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Record W1839380768 · doi:10.1177/1203475415591936

Efficacy of Topical Calcineurin Inhibitors in Oral Lichen Planus

2015· review· en· W1839380768 on OpenAlexaff
Bahman Sotoodian, Jacky Lo, Andrew N. Lin

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2015
Typereview
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsPimecrolimusCalcineurinTacrolimusMedicineOral lichen planusDermatologyAdverse effectTriamcinolone acetonideClinical trialProtein synthesis inhibitorPlaceboPharmacologyInternal medicineSurgeryTransplantationAntibacterial agentPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Oral lichen planus (OLP) is associated with severe pain and significant impairment for patients. OBJECTIVE: To evaluate the safety and efficacy of topical calcineurin inhibitors (TCI) in the treatment of OLP. METHODS: Medline and the Cochrane Database were searched using the keywords "calcineurin inhibitor OR tacrolimus OR pimecrolimus" AND "oral lichen planus." RESULTS: Four retrospective studies that looked at the effects of tacrolimus on OLP; 4 randomized, double-blind clinical trials (RDBCT) comparing tacrolimus with topical corticosteroids; and 5 RDBCT comparing pimecrolimus with placebo or triamcinolone were noted. Six open prospective and multiple case reports assessing the efficacy of calcineurin inhibitor for treatment of diverse types of OLP were found. CONCLUSION: There is strong evidence to suggest that the use of tacrolimus 0.1% ointment and pimecrolimus 1% cream is superior or equally efficacious as traditional therapies for OLP. Topical calcineurin inhibitors are well tolerated, with no significant systemic adverse effects.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.126
GPT teacher head0.412
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations62
Published2015
Admission routes1
Has abstractyes

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