremities. While both options have been proven to an effective treatment on the upper extremity, there has been no direct side-by-side comparison. This study aimed to compare the safety and efficacy of both PDT on the upper extremities. Design: This was a prospective, single-center, split-arm randomized clinical trial with 20 adult subjects presenting with 4-17 clinically confirmed mild-moderate AKs (Olsen grading) on each distal upper extremity. Subjects were treated with ALA 10% gel/red light and ALA 20% solution/blue light PDT on respective randomly selected upper extremities. Lesion complete clearance rate (LCCR) served as the primary endpoint. Secondary endpoints included complete clearance per patient side (PatCR), LCCR of moderate lesions, LCCR 12 weeks after PDT-1, PatCR 12 weeks after PDT-1, overall cosmetic outcome assessed by the investigator, and patient satisfaction. Results: The LCCR was significantly greater for ALA10% vs. ALA20% at Day 120; no significant differences were observed at the other observed time points. 30 patients were enrolled in the study and received their first treatment (PDT1). LCCRs after PDT1 were 65.4% and 58.4% for ALA10% and ALA 20%, respectively. 25 patients received a second treatment (PDT2), resulting in LCCRs of 88.2% and 72.1% respectively. 22 patients returned for follow-up 6 months after their last PDT treatment (PDT1 or PDT2), with LCCR of 83.7% (ALA10%) and 79.3% (ALA20%). 17 patients returned for follow-up 12 months after the last PDT treatment, with LCCRs of 81.5% (ALA10%) and 87.6% (ALA20%). There were no statistical differences between ALA10% and ALA20% for subject-reported pain or satisfaction ratings. ALA10% was rated as significantly easier to apply compared to ALA20% by the investigator. Conclusion: Both ALA10% and ALA20% appear to be safe and effective for PDT treatment of AKs on the upper extremities. There is a trend for increased efficacy with ALA10%, and it may be easier to apply. Additional data is in the process of being collected as the study continues.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".