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Record W4416195856 · doi:10.25251/9sm0xp66

Safety and Efficacy of Photodynamic Therapy with Aminolevulinic Acid 10% Topical Gel Activated by Red Light versus Aminolevulinic Acid 20% Topical Solution Activated by Blue Light for the Treatment of Actinic Keratosis on the Upper Extremities: A Blinded Randomized Study

2025· article· W4416195856 on OpenAlexaff
Payvand Kamrani, Maya Firsowicz, Misha Zarbafian, Kavita Darji, Raheel Zubair, Lisa E. Ishii, Mitchel P. Goldman, Monica Boen

Bibliographic record

VenueSKIN The Journal of Cutaneous Medicine · 2025
Typearticle
Language
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsCovenant Health
Fundersnot available
KeywordsPhotodynamic therapyActinic keratosisActinic keratosesIntense pulsed lightRed lightClinical endpointBlue lightClinical trial

Abstract

fetched live from OpenAlex

Introduction: Actinic keratoses (AKs) are common precancerous skin lesions resulting from chronic sun exposure and carry the potential to progress into squamous cell carcinoma if left untreated. Photodynamic therapy (PDT) is a well-established, non-invasive treatment option for AKs. Currently, PDT with 10% aminolevulinic acid (ALA) gel activated by red light is FDA-approved for the treatment of AKs on the face and scalp, while PDT with ALA 20% solution activated by blue light is FDA-approved for AKs on the face, scalp, and upper extremities. Although both PDT treatment regimens have demonstrated clinical effectiveness for treating AKs on the upper extremities, no head-to-head studies have directly compared their relative efficacy and safety using the recommended incubation times and light sources. The purpose of this study was to compare the safety, tolerability, and efficacy of both therapeutic combinations for PDT treatment of AKs on the upper extremities. Methods: This was a prospective, single-center, split-arm randomized clinical trial involving 30 adults, each with 4-17 clinically confirmed mild-to-moderate AKs on both distal upper extremities (graded by Olsen criteria). Each participant received PDT with 10% ALA gel plus red light on one arm and 20% ALA solution plus blue light on the contralateral arm, with side assignment randomized. The primary endpoint was total lesion clearance rate (TLCR) at 12 weeks after the first PDT. Secondary endpoints included TLCR for moderate grade 3 lesions, TLCR at 6- and 12-months after the last PDT, investigator-assessed cosmetic outcomes, and patient-reported satisfaction. Results: Of the 30 enrolled patients, 27 completed the study. Mixed-effects statistical analysis showed significant improvement in TLCR for both treatment arms (p<0.0001). At 6 months post-2 PDT treatments, TCLR was 87.6% with 10% ALA gel and 84.5% with 20% ALA solution. At 12-months, TLCR was 90.5% for 10% ALA gel and 86.9% for 20% ALA solution. Although differences were not statistically significant, 10% ALA gel demonstrated a trend toward higher clearance of grade 3 AK lesions (94.12%) compared with 20% ALA (88.24%). No statistical differences were observed between groups in patient-reported pain or satisfaction ratings. Moderate erythema occurred more frequently in the 10% ALA gel group (41.5%) than with the 20% ALA solution group (23.6%), though this difference was not statistically significant. All erythema resolved, and no serious adverse events were reported. Conclusion: This study represents the first direct, head-to-head comparison of 10% ALA gel with red light and 20% ALA solution with blue light for the treatment of AKs on the upper extremities. Both regimens were safe, well tolerated, and achieved high lesion clearance rates. A trend toward greater efficacy was observed with 10% ALA gel in the management of grade 3 lesions, potentially related to a stronger post-PDT inflammatory response, as indicated by higher rates of erythema. Overall, both regimens were effective treatment options, with 10% ALA gel offering additional advantages in ease of application as a field therapy and potentially higher clearance rates in patients with more severe AKs.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.302
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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