Therapeutic Options for the Treatment of Darier’s Disease: A Comprehensive Review of the Literature
Bibliographic record
Abstract
Darier's disease (also known as keratosis follicularis or dyskeratosis follicularis) is an autosomal dominant inherited disorder which manifests as hyperkeratotic greasy papules in the first or second decade of life. Aside from symptom management and behavioral modifications to avoid triggers, there are currently no validated treatments for Darier's disease (DD). However, a variety of treatments have been proposed in the literature including retinoids, steroids, vitamin D analogs, photodynamic therapy, and surgical excision. The purpose of this review article is to identify therapeutic options for treating DD and to outline the evidence underlying these interventions. A search was conducted in Medline for English language articles from inception to July 4, 2020. Our search identified a total of 474 nonduplicate studies, which were screened by title and abstract. Of these, 155 full text articles were screened against inclusion/exclusion criteria, and 113 studies were included in our review. We identified Grade B evidence for the following treatments of DD: oral acitretin, oral isotretinoin, systemic Vitamin A, topical tretinoin, topical isotretinoin, topical adapalene gel, topical 5-flououracil, topical calciptriol and tacalcitol (with sunscreen), grenz ray radiation, and x-ray radiation. All other evidence for treatments of DD consisted of case reports or case series, which is considered grade C evidence. Considering the quality and quantity of evidence, clinicians may consider initiating a trial of select topical or oral retinoids first in patients with localized or generalized DD, respectively.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".