Management of Nail Disease in Patients With Psoriatic Arthritis: An Updated Literature Review Informing the 2021 GRAPPA Treatment Recommendations
Bibliographic record
Abstract
OBJECTIVE: Nail psoriasis is common, impairs fine motor finger functioning, affects cosmesis, and is associated with a lower quality of life. This review updates the previous Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations for nail psoriasis. METHODS: This systematic literature review of the PubMed, MEDLINE, Embase, and Cochrane databases examined the updated evidence since the last GRAPPA nail psoriasis treatment recommendations published in 2014. Recommendations are based on preformed PICO (Patient/Population - Intervention - Comparison/Comparator - Outcome) questions formulated by an international group of dermatologists, rheumatologists, and patient panel members. Data from this literature review were evaluated in line with Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology. RESULTS: Overall, there is insufficient evidence to make any recommendation for the use of topical corticosteroids, topical calcipotriol, topical tazarotene, topical cyclosporine, dimethyl fumarates/fumaric acid esters, phototherapy, and alitretinoin. There is a low strength of evidence to support the use of calcipotriol and corticosteroid preparations, topical tacrolimus, oral cyclosporine, oral methotrexate, intralesional corticosteroids, pulsed dye laser, acitretin, Janus kinase inhibitors, and apremilast. CONCLUSION: The highest strength of supporting evidence is for the recommendation of biologic agents including tumor necrosis factor inhibitors, and interleukin 12/23, 17, and 23 inhibitors.
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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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".