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Abstract Number: 1541

Subgroups of Established Rheumatoid Arthritis Patients Can be Characterized By Patient and Physician Assessment Discrepancy, Anxiety and Depression and Presence of Depression Might be Associated with Slower Response to Treatment

Yong Gil Hwang1, Juan (June) Feng2, Heather Eng2, Jason Lyons2, Anthony Fabio3 and Larry W. Moreland4, 1Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 2Epidemiology Data Center, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA, 3Department Of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 4Rheumatology & Clinical Immunology, University of Pittsburgh, Pittsburgh, PA

Meeting: 2015 ACR/ARHP Annual Meeting

Date of first publication: September 29, 2015

Keywords: phenotypes and rheumatoid arthritis (RA)

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Session Information

Date: Monday, November 9, 2015

Title: Rheumatoid Arthritis - Clinical Aspects Poster II

Session Type: ACR Poster Session B

Session Time: 9:00AM-11:00AM

Background/Purpose: Rheumatoid
arthritis (RA) is a heterogeneous inflammatory disease with various signs and
symptoms.  Previous studies have shown that RA patients can be sub-grouped
based on inflammation, pain, and mental health, but it cannot be readily
implemented without extra burden in daily practice. We identified subgroups of
RA patients using the American College of Rheumatology (ACR) core data set
measures and Multi-Dimensional Health Assessment Questionnaire (MDHAQ) and
investigated the clinical significance of the subgroups.

Methods: RA subjects
enrolled in the University of Pittsburgh Rheumatoid Arthritis Comparative
Effectiveness Registry (RACER) with moderate to high disease activity by
Clinical Disease Activity Index (CDAI > 10) were included.  Based on
previous work, ACR core set measures and sleep, anxiety; depression questions
in MDHAQ at the initial visit were included as clustering variables. Remission
or mild disease activity (CDAI ≤ 10) was considered as low disease
activity (LDA). Time to achieve LDA was calculated for each cluster
identified.  We used a hierarchical clustering procedure with the Ward
method. To examine differences between clusters, we used the Kruskal-Wallis
test comparing the factors between each of the clusters.

Results:
For
the 175 subjects analyzed, subject age was 57.5 ± 13.4 (Mean±SD) years with
disease duration of 13.7 ± 13.5 years.  Five clusters were identified but
the majority of subjects were grouped into cluster 1 (reference cluster).
(Table.1) Qualitative comparison showed that 5 clusters can be grouped into 2
categories (Physical Global Assessment [PhGA] – Patient Global Assessment
[PtGA] concordant group [Cluster 1, 2, 3] and PhGA-PtGA discordant group
[cluster 3, 4]). Furthermore, they were different in anxiety and depression
level. Although cluster 2 and 3 had similar disease activity, cluster 2 had
higher anxiety and cluster 3 had higher depression. Similarly, cluster 4 had
higher anxiety and cluster 5 had higher depression. Clusters having higher
depression (cluster 3 in comparison with cluster 1 and 2, cluster 5 in
comparison with cluster 4) had longer time to achieve low disease activity when
compared with other similar clusters (Table.2).

Conclusion: This study
suggests that discrepancy between patient and physician global assessment,
severity of anxiety and depression can be useful to identify and distinguish
subgroups of RA patients. Severity of depression may be associated with longer
time to achieve low disease activity.  Given very small numbers in other
clusters except the reference cluster, further analyses will be necessary to
confirm these findings.

 

Table 1. Clinical characteristics of the patients, used as variables to define the clusters

Characteristics

Mean

(Min-Max)

Cluster 1

(n=134)

Cluster 2

(n=14)

Cluster 3

(n=16)

Cluster 4

(n=4)

Cluster 5

(n=2)

P1

Total Swollen

8.00(0.00-26.00)

7.50(2.00-26.00)

7.50(1.00-13.00)

5.50(2.00-8.00)

9.50(4.00-15.00)

0.90544

Total Tender

8.51(1.00-28.00)

7.71(1.00-19.00)

6.88(1.00-16.00)

8.00(5.00-12.00)

5.00(4.00-6.00)

0.85361

Physician Global Health

4.76(0.00-10.00)

4.89(2.00-8.50)

4.63(1.00-10.00)

4.13(3.00-6.00)

5.50(5.00-6.00)

0.84530

Patient Global Health

5.87(0.00-10.00)

5.75(2.50-9.00)

5.63(3.00-8.50)

6.13(5.00-8.50)

7.25(6.00-8.50)

0.81949

HAQ

3.02(0.00-7.70)

3.52(0.00-7.70)

2.33(0.30-6.30)

4.03(1.7-6.70)

2.50(1.70-3.30)

0.32824

Patient Pain VAS

6.37(0.50-10.00)

6.39(2.50-10.00)

6.66(3.00-10.00)

7.50(6.50-8.50)

8.75(8.50-9.00)

0.44445

CRP mg/dL

0.64(0.02-3.54)

0.45(0.03-1.29)

0.69(0.05-2.00)

0.71(0.05-1.45)

0.23(0.14-0.33)

0.60441

R3 Sleep

1.26(0.00-3.00)

1.36(0.00-2.00)

0.94(0.00-3.00)

1.00(0.00-2.00)

1.50(1.00-2.00)

0.46614

R3 Anxiety

0.72(0.00-3.00)234

1.50(1.00-3.00)68

0.25(0.00-1.00)9

2.00(2.00-2. 00)11

0.00(0.00-0.00)

0.00000

R3 Depression

0.72(0.00-3.00)35

0.50(0.00-2.00)68

1.25(1.00-2.00)910

0.00(0.00-0. 00)11

2.00(2.00-2.00)

0.00033

1 P values are p value Kruskal-Wallis Test for overall difference. 2 Cluster 1 significantly different from cluster 2(p≤0.05) 3 Cluster 1 significantly different from cluster 3(p≤0.05) 4 Cluster 1 significantly different from cluster 4(p≤0.05) 5 Cluster 1 significantly different from cluster 5(p≤0.05) 6 Cluster 2 significantly different from cluster 3(p≤0.05) 7 Cluster 2 significantly different from cluster 4(p≤0.05)

8 Cluster 2 significantly different from cluster 5(p≤0.05)  9 Cluster 3 significantly different from cluster 4(p≤0.05)  10 Cluster 3 significantly different from cluster 5(p≤0.05) 11 Cluster 4 significantly different from cluster 5(p≤0.05)

 

.

Table.2  Time to achieve low disease activity ( remission or mild disease activity by Clinical Disease Activity Index) for each cluster

 

Patients numbers

% of patients achieved Low disease activity

Mean time to achieve low disease activity

Cluster . *

5

17.39

68.25

Cluster 1

134

100

242.4

Cluster 2

14

100

263.2

Cluster 3

16

100

293.6

Cluster 4

4

100

86.8

Cluster 5

2

100

357.5

(*Among 175 subjects, 170 were qualified for cluster analysis)

 


Disclosure: Y. G. Hwang, None; J. Feng, None; H. Eng, None; J. Lyons, None; A. Fabio, None; L. W. Moreland, None.

To cite this abstract in AMA style:

Hwang YG, Feng J, Eng H, Lyons J, Fabio A, Moreland LW. Subgroups of Established Rheumatoid Arthritis Patients Can be Characterized By Patient and Physician Assessment Discrepancy, Anxiety and Depression and Presence of Depression Might be Associated with Slower Response to Treatment [abstract]. Arthritis Rheumatol. 2015; 67 (suppl 10). https://acrabstracts.org/abstract/subgroups-of-established-rheumatoid-arthritis-patients-can-be-characterized-by-patient-and-physician-assessment-discrepancy-anxiety-and-depression-and-presence-of-depression-might-be-associated-with/. Accessed .
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