PRESTO Successfully Predicts Future PsA in Patients With Psoriasis

A simple and scalable tool created with readily available clinical variables was able to successfully predict the development of psoriatic arthritis (PsA), within clinically meaningful time frames and with reasonable accuracy, in patients with psoriasis, according to a study published in Arthritis & Rheumatology.¹ Findings may improve early diagnosis.

Lihi Eder, MD, PhD

Credit: Institute of Medical Science, University of Toronto

Previous research has focused on risk factors in patients with psoriasis to identify patients at an increased risk for developing PsA, with the most recent evidence suggesting obesity, psoriatic nail lesions, and extensive psoriasis as the most common influences. Other factors included a history of physical trauma, thyroid disease, depression, musculoskeletal symptoms, a history of uveitis, and the location of psoriasis (intergluteal or scalp). However, no unifying prediction tool exists currently.²

“Risk estimation using prediction tools plays an important role in shaping treatment plans, based on the ability of the risk score to accurately predict and stratify a patient’s risk,” wrote Lihi Eder, MD, PhD, lead investigator and rheumatologist associated with Women’s College Research Institute, Women’s College Hospital, Toronto, Canada, and colleagues. “A prognostic model for PsA could assist clinicians in identifying susceptible psoriasis patients for screening or interventional purposes and facilitate informed decision-making by both the treating physician and patient.”

Investigators developed a risk prediction model for the development of PsA, the Psoriatic Arthritis Risk Estimation Tool (PRESTO), using the ongoing University of Toronto Psoriasis Cohort and evaluated its performance among patients with psoriasis without PsA. Eligible patients were recruited from phototherapy centers and dermatology clinics in the Toronto area, family medicine clinics, and though advertisements in hospitals and the local media.

Participants were assessed on an annual basis and information such as demographics, comorbidities, medications, symptoms, and psoriasis characteristics were collected and used to develop prediction models for PsA. Risks of developing PsA within 1- and 5-year time periods were estimated, and model performance was evaluated by the area under the curve and calibration plots.

A total of 635 patients with psoriasis from the Toronto Psoriasis Cohort were included in the analysis, of which 51 developed PsA within 1 year and 71 developed the condition within 5 years.

The risk of developing PsA within 1 year was linked to a family history of psoriasis, joint stiffness, back stiffness, male sex, younger age, nail pilling, pain severity, the use of biologic medications, and patient global health. The risk of developing PsA within 5 years was linked to pain, fatigue, psoriatic nail lesion, psoriasis severity, morning stiffness, and the use of systemic non-biologic medication or phototherapy.

The calibration plots demonstrated a reasonable agreement between observed and predicted probabilities.

Investigators noted the small sample size as a limitation of the study as it prevented analysis by sex and ethic group and may have prevented the inclusion of previously reported risk factors and the precision of the model. The generalizability of the study may have also been limited as the patients were mostly recruited from dermatology clinics.

“The PRESTO tool could serve future efforts to reduce the progression from psoriasis to psoriatic arthritis,” investigators concluded. “For example, PRESTO can be used to enrich prevention trials with at-risk populations. It can also identify patients with psoriasis who can benefit from early treatments, and it can serve as an educational tool for patients to increase awareness of psoriatic arthritis risk. Ultimately, we hope that these efforts will improve the lives of people living with psoriatic disease.”

References

1. ^{Eder L, Lee KA, Chandran V, et al. Derivation of a multivariable psoriatic arthritis risk estimation tool (PRESTO): a step towards prevention [published online ahead of print, 2023 Aug 9]. Arthritis Rheumatol. 2023;10.1002/art.42661. doi:10.1002/art.42661}
2. ^{Scher JU, Ogdie A, Merola JF, Ritchlin C. Preventing psoriatic arthritis: focusing on patients with psoriasis at increased risk of transition. Nat Rev Rheumatol 2019;15(3):153–66}