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Record W4414327069 · doi:10.58931/cdt.2025.63144

Off-Label Isotretinoin in Dermatologic Conditions: Doses, Duration, and Data

2025· article· en· W4414327069 on OpenAlexaffabout
Fiona Lovegrove

Bibliographic record

VenueCanadian dermatology today. · 2025
Typearticle
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsProbity Medical ResearchWestern University
Fundersnot available
KeywordsIsotretinoinAcneAdverse effectAcne treatmentClinical PracticeClinical trialPharmacodynamics

Abstract

fetched live from OpenAlex

Isotretinoin, also known as 13-cis-retinoic acid, has been a mainstay in dermatologic practice since its introduction in the early 1980s. Approved by Health Canada for the treatment of severe acne vulgaris, including recalcitrant nodular acne and acne conglobata, isotretinoin has since been repurposed for a wide variety of other skin conditions. Early clinical trials using an average maximum dose of 1.2 mg/kg/day over a 16 week period demonstrated significant efficacy, with 95% of patients showing clinical improvement and 84% achieving complete clearance. Traditional isotretinoin regimens involved an initial dose of 0.5 mg/kg/day for 2–4 weeks, followed by maintenance therapy ranging from 0.1–1 mg/kg/day (up to a maximum of 2 mg/kg/day) over a total course of 12–16 weeks. However, findings from a larger dose-ranging study highlighted that side effects such as xerosis were dose-dependent, yet recurrence rates reached 42% in patients treated with 0.1 mg/kg/day, suggesting the need to carefully balance efficacy and side-effect risks when prescribing isotretinoin. More recently, micronized isotretinoin formulations and a better understanding of its pharmacodynamics have led to more widespread use of low-dose regimens. These offer similar efficacy with fewer adverse effects, better tolerability, and improved adherence.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.313
Teacher spread0.293 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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