Psoriatic arthritis (PsA) is a heterogeneous disease with variable phenotypes.1 Several composite measures have been developed in the past decade to assess disease activity in PsA, but there is no consensus on the best method to accurately assess patients’ overall disease activity and responses to treatment.2,3 Recently, the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) and the Outcome Measures in Rheumatology (OMERACT) initiatives recommended that the PsA Disease Activity Score (PASDAS) be used in clinical trials but not in routine clinical practice because of the measure’s complexity.3,4 There is still no agreement on which composite measure to apply in routine clinical practice.

Consensus has been reached regarding the following definitions of remission as appropriate targets of treatment5,6:

  • Very low disease activity (VLDA);
  • Minimal disease activity (MDA) 7 of 7 (ie, meeting all 7 of the MDA criteria);
  • A cutoff score of ≤4 on the Disease Activity Index for Psoriatic Arthritis (DAPSA); and
  • A cutoff score of ≤4 on the clinical DAPSA (cDAPSA).

A cutoff score of 2 or less on the Composite Psoriatic Disease Activity Index (CPDAI) has been suggested as being equivalent to VLDA, but the CPDAI is not a validated measure.3 Earlier studies suggested that VLDA is a stringent remission criterion compared with the DAPSA or cDAPSA cutoffs, with pain and patient global disease activity (PtGA) visual analog scale (VAS) scores being the most rigid targets to achieve.4,7-9

This Journal Club discussion will focus on a study by Farkas et al that evaluated 4 composite measures of remission targets in PsA: MDA, CPDAI, DAPSA, and cDAPSA.10


A single-center, cross-sectional study was conducted in Ireland.10 Disease remission was evaluated by comparing 4 composite measures: MDA, CPDAI, DAPSA, and cDAPSA. The investigators determined which of these composite measures was the most stringent for identifying remission in patients with PsA and which was the most difficult to achieve.

A total of 258 patients were included (mean age, 50.7 years; men, 50.4%). Patients were aged 18 years and older and fulfilled the CASPAR (Classification Criteria for Psoriatic Arthritis) criteria11 for a diagnosis of PsA. Patients were assessed for disease remission by use of the following cutoffs:

  • MDA if fulfilled at least 5 of 7 of the following criteria, and VLDA if patients met all of the following criteria:
    • Tender joint count (TJC) ≤1/68
    • Swollen joint count (SJC) ≤1/66
    • Psoriasis Area Severity Index (PASI) ≤1 or body surface area ≤3
    • Leeds Enthesitis Index (LEI) ≤1
    • PtGA VAS ≤2 cm
    • Pain VAS ≤1.5 cm
    • Health Assessment Questionnaire-Disability Index (HAQ-DI) ≤0.5
  • DAPSA score of ≤4, calculated as the sum of TJC, SJC, PtGA VAS, pain VAS, and C-reactive protein
  • cDAPSA score of ≤4, calculated as the sum of  TJC, SJC, PtGA VAS, and pain VAS
  • CPDAI of ≤2, calculated as the sum of the following 5 PsA domains:
    • Peripheral arthritis (TJC, SJC, HAQ-DI)
    • Skin disease (PASI, Dermatology Life Quality Index)
    • Enthesitis (LEI, HAQ-DI)
    • Dactylitis (dactylitis digit count, HAQ-DI)
    • Axial disease (Bath Ankylosing Spondylitis Disease Activity Index [BASDAI], Ankylosing Spondylitis Quality of Life)

A web-based tool, Measuring Outcome in PsA (MOPSA), was used to calculate the composite scores.


Of 222 patients with all 4 composite score values, 20 (9.0%) met the criteria for VLDA, 44 (19.8%) were in remission according to the DAPSA measure, 52 (23.4%) were in remission according to the cDAPSA, and 67 (30.2%) were in remission according to the CPDAI.

Of the 20 patients who achieved VLDA, all were in remission according to the cDAPSA measure, 19 (95.0%) were in remission according to the DAPSA, and 16 (80.0%) were in remission according to the CPDAI. By comparison, criteria for VLDA were also met for 43.2% of patients in remission according to the DAPSA, 38.5% of those in remission according to the cDAPSA, and 23.9% of those in remission according to the CPDAI.

Concerning the individual domains of the composite scores, mean PtGA and pain VAS scores were significantly higher among patients in remission according to the CPDAI than among patients in remission according to the DAPSA, cDAPSA, or VLDA measures. Moreover, patients with VLDA had a significantly lower mean HAQ-DI score than patients in remission according to the CPDAI, DAPSA, and cDAPSA measures.

Of the 258 patients included in the study, 120 patients achieved MDA status (46.5%), and 30 of these patients met the stringent VLDA criteria. The VAS target for pain was achieved by 57.5%, 43.3%, and 44.8% of patients who met the criteria for remission according to MDA, low disease activity (MDA 5 or 6 of 7), and CPDAI, respectively.

Multivariate regression analysis revealed that the pain VAS target of 1.5 cm was the most difficult component to achieve. Mean HAQ-DI, BASDAI, Ankylosing Spondylitis Quality of Life, PtGA VAS, and TJC scores were significantly higher among patients who did not fulfill the pain VAS target. The percentage of patients with inflammatory-type back pain was also significantly higher among those with pain VAS scores greater than 1.5 cm.


Allan Gibofsky, MD, JD

Kevin Yip, MD

Genna Braverman, MD

Allan Gibofsky, MD, JD, professor of medicine at Weill Cornell Medicine and an attending rheumatologist at the Hospital for Special Surgery, and his colleagues, Kevin Yip, MD, and Genna Braverman, MD, who are currently pursuing clinical fellowships in rheumatology, discuss this study and the clinical implications of published research in this area.

Allan Gibofsky, MD, JD: The current study underscores in PsA something that we have known for a longer time in rheumatoid arthritis: the use of an objective metric is essential in defining outcomes. The treatment of PsA is complicated by the multiple domains involved in the disease, such as the skin, enthesopathy, and dactylitis. In contrast, in rheumatoid arthritis we predominantly look at the joints. In this paper, we see a significant improvement in defining multiple metrics, all of which seem achievable in PsA. Each of the metrics has benefits and limitations for achieving disease activity control in this complicated population of patients.

Kevin Yip, MD: The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis and OMERACT previously evaluated a few of these outcome measures, specifically DAPSA and CPDAI, which were used in the current study and compared with PASDAS, the gold standard. OMERACT views these outcome measures as a gold standard from a research perspective. Implementing PASDAS on a day-to-day basis is not feasible, given that it is a long and laborious study to use in clinical practice. Looking at this pragmatically, this is important because we need metrics we can use in the clinic to gauge patient outcomes and disease activity.

Genna Braverman, MD: Rheumatoid arthritis has an established paradigm in terms of measuring disease activity, whereas the metrics used for PsA are more feasible to apply in research settings than in clinical settings. From a clinical perspective, it is important to know which metric to use to track a patient’s disease activity, and this study defined multiple metrics that can be applied in patients with PsA.

AG: What are the strengths and weaknesses of the study?

KY: The snapshot of all 4 composite measures at the same time is a strength of the study and generated a wealth of information on different data points in PsA such as TJC, SJC, dactylitis, enthesitis, and skin, in addition to overlapping features associated with back pain. The comparison of each data point and their relationships is beneficial. The study showed how stringent the previously defined measures are for achieving remission, which variables are the most challenging to achieve, and the relationships of these variables with each other. From that analysis, the authors attempted to allude to which measures might be stronger, weaker, or more stringent. Other strengths of the study include the large sample size and the use of the Measuring Outcome in PsA tool to calculate composite scores.

GB: The most significant strength is the study design. It was a cross-sectional study that provided us with a snapshot of how these different disease metrics might change in response to therapy. However, it would have been interesting if the authors had provided information on how the study population was treated and whether they received biologics or nonsteroidal anti-inflammatory drugs. This information could help us to understand which patients were in remission and by what metrics they were achieving remission. In addition, not all the indices included in the study used the same disease features. Some axial diseases were incorporated, but this was done inconsistently. The authors presented no ideal way of capturing axial involvement. No radiographic assessments were performed. Also, the BASDAI overlapped with peripheral arthritis. Using the BASDAI as an axial measure might have overestimated axial involvement.

KY: Another limitation is the lack of information on the timing of measurement of these metrics during the 2-year time frame.

AG: We see in the study a snapshot at one point in time, but we do not know at which point in time. We are lacking details on the effect of prior or current treatment, and we do not have information on trajectories of the metrics as a function of treatment. Another weakness of the study that Dr Braverman already alluded to is that one of the domains of PsA is the disease itself. There is no good metric for the actual disease, including the most sensitive metric (the VLDA subset of the MDA). Even though we have all these metrics such as the MDA, CPDAI, and PASDAS, none stratify the patients into categories of remission; VLDA; or low, moderate, or high disease activity.

Applying the findings of the study in clinical practice is challenging. For example, in rheumatoid arthritis, although the metrics used most often are simpler to perform, only about one-third of practicing rheumatologists actually use them in clinical practice. In that one-third, very few use the metrics to define or change therapy. The authors of the current study did point out that no agreed-upon metric of disease activity exists for PsA. Getting physicians to reach an agreement on the metrics is more feasible than getting them to apply the metrics in their practice or to use them to define therapy. These kinds of metrics, which require assessment of multiple domains, are time-consuming and will be problematic even if they do not require calculations on the computer. None of these metrics have proved particularly valuable to be universally endorsed in clinical practice, even in clinical trials. There is no full agreement on which gives the best primary outcome. So, should it be used? Perhaps. Will it make a difference if a metric is used in combination with therapy? Almost certainly. But we are not quite to the point of imposing a metric for use in assessing PsA disease activity.

What are your thoughts about the study population? Is it ideal, and are the patients similar to those seen at your clinical practice?

KY: The article did not provide specific details of the patients included in the study, such as their body mass index, smoking history, family history of diseases, comorbidities, or medications used. This is critical information needed to compare the study cohort with patients seen in clinical settings.

AG: It is well known that there is a significant disparity in the distribution of patients across disease states. For example, the Baltimore cohort of lupus patients has been reported to be different from the Southern California cohort or the New York cohort. This is a great study in an Irish cohort with excellent methodology and questions, but the generalizability of the study findings to patient populations worldwide remains to be determined.

Let’s turn to biases, unaccounted variables, or confounders that may affect the validity of these findings in clinical practice, such as back pain. Patients with inflammatory diseases like PsA can still complain of noninflammatory back pain. When a scoring of back pain is included in any of these metrics, one must be very careful about differentiating between inflammatory and noninflammatory back pain.

GB: Another is the lack of information on the comorbid conditions of the study population, which can confound patient-reported experience. This omission makes it challenging to interpret the assessments.

KY: We do not know the smoking history of the study population, and we know that smoking is strongly correlated to psoriasis. If, for example, one-half of the study population had a history of smoking, we must take that into account in terms of the numbers we see.

AG: Another factor that the authors themselves acknowledge is the assessment of pain. The assessment of pain is included in some but not all of the composite metrics, which makes comparisons among the composite metrics difficult.

Should current clinical practice guidelines be re-examined on the basis of these findings?  I will go out on a limb and say that these findings point in the direction of the better metric to use. Current paradigms in other diseases suggest that coupling a validated metric to a therapy does provide a better outcome. So, I would say that we should re-evaluate current guidelines. The authors have demonstrated that the MDA measure across multiple populations is the best metric to use and that the VLDA subset of the MDA measure provides the best criteria for remission. They also showed that the MDA measure should be incorporated into clinical practice and be used longitudinally to assess disease activity and response to therapy.

Let’s now discuss improvements that could be made to the study design, and whether further research is needed to validate the findings and address the limitations.

The current study looked at the MDA measure, which has 7 domains, and patients classified as having MDA needed to fulfill at least 5 of the 7 criteria. I would like to see which 5 or 6 of the 7 domains were being observed in the study because I think one might be able to break the MDA measure into subsets and correlate these with different populations.

GB: The current study clearly demonstrated the need for and importance of a defined metric to achieve targets in treating diseases. This is an unmet need in PsA. We need a better understanding of which metrics and domains to use in PsA. We further need multicenter studies with reproducible findings that can be demonstrated in different patient populations. We also need more evidence on how these metrics track over time when we make changes in therapy based on measures of disease activity.


Allan Gibofsky, MD, JD, reported affiliations withAbbVie, Acquist Therapeutics, Inc., Amgen Inc., Biosplice Therapeutics, Inc., Boehringer Ingelheim, Eli Lilly and Company, Pfizer Inc., Johnson & Johnson, and Regeneron Pharmaceuticals, Inc.


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Posted by Haymarket’s Clinical Content Hub. The editorial staff of Rheumatology Advisor had no role in this content’s preparation.

                                                                                                                                 Reviewed February 2022