Q&A: Achieving Minimal Disease Activity in Patients with Recent-Onset Psoriatic Arthritis

In patients with recent-onset psoriatic arthritis (PsA), a key objective should be the control of pain, which is not always associated with inflammatory burden, and the establishment of generic and specific measures to better control the various PsA domains. This is according to a study published in Arthritis Research & Therapy.¹

In this Q&A, corresponding author Rubén Queiro, MD, PhD, associate professor of medicine at the faculty of health sciences of the University of Oviedo in Spain, discussed the research and its findings.

This multicenter, observational, prospective study, with 2-year follow-up, included 158 adult patients with recent-onset PsA. At the first and second follow-up visit, 55.5% and 58.3% of the patients had minimal disease activity (MDA), respectively. Predictive models based on artificial intelligence were used to detect variables associated with achieving MDA. The variables with the greatest predictive ability were global pain, Psoriatic Arthritis Impact of Disease (PsAID), patient global assessment of disease, and physical function according to the Health Assessment Questionnaire (HAQ)-Disability Index.

Rheumatology Network: Why was the study conducted?

Rubén Queiro, MD, PhD: Achieving a state of MDA is the closest we get to clinical remission in PsA. This stringent treatment goal is known to be associated with other favorable outcomes, but we have little information on patient- and disease-related factors to help us predict achievement of this goal. This information is even scarcer in patients with recent-onset PsA. Such data are crucial since the therapeutic measures used to change the adverse course of PsA are more likely tosucceed if we intervene early. Therefore, the main purpose of this study was to fill the current gap in this regard, providing information that we believe may be useful toimprove the care of patients with PsA.

RN: What were the surprises from the findings?

RQ: In this study, carried out in patients with recent-onset PsA, assessed at baseline before the potential modification of its natural history because of the treatment prescribed by a rheumatologist, 9 disease variables were associated with achieving MDA. Of these, global pain, the impact of disease measured by the PsAID questionnaire, patient global assessment of disease, and impaired physical function according to the HAQ-Disability Index carried considerable predictive weight.

RN: How significant are the findings?

RQ: Although these variables are somehow related to each other, our predictive models based on machine learning showed that they all have an independent weight on the prediction of achieving MDA in this population of recent-onset PsA. Hierarchically, the most important variables in the prediction model were global pain, impact on quality of life, the patient's estimate of disease activity, and physical functionality.

The importance of these findings is that for the first time we can establish clear objectives within our therapeutic actions aimed at patients with recent-onset PsA. In this way, pain and improvement in the patient's quality of life become first-order treatment objectives. Therefore, these goals go beyond the more simplistic goal of just reducing the inflammatory burden of the disease.

RN: What is the current practice and how could the findings possibly change things?

RQ: Until now for many rheumatologists, the goal of treatment for these patients is to reduce the inflammatory burden of the disease as a means of improving other aspects, such as physical function or quality of life. Our data focus more on measures aimed at improving pain and quality of life as basic premises for the patient to achieve a strict objective such as MDA. Estimations on disease made by clinicians and patients often differ, but the patient’s opinion is key when sharing decision-making.

Reference:

Queiro, R., Seoane-Mato, D., Laiz, A. et al. Minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis: predictive model based on machine learning. Arthritis Res Ther 24, 153 (2022). https://doi.org/10.1186/s13075-022-02838-2