In Search of Predictive Indicators for the Development of Psoriatic Arthritis in Patients with Cutaneous Psoriasis: The Path Traversed and the Road Ahead
| Author | Malvika Shastri | en |
| Author | Gitanjali Wahengbam | en |
| Author | Muskan Arora | en |
| Author | Pragati Pandey | en |
| Author | Ayush Sharma | en |
| Author | Aman Sharma | en |
| Author | Sunil Dogra | en |
| Author | Seema Chhabra | en |
| Orcid | Malvika Shastri [0000-0001-9858-7935] | en |
| Orcid | Sunil Dogra [0000-0001-9912-0085] | en |
| Orcid | Seema Chhabra [0000-0003-2925-5608] | en |
| Issued Date | 2024-12-31 | en |
| Abstract | Context: Psoriatic arthritis (PsA), a seronegative, irreversible inflammatory arthritis, displays a heterogeneous clinical presentation that frequently impedes early detection of PsA. Objectives: Since extensive inflammatory and musculoskeletal damage makes early therapeutic intervention quite challenging, this study was conducted to include and review all available markers, with an emphasis on upcoming reliable biomarkers for the early and timely prediction of possible transition to PsA in patients with cutaneous psoriasis (PsO). Methods: A thorough literature search was performed using databases such as PubMed, SCOPUS, Embase, and Google Scholar. The aim was to review the latest research on clinical, radiological, serological, and biochemical predictors that could help in the early and timely recognition of the possible transition to PsA in patients with cutaneous PsO. Results: Early detection and monitoring for developing PsA have relied mostly on the evaluation of clinical features of disease, the genetic profile of patients, serial imaging, and a few serological markers. Recent research focuses on employing a multi-omic approach for the quick diagnosis of at-risk patients by scanning their genetic, protein, lipid, and metabolite profiles. Digital technology is the latest approach to evaluate early PsA with high accuracy and precision. It includes machine learning algorithms, specific immune profiles, and neural networks to decode distinct PsA phenotypes in psoriatic patients with a higher likelihood of developing arthritic features. Conclusions: Early identification of signs and symptoms will enable dermatologists to timely refer at-risk patients to rheumatologists, thus preventing irreversible joint damage. In the absence of a single specific marker, efforts should be made to adopt a holistic approach for early screening of PsA patients and initiating definitive treatment as early as possible. This intervention is of critical value since the prevention/reduction of PsA development is now being suggested as a new clinical endpoint in PsO trials. | en |
| DOI | https://doi.org/10.5812/jssc-153598 | en |
| URI | https://brieflands.com/journals/jssc/articles/153598 | en |
| Keyword | Psoriatic Arthritis | en |
| Keyword | Cutaneous Psoriasis | en |
| Keyword | Indicators | en |
| Keyword | Early | en |
| Keyword | Multiomics | en |
| Publisher | Brieflands | en |
| Title | In Search of Predictive Indicators for the Development of Psoriatic Arthritis in Patients with Cutaneous Psoriasis: The Path Traversed and the Road Ahead | en |
| Type | Review Article | en |
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