Optimizing Anti-Inflammatory and Immunomodulatory Effects of Corticosteroid and Vitamin D Analogue Fixed-Dose Combination Therapy
Bibliographic record
Abstract
Fixed-dose combination topical therapy with corticosteroid and vitamin D analog provides effective treatment and possible long-term management of psoriasis. The anti-inflammatory and immunomodulatory effects of corticosteroids and vitamin D analogs in treating psoriasis are well investigated; their complementary effects lead to the disruption of the inflammatory feedback loop underlying psoriasis pathogenesis. Recent preclinical data showed that combination therapy is more effective than monotherapies of the active ingredients in preventing activation of resting pro-inflammatory cells, inducing immunomodulation, reducing inflammatory responses by regulating T cell production, and normalizing keratinocytes. The increased understanding of the mechanism of action of fixed-dose combination therapy from preclinical studies is supported by several clinical studies. As the efficacy of topical therapy is correlated with the skin penetration of the active ingredients, new drug delivery systems have been developed. The fixed-dose combination Cal/BD aerosol foam creates a modified supersaturated formulation when applied to the skin, which is maintained for at least 26 h in the laboratory setting. Clinical studies have demonstrated superior efficacy of fixed-dose combination calcipotriol (Cal) 50 µg/g and betamethasone dipropionate (BD) 0.5 mg/g aerosol foam compared with monotherapies of the active ingredients. Furthermore, Cal/BD aerosol foam has shown significantly improved efficacy compared with more traditional formulations, such as Cal/BD ointment and gel, in other studies. Calcipotriol also mitigates risks associated with betamethasone dipropionate and vice versa, resulting in the favorable safety profile observed with fixed-dose combination treatment. Recent data also suggest that fixed-dose combination treatment could provide long-term management of psoriasis, although further clinical investigations are needed. Overall, these data support the value of fixed-dose combination therapy of corticosteroid and vitamin D analog and highlight the added potential of innovative drug delivery for the treatment of psoriasis. FUNDING: LEO Pharma.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".