Change in psoriatic arthritis outcome measures impacts SF-36 physical and mental component scores differently: an observational cohort study.

OBJECTIVE: The objective was to investigate interplay and physical and mental component scores between change (Δ) in health-related quality of life (HRQoL) quantified by the physical component score (PCS) and mental component score (MCS) retrieved from short-form health survey (SF-36), change in disease activity (ΔDAS28CRP) and manifestations of PsA.
METHODS: PsA patients initiating new medical therapy were enrolled. Independent disease measures evaluating disease activity, enthesitis, psoriasis, pain and fatigue were collected at treatment initiation and after 4 months. Interplay between independent disease measures and dependent outcome measures, ΔPCS and ΔMCS, was described with univariate regression analyses. Multivariate regression analyses were applied to assess the impact of independent variables, such as individual disease outcome measures vs ΔDAS28CRP on ΔPCS and ΔMCS.
RESULTS: One hundred and eight PsA patients were included. In the univariate regression analyses, improvement in fatigue, pain and disability were associated with improvement in ΔPCS (β; -2.08, -0.18 and -13.00, respectively; all P < 0.001) and ΔMCS (β; -1.59, -0.12 and -6.07, respectively; P < 0.001, P < 0.001 and P = 0.003, respectively). When patient-reported outcomes were included in the final multivariate models, improvements in ΔPCS and ΔMCS were associated with improvements in pain, fatigue and disability (P < 0.001). Improvement in enthesitis impacted ΔPCS positively (β -0.31, P < 0.001). No association was found between change in skin psoriasis, ΔPCS and ΔMCS (β 0.15, P = 0.056 and β 0.05, P = 0.561, respectively).
CONCLUSION: In this PsA patient cohort, diminishing pain, disability and fatigue improved PCS and MCS significantly. Changes in enthesitis and psoriasis did not grossly impact HRQoL compared with DAS28CRP. Individual PsA manifestations influence HRQoL differently, which is important clinically when targeting treatment. TRIAL REGISTRATION: ClinicalTrials.gov, http://clinicaltrials.gov, NCT02572700.

Key messages

Clinical manifestations and patient-reported outcomes are factors well known to impair quality of life in patients with PsA.

Diminishing factors such as pain, fatigue and physical disability improve both physical and mental component scores independent of change in DAS28CRP.

Increasing health-related quality of life for PsA patients necessitates treatment targeting both inflammatory arthritis and patient-reported outcomes.

Introduction

PsA is a chronic immune-mediated inflammatory disease with increasing prevalence and negative societal impact [1-3] affecting up to one in four patients with psoriasis [4]. The diverse clinical manifestations of PsA, including joint swelling and tenderness, skin psoriasis, enthesitis, dactylitis and nail psoriasis, together with patient-reported outcomes including fatigue, pain and physical impairment, are well-known causes of decreased health-related quality of life (HRQoL) [5].

The heterogeneous manifestations of PsA often complicate treatment aiming to improve HRQoL and are often combined with a discrepancy in perception of disease activity between patients and physicians [6] indicating that features such as fatigue, pain, disability, tender and swollen joint counts are of most importance in contributing to this discrepancy [7]. Treating physicians prioritize reduction in joint pain, swelling and stiffness [8], whereas patients often rank pain, cutaneous manifestations and fatigue as their priority symptoms of focus [9, 10]. Several studies investigating decreased HRQoL in PsA patients have been conducted in cross-sectional settings to assess associations with individual clinical manifestations [11-14], whereas studies that included follow-up examining the relationship between changes in individual PsA manifestations and change in quality of life (QoL) have been sparse [15, 16].

Treatment of PsA aims to decrease disease activity, often by using medical therapies such as conventional synthetic DMARDs (csDMARDs) and/or biological DMARDs (bDMARDs). Available medical therapies are well known to reduce inflammation of joints and skin effectively [17], albeit with minor effect on patient-reported fatigue [18]. This demonstrates the relevance of investigating the impact of different PsA disease outcomes on patient-reported HRQoL and whether changes in clinical manifestations and patient-reported outcomes will contribute to change in HRQoL in patients with PsA.

The objective of this study was to investigate the interplay between changes in composite joint disease outcome (DAS28RP) and individual clinical PsA manifestation, including skin psoriasis and enthesitis, in addition to patient-reported pain, physical disability, and fatigue as predictors of change in patient-reported HRQoL assessed by the physical component score (PCS) and mental component score (MCS), respectively, retrieved from the Short Form 36 (SF-36) questionnaire. In this set-up, PCS and MCS are considered dependent factors.

Methods

Study design

The study was designed as an observational cohort study including patients from the Parker Institute’s consecutive PsA patient cohort (the PIPA cohort) [19] registered at ClinicalTrials.gov (NCT02572700). The study was conducted in compliance with national legislation approved by the Danish Ethics Committee (H-15009080) and in accordance with the General Data Protection Regulation (BFH-2015–043) approved by the Capital Region of Denmark. The pre-specified protocol was made available from the Parker Institute’s website (www.parkerinst.dk).

Participants

Patients diagnosed with PsA were recruited from departments of rheumatology in Region Zealand and the Capital Region of Denmark. Patients were included if they fulfilled the Classification Criteria for PsA (CASPAR) [20], were ≥18 years of age and were scheduled to initiate a new course of treatment. Before inclusion, patients provided written informed consent. Patients attended a baseline visit at treatment initiation and at follow up after 4 months.

Sampling and sample size

Data were retrieved from the on-going consecutive PIPA cohort, and sample size was based on the cut-off date of 12 November 2020, when data on all included PIPA patients were obtained from the PIPA database. For the present study, additional inclusion criteria were deemed relevant, and only data on patients with a complete response to SF-36 and complete data to calculate disease activity (DAS28CRP) were included for analysis.

Variables and outcome measures

The primary outcome analysed included change in (Δ) PCS and MCS as a function of independent variables ΔDAS28CRP, Δpain, Δfatigue, change in Spondyloarthritis Research Consortium of Canada enthesitis index (SPARCC) (ΔSPARCC) and ΔHAQ. The Danish version of SF-36 was included for the investigation of HRQoL [21]. SF-36 assesses eight health domains, namely physical functioning (PF), role physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role emotional (RE) and mental health (MH), on scales from 0 to 100, with 0 representing maximum health impairment and 100 no health impairment [22]. From eight general domains, two domains have been identified, the PCS and the MCS by component analyses [23]. During the present study, PCS and MCS were used as a proxy for physical HRQoL and mental HRQoL, respectively.

Independent explanatory variables included clinical measures evaluated by a physician. Assessments were performed of swollen and tender joints (66/68 joint count), skin psoriasis quantified by the Psoriasis Area Severity Index (PASI) and enthesitis evaluated with the SPARCC. Blood biochemistry was conducted to measure blood CRP for the calculation of DAS28CRP. Additionally, patient-reported outcomes were obtained from questionnaires implemented on touch screens at the outpatient clinic of the Parker Institute and filled in by patients on the same day as the clinical examination. The HAQ was included for the assessment of physical function during activities of daily living. The HAQ consisted of 20 questions yielding a total score from 0 to 3, with higher numbers indicating increasing disability [24]. A visual analog scale (VAS) was developed to measure patient-reported pain, fatigue and global health on a 0–100 mm scale [25]. VAS pain was used in the present study, with 0 representing no pain and 100 the worst imaginable pain [26]. Fatigue measures were retrieved from the PsA Impact of Disease (PsAID) questionnaire, which requires patients to rate their fatigue on a scale from 0indicating no fatigue to 10 indicating total exhaustion [26].

Statistical analysis

Patient characteristics are presented as medians with the corresponding interquartile range (IQR) for continuous variables and number with the corresponding percentage for categorical variables. Changes in (Δ) clinical and patient-reported outcome measures from baseline (treatment initiation) to 4 months follow-up were described as the mean change with 95% CIs. Wilcoxon signed-rank test was applied to evaluate statistically significant changes. Two-sided P-values <0.05 were considered statistically significant. SF-36 domain scores were normalized and z-transformed, and a spydergram was configured to evaluate the contribution of each SF-36 domain score over time in comparison to Danish normative SF-36 data [27]. Before the complete case analysis, the Pearson correlation coefficient comparing ΔPCS and ΔMCS was evaluated. Univariate regression analysis was applied to assess the association between individual clinical and patient-reported outcome measures, such as DAS28CRP/ΔSPARCC/ΔPASI/ΔVAS pain/ΔHAQ/ΔPsAID fatigue with ΔPCS and ΔMCS, respectively. To address the study objectives, multivariate regression analysis was performed, including ΔDAS28CRP, ΔPCS/ΔMCS and individual disease outcome measures (i.e. ΔSPARCC/ΔPASI/ΔVAS pain/ΔHAQ/ΔPsAID fatigue, respectively), respectively. Only clinical and patient-reported measures considered predictors of change in PCS and MCS were included in a multivariate analysis (e.g. univariate regression analysis with P-value <0.05). Results from regression analyses were presented as beta coefficients (β) with 95% CI, S.e. and R2. Additionally, R2-change was included to evaluate the contribution of ΔSPARCC/ΔPASI/ΔVAS pain/ΔHAQ/ΔPsAID fatigue, respectively, when included in the multivariate regression analyses with ΔDAS28CRP and ΔPCS/ΔMCS. Results of the multivariate regression analyses were also presented in xyz plots, with blue arrows indicating positive change and red arrows negative change in the relevant outcome measure. The PCS and MCS were calculated in accordance with the Danish SF-36 guide [27]. Statistical analysis was carried out using R Statistics software with the additional packages MASS, plyr and plot3D.

Results

Patient characteristics and outcome measures

A total of 108 PsA patients were included in the complete case analysis (Fig. 1). Included patients were defined by 56.48% being female, a median age of 52.70 years (IQR 42.95–61.3 years), and with median disease duration of 2.88 years (IQR 0.50–10.00 years) (Table 1). Treatment characteristics showed that 37.96% of included PsA patients initiated treatment with csDMARDs as monotherapy, whereas 62.04% were initiating bDMARD treatment, with 33.33% being bDMARD monotherapy. The majority of patients in bDMARD monotherapy had a history of previous csDMARD use.

Patient inclusion flow chart

Data were included from the PIPA cohort study [19]. aPatients were screened for eligibility by initial interviews at departments of rheumatology or by telephone and later clinical assessment. bInclusion criteria included age ≥18 years, diagnosed with PsA fulfilling the CASPAR criteria, presenting with peripheral joint involvement and about to initiate a new conventional synthetic DMARD or biological DMARD treatment course. Data were retrieved on 18 November 2020 from the consecutive cohort.

Table 1

Patient characteristics

Characteristic	n	Baseline	Follow-up	Mean change	P-value
				[95% CI]
Female, n (%)	108	61 (56.48)	–	–	–
Age, years	108	52.70 (42.95–61.30)	–	–	–
Disease duration, years	108	2.88 (0.50–10.00)	–	–	–
Treatment characteristics
csDMARD monotherapy, n (%)	108	41 (37.96)	–	–	–
bDMARD all, n (%)	108	67 (62.04)	–	–	–
bDMARD monotherapy, n (%)	108	36 (33.33)	–	–	–
Clinical outcome
DAS28CRP	108	4.27 (3.57–4.28)	3.09 (2.50–4.24)	−0.97 [−4.25, 2.31]	<0.001
SPARCC enthesitis (0–16)	108	4.50 (2.00–7.00)	3.00 (0.50–6.00)	−4.10 [−28.08, 19.88]	0.031
PASI (0–72)	103a	4.00 (0.00–10.45)	0.50 (0.00–3.93)	−4.49 [−32.07, 23.09]	<0.001
Patient-reported outcome
HAQ (0–3)	108	0.88 (0.50–1.25)	0.63 (0.22–1.00)	−0.25 [−2.01, 1.50]	<0.001
PsAID Fatigue (0–10)	108	7.00 (3.00–8.00)	4.50 (2.00–7.25)	−1.14 [−9.36, 7.08]	<0.001
VAS Pain (0–100)	108	57.00 (28.00–74.00)	25.00 (10.00–63.25)	−15.73 [−94.86, 63.40]	<0.001
SF-36 data
SF-36 PCS (0–100)	108	32.26 (27.10–38.87)	37.69 (31.99–47.72)	5.00 [−24.42, 34.41]	<0.001
SF-36 MCS (0–100)	108	48.35 (37.88–57.18)	53.12 (40.53–59.03)	2.76 [−31.59, 37.11]	0.012
SF-36 PF (0–100)	108	55.00 (45.00–75.00)	70.00 (53.75–85.00)	9.58 [−56.71, 75.88]	<0.001
SF-36 RP (0–100)	108	0.00 (0.00–50.00)	25.00 (0.00–100.00)	17.82 [−94.53, 130.18]	<0.001
SF-36 BP (0–100)	108	41.00 (22.00–52.00)	52.00 (38.75–82.00)	15.08 [−54.88, 85.05]	<0.001
SF-36 GH (0–100)	108	45.00 (26.50–62.00)	50.00 (35.00–73.25)	5.64 [−59.02, 70.30]	0,002
SF-36 VT (0–100)	108	35.00 (20.00–56.25)	50.00 (30.00–75.00)	10.23 [−61.48, 81.94]	<0.001
SF-36 SF (0–100)	108	75.00 (50.00–100.00)	87.50 (62.50–100.00)	4.63 [−76.19, 85.45]	0.005
SF-36 RE (0–100)	108	50.00 (0.00–100.00)	100.00 (33.33–100.00)	15.43 [−98.71, 129.57]	0.001
SF-36 MH (0–100)	108	74.00 (55.00–84.00)	84.00 (60.00–92.00)	4.81 [−56.47, 66.10]	0.004

Data are presented as the median with interquartile range or number with percentage.

PASI was not calculated for pustulosis palmoplantaris.

bDMARD; biological DMARD; BP: bodily pain; csDMARD: conventional synthetic DMARD; GH: general health; MCS: mental component score; MH: mental health; PASI: Psoriatic Area Severity Index; PCS: physical component score; PF: physical functioning; PsAID: PsA Impact of Disease; RE: role emotional; RP: role physical; SF: social functioning; SF-36: Short Form Questionnaire; SPARCC: Spondyloarthritis Research Consortium of Canada enthesitis index; VAS: visual analog scale; VT: vitality.

Statistically significant changes were seen between baseline and 4 months follow-up for all clinical and patient-reported outcome measures evaluated (Table 1). Mean changes in clinical and patient-reported outcomes from baseline to follow-up, ΔDAS28CRP, ΔPASI, ΔSPARCC, ΔHAQ, ΔPsAID fatigue and ΔVAS pain, were all statistically significant (Table 1), representing a decrease in disease activity measures, whereas the statistically significant increases for ΔPCS and ΔMCS, indicate an improvement in HRQoL over time. After 4 months of treatment, an increase, indicating improvement, in all SF-36 domain scores was seen, with statistically significant mean changes in seven of eight domains. Only SF was not statistically significant (P = 0.005) (Table 1). Lowest scores at baseline were seen in RP and VT (median score of 0.00 and 35.00, respectively). Greatest improvements over time were reported in RP and RE (mean change of 17.82 and 15.43, respectively), whereas only minor improvements were seen in GH, SF and MH (mean change of 5.64, 4.63 and 4.81, respectively) (Table 1; Fig. 2). PsA patient domain scores at both baseline and follow-up were low compared with Danish normative data, demonstrating decreased scores in all domains of PsA patients compared with Danish norms (Fig. 2). The Pearson correlation coefficient for ΔPCS and ΔMCS was 0.11, indicating no association between ΔPCS and ΔMCS (Supplementary Fig. S1, available at Rheumatology Advances in Practice online).

SF-36 spydergram for PsA patients before and 4 months after treatment compared with Danish SF-36 normative data

Mean SF-36 scores at baseline (yellow) and 4 months follow-up (blue) and Danish normative data (green). BP: bodily pain; GH: general health; MH: mental health; PF: physical functioning; RE: role emotional; RP: role physical; SF: social functioning; VT: vitality.

Patient-reported outcomes as predictors of change in PCS and MCS

Results from the univariate regression analyses including patient-reported outcomes, ΔPsAID fatigue, ΔVAS pain and ΔHAQ, vs ΔPCS and ΔMCS, respectively, were all statistically significant (P < 0.001) and considered possible predictors of change in both PCS and MCS (Table 2). Inclusion in the multivariate regression analyses with DAS28CRP was deemed relevant. Multivariate analyses suggest changes in DAS28CRP and HAQ/PsAID fatigue/VAS pain, respectively, to be associated with changes in PCS and MCS (Table 3), with statistically significant P-values (P < 0.001). The multivariate regression analysis demonstrating the interplay between (1) ΔPCS and ΔMCS, (2) ΔDAS28CRP and (3) patient-reported outcome, ΔPsAID fatigue, and ΔVAS pain are illustrated in Fig. 3A and B, with a statistically significant contribution (all P < 0.001) from ΔHAQ to the ΔPCS model with β = −11.75, S.e. = 1.65, ΔPsAID with β = −1.79, S.e. = 0.29, and ΔVAS pain with β = −0.16 = S.e. 0.03, and to the ΔMCS model with ΔHAQ with β = −3.63, S.e. = 2.18, ΔPsAID fatigue with β = −1.32, S.e. = 0.35, and ΔVAS pain with β = −0.008, S.e. = 0.124. The orientation of the regression planes displays the associations between included variables, indicating that improvements in either pain or fatigue measures were associated with the improvement in PCS (green regression plane) and MCS (blue regression plane) and to a larger extent than the joint disease outcome, DAS28CRP. The same association was seen when including HAQ (plot not shown).

Table 2

Univariate regression analyses with change in physical and mental component scores

Variable	ΔPCS					ΔMCS
	β	95% CI	S.e.	R 2	P-value	β	95% CI	S.e.	R 2	P-value
ΔDAS28CRP	−3.19	−4.56, −1.82	0.69	0.159	<0.001	−2.71	−4.21, −1.20	0.76	0.098	<0.001
ΔPASI	0.15	0.00, 0.31	0.08	0.027	0.056	0.05	−0.11, 0.21	0.08	−0.007	0.561
ΔSPARCC	−0.56	−1.11, −0.02	0.27	0.029	0.043	−0.25	−0.84, 0.33	0.30	−0.002	0.382
ΔHAQ	−13.00	−15.92, −10.08	1.47	0.418	<0.001	−6.07	−9.97, −2.16	1.97	0.073	0.003
ΔPsAID fatigue	−2.08	−2.62, −1.53	0.28	0.343	<0.001	−1.59	−2.24, −0.95	0.33	0.176	<0.001
ΔVAS pain	−0.18	−0.24, −0.13	0.03	0.315	<0.001	−0.12	−0.18, −0.06	0.03	0.109	<0.001

Univariate regression analysis used ΔPCS/ΔMCS as dependent variables and displayed associations between individual outcome measures. Outcome measures considered predictors of change in PCS/MCS with statistically significant P-values (P < 0.05) were also included in a multivariate regression analysis with DAS28CRP and ΔPCS/ΔMCS. Results are presented with beta coefficients (β) and corresponding S.e.

DAS28CRP: DAS for 28 joints and CRP; Δ: change in; MCS: mental component score; PASI: Psoriasis Area Severity Index; PCS: physical component score; PsAID; PsA impact of disease; SPARCC: Spondyloarthritis Research Consortium of Canada enthesitis index; VAS; visual analog scale.

Table 3

Multivariate regression analyses

Variable	ΔPCS						ΔMCS
	β	95% CI	S.e.	R 2	R 2 change	P-value	β	95% CI	S.e.	R 2	R 2 change	P-value
ΔSPARCC	−0.31	−0.83, 0.21	0.26	0.162	0.003	<0.001	–	–	–	–	–	–
ΔHAQ	−11.75	−15.02, −8.47	1.65	0.427	0.268	<0.001	−3.63	−7.95, 0.69	2.18	0.113	0.015	<0.001
ΔPsAID fatigue	−1.79	−2.37, −1.21	0.29	0.373	0.214	<0.001	−1.32	−2.02, −0.62	0.35	0.197	0.099	<0.001
ΔVAS pain	−0.16	−0.23, −0.10	0.03	0.316	0.157	<0.001	−0.08	−0.16, 0.00	0.04	0.124	0.026	<0.001

Explanatory outcome measures considered predictors of change in PCS/MCS with statistically significant P-values (P < 0.05) were added to a multivariate regression analysis with DAS28CRP and ΔPCS/ΔMCS. Results are presented with beta coefficients (β) and corresponding S.e., R2 and R2 change. The R2 change was calculated based on R2 of the univariate model with ΔDAS28CRP and the R2 of the multivariate model after addition of ΔSPARCC/ΔHAQ/ΔPsAID fatigue/ΔVAS pain, respectively.

DAS28CRP: DAS for 28 joints and CRP; Δ: change in; MCS: mental component score; PCS: physical component score; PsAID: PsA impact of disease; SPARCC: Spondyloarthritis Research Consortium of Canada enthesitis index; VAS: visual analog scale.

3D associations between change in specific individual disease outcome measures, ΔDAS28CRP and change in physical and mental component scores

Three-dimensional associations between outcome measures from baseline to follow-up (ΔDAS28CRP and ΔPCS/ΔMCS) and ΔPsAID fatigue (A), ΔVAS pain (B), ΔSPARCC (C) and ΔPASI (D), respectively, presented in xyz plots, with blue arrows indicating positive change and red arrows negative change from baseline to follow-up. The green and blue regression planes represent ΔPCS- and ΔMCS-related data, respectively. DAS28CRP: DAS for 28 joints and CRP; MCS: mental component score; PASI: Psoriasis Area Severity Index; PCS: physical component score; PsAID: PsA impact of disease; SPARCC: Spondyloarthritis Research Consortium of Canada enthesitis index; VAS: visual analog scale.

Clinical outcomes as predictors of change in PCS and MCS

Univariate regression analyses including clinical disease outcome, ΔDAS28CRP and ΔSPARCC, vs ΔPCS displayed statistical significance (P < 0.001 and P = 0.043, respectively). Only ΔDAS28CRP showed a statistically significant association with ΔMCS (P < 0.001) (Table 2). ΔSPARCC was not included in the multivariate regression analysis with ΔDAS28CRP and ΔMCS. ΔPASI showed no clear association with the ΔPCS and ΔMCS response over time (P = 0.056 and P = 0.561, respectively) (Table 2). Associations between (1) ΔPCS and ΔMCS, (2) ΔDAS28CRP and (3) individual clinical inflammatory outcomes, ΔSPARCC and ΔPASI are illustrated in Fig. 3C and D. The unclear associations between ΔPCS/ΔMCS and several outcome measures (e.g. ΔPASI and ΔSPARCC) were also indicated by the orientations of the regression planes. Improvements in ΔPCS and ΔMCS were primarily associated with decrease in the joint-related disease activity outcome (DAS28CRP), however, not grossly dependent on concomitant improvement in SPARCC, which was also indicated in the regression analyses.

Discussion

In the present study, the influence and interplay of individual disease outcomes of PsA on HRQoL were investigated, and an assessment of the change in PCS and MCS as a proxy for physical and mental HRQoL was conducted. Although it is well known that PsA patients suffer from decreased HRQoL, the present study adds to existing knowledge that changes in individual manifestations of PsA affect changes in PCS and MCS differently. The evaluation of ΔPCS and ΔMCS in separate models was justified by the weak correlation, demonstrating no association between ΔPCS and ΔMCS (Pearson correlation coefficient = 0.11).

Patient-reported outcomes

Overall, results indicated that improvement in SF-36 component scores, PCS and MCS, were associated with improvement in the patient-reported measures of HAQ, PsAID fatigue and VAS pain. It became apparent that improvements in PCS and MCS were not necessarily dependent on improvements in PsA disease activity (DAS28CRP). In fact, changes in these patient-reported outcomes affected PCS and MCS to a larger extent than changes in DAS28CRP scores. Moreover, improvements in PCS and MCS were also seen in the combination of positive change in patient-reported outcome and negative change in DAS28CRP (Fig. 3). This is highly relevant to clinical practice and treatment of PsA, because it implies that improving disability, fatigue and pain measures can improve PCS and MCS scores and HRQoL independent of change in DAS28CRP. This highlights the importance of including patient-reported outcome measures when monitoring treatment of PsA.

Clinical outcome

Assessing the impact of change in the clinical outcome measures, PASI and SPARCC, on change in SF-36 indicated that improvements in PCS and MCS were associated with decreasing joint-associated outcome, as measured by DAS28CRP, more than individual outcome measures from other domains of disease. This is in line with individual domain scores demonstrating a major impact on physical domains (PF, RP and BP), also reported in similar studies [28]. This does not exclude psoriasis and enthesitis as important factors in relationship to HRQoL but implies the close association between these clinical manifestations and DAS28CRP. The lack of association between PASI, PCS and MCS might also be explained by the relationship between positive and negative weights of domains in the calculation of PCS and MCS. Previous studies have shown that mental domains (VT, SF, RE and MH) are the main domains affected by psoriasis [28], of which SF and MH in this study scored 75.00 and 74.00, respectively, and presented as the domains less affected. Overall, the results indicate the joint disease outcomes, tender and swollen joints, are the most important clinical domain of disease in this patient cohort. Five PsA patients had no PASI scores registered because they were diagnosed with palmoplantar pustulosis; this was considered missing data and excluded from further analysis. The small amount of missing data was not considered to influence the results.

Interestingly, only minor improvements were reported in SF-36 domains, GH and MH, in response to medical treatment. These findings together with additional results are important to PsA patients and also important for physicians to consider in the case of treatment-resistant PsA, because it might be possible to change HRQoL for PsA patients independently of disease activity, demonstrating the relevance of integrating an interdisciplinary approach during treatment together with the shared decision-making including PsA patients themselves.

The sample size of 108 PsA patients was deemed sufficient for the evaluation of the study objective. However, it is believed that an increased number of participants might make associations stronger, increasing relevant statistically significant changes. Limitations might also include the results being largely dependent on the cohort examined, which might also explain the unclear association between ΔPASI, ΔPCS and ΔMCS, because the PsA patients included in the present study had relatively low PASI scores at baseline. In comparison, a similar study showed that diminishing skin psoriasis resulted in improved HRQoL [16]. A low PASI score might further reduce the importance of experienced pain associated with psoriatic skin and HRQoL [29]. The present study did not distinguish between skin-associated pain and joint-associated pain when using VAS pain. Despite the limitations, this study provides important insight into the relationship between HRQoL and individual outcome measures in PsA patients.

Overall, it may be concluded that it is possible to improve HRQoL in PsA patients by improving individual manifestations of the disease. This study demonstrates that improving HRQoL for PsA patients necessitates the incorporation of both clinical measures from the various domains of arthritis (i.e. joints and entheses) and patient-reported outcome measures (i.e. disability, pain and fatigue) as a part of their individual treatment strategy. Thus, treating PsA patients to a single domain target, such as joint disease outcomes, will simply not fit all patients with heterogeneous manifestations.

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