Flares in Rheumatoid Arthritis Patients with Low Disease Activity: Predictability and Association with Worse Clinical Outcomes

Abstract

Objective:
To investigate predictors of flare in rheumatoid arthritis (RA) patients with low disease activity (LDA) and to evaluate the effect of flare on 12-month clinical outcomes.

Methods:
Patients with RA who were taking disease-modifying antirheumatic drugs and had a stable 28-joint count Disease Activity Score (DAS28) < 3.2 were eligible for inclusion. At baseline and every 3 months, clinical (DAS28), functional [Health Assessment Questionnaire-Disability Index (HAQ-DI), EQ-5D, Functional Assessment of Chronic Illness Therapy Fatigue scale (FACIT-F), Medical Outcomes Study Short Form-36 (SF-36)], serum biomarkers [multibiomarker disease activity (MBDA) score, calprotectin, CXCL10], and imaging data were collected. Flare was defined as an increase in DAS28 compared with baseline of > 1.2, or > 0.6 if concurrent DAS28 ≥ 3.2. Cox regression analyses were used to identify baseline predictors of flare. Biomarkers were cross-sectionally correlated at time of flare. Linear regressions were performed to compare clinical outcomes after 1 year.

Results:
Of 152 patients, 46 (30%) experienced a flare. Functional disability at baseline was associated with flare: HAQ-DI had an unadjusted HR 1.82 (95% CI 1.20-2.72) and EQ-5D had HR 0.20 (95% CI 0.07-0.57). In multivariate analyses, only HAQ-DI remained a significant independent predictor of flare (HR 1.76, 95% CI 1.05-2.93). At time of flare, DAS28 and its components significantly correlated with MBDA and calprotectin, but correlation coefficients were low at 0.52 and 0.49, respectively. Two-thirds of flares were not associated with a rise in biomarkers. Patients who flared had significantly worse outcomes at 12 months (HAQ-DI, EQ-5D, FACIT-F, SF-36, and radiographic progression).

Conclusion:
Flares occur frequently in RA patients with LDA and are associated with worse disease activity, quality of life, and radiographic progression. Higher baseline HAQ-DI was modestly predictive of flare, while biomarker correlation at the time of flare suggests a noninflammatory component in a majority of events.

Full text

1515
Bechman, et al: Flare in RA with LDA
Pers onal non -com merc ial use only. The Journal of Rheumatology Copyright © 2018. All rights reserved.
Flares in Rheumatoid Arthritis Patients with Low
Disease Activity: Predictability and Association with
Worse Clinical Outcomes
Katie Bechman, Lieke Tweehuysen, Toby Garrood, David L. Scott, Andrew P. Cope,
James B. Galloway, and Margaret H.Y. Ma
ABSTRACT.Objective.To investigate predictors of flare in rheumatoid arthritis (RA) patients with low disease
activity (LDA) and to evaluate the effect of flare on 12-month clinical outcomes.
Methods.Patients with RA who were taking disease-modifying antirheumatic drugs and had a stable
28-joint count Disease Activity Score (DAS28) < 3.2 were eligible for inclusion. At baseline and every
3 months, clinical (DAS28), functional [Health Assessment Questionnaire–Disability Index
(HAQ-DI), EQ-5D, Functional Assessment of Chronic Illness Therapy Fatigue scale (FACIT-F),
Medical Outcomes Study Short Form-36 (SF-36)], serum biomarkers [multibiomarker disease activity
(MBDA) score, calprotectin, CXCL10], and imaging data were collected. Flare was defined as an
increase in DAS28 compared with baseline of > 1.2, or > 0.6 if concurrent DAS28 ≥ 3.2. Cox
regression analyses were used to identify baseline predictors of flare. Biomarkers were cross-
sectionally correlated at time of flare. Linear regressions were performed to compare clinical outcomes
after 1 year.
Results.Of 152 patients, 46 (30%) experienced a flare. Functional disability at baseline was associated
with flare: HAQ-DI had an unadjusted HR 1.82 (95% CI 1.20–2.72) and EQ-5D had HR 0.20 (95%
CI 0.07–0.57). In multivariate analyses, only HAQ-DI remained a significant independent predictor
of flare (HR 1.76, 95% CI 1.05–2.93). At time of flare, DAS28 and its components significantly corre-
lated with MBDA and calprotectin, but correlation coefficients were low at 0.52 and 0.49, respectively.
Two-thirds of flares were not associated with a rise in biomarkers. Patients who flared had significantly
worse outcomes at 12 months (HAQ-DI, EQ-5D, FACIT-F, SF-36, and radiographic progression).
Conclusion.Flares occur frequently in RA patients with LDA and are associated with worse disease
activity, quality of life, and radiographic progression. Higher baseline HAQ-DI was modestly
predictive of flare, while biomarker correlation at the time of flare suggests a noninflammatory
component in a majority of events. (First Release September 1 2018; J Rheumatol 2018;45:1515–21;
doi:10.3899/jrheum.171375)
Key Indexing Terms:
RHEUMATOID ARTHRITIS LOW DISEASE ACTIVITY QUALITY OF LIFE
SERUM BIOMARKERS FLARE MULTIBIOMARKER DISEASE ACTIVITY SCORE
From the Academic Department of Rheumatology, Kings College London,
London; Department of Rheumatology, Guy’s and St Thomas’ UK National
Health Service (NHS) Foundation Trust, London, UK; Department of
Rheumatology, Sint Maartenskliniek, Nijmegen, the Netherlands.
This report represents independent research by Katie Bechman, partly
funded by the UK National Institute for Health Research (NIHR)
Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation
Trust and King’s College London. Margaret Ma’s work was funded by the
NIHR (DRF-2009-02-86 to M.H.Y. Ma).
K. Bechman, MBChB, BSc, Rheumatology Registrar and Clinical
Research Fellow, Academic Department of Rheumatology, Kings College
London; L. Tweehuysen, MD, Rheumatology Registrar and Clinical
Research Fellow, Department of Rheumatology, Sint Maartenskliniek;
T. Garrood, MBBS, MRCP, MSc, PhD, Consultant Rheumatologist,
Department of Rheumatology, Guy’s and St Thomas’ NHS Foundation
Trust; D.L. Scott, BSc, MD, FRCP, Professor of Rheumatology, Academic
Department of Rheumatology, Kings College London; A.P. Cope, BSc,
MBBS, PhD, FRCP, FHEA, Professor of Rheumatology, Academic
Department of Rheumatology, Kings College London; J.B. Galloway,
MBChB, MSc, CHP, MRCP, PhD, Consultant Rheumatologist/Senior
Lecturer, Academic Department of Rheumatology, Kings College London;
M.H. Ma, MBBS, BSc, MRCP, MSc, PhD, Consultant Rheumatologist,
Academic Department of Rheumatology, Kings College London.
Address correspondence to K. Bechman, Academic Rheumatology
Department, Third Floor, Room 3.46, Weston Education Centre, King’s
College London, London SE5 9RJ, UK. E-mail: katie.bechman@kcl.ac.uk
Accepted for publication April 27, 2018.
Guidelines for the treatment of rheumatoid arthritis (RA)
have emphasized a “treat-to-target” approach with the
explicit aim of low disease activity (LDA) states1,2. However,
disease activity in RA can fluctuate. Episodic worsening of
disease activity, described as “flare,” is common. Flare was
originally defined by the Outcome Measures in
Rheumatology Clinical Trials (OMERACT 9) group as a
cluster of symptoms of sufficient duration and intensity to
require initiation, change, or increase in therapy3. These
definitions focused on the more severe end of the flare
continuum for evaluation of flares in randomized controlled
trials. In daily practice, flare can vary in duration, intensity,
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frequency, and manageability4, with about half of patients in
remission experiencing a disease flare within 2 years5. This
has important clinical implications because flares in patients
with apparent LDA states are associated with radiographic
progression6,7, functional deterioration7, and worsening
cardiovascular comorbidity8.
Predicting flare is therefore of direct relevance to clinical
practice. Saleem, et al demonstrated that functional disability
[Health Assessment Questionnaire–Disability Index
(HAQ-DI)] and power Doppler ultrasound (PDUS) positivity
at baseline were independently associated with flare in
patients with RA in remission9. Further, a previous meta-
analysis revealed an association between PDUS positivity
and flare in RA patients in remission10.
The finding of PD positivity despite clinical remission
provides evidence that flares may be related to incomplete
suppression of inflammation. Based on this hypothesis,
serum biomarkers may detect subclinical disease activity and
consequently predict flare. In contrast to ultrasound (US),
biomarkers may have smaller measurement error and may be
less operator-dependent, costly, and time-consuming. In
recent years, the predictive values of the multibiomarker
disease activity (MBDA) score, calprotectin (S100A8/A9),
and CXCL10 for treatment response in RA have been inves-
tigated. In the DRESS study, baseline MBDA score was
predictive of flare and major flare in patients with LDA who
did not taper treatment (usual care group)11. To our
knowledge, calprotectin and CXCL10 have not been inves-
tigated as predictors of flare in disease-modifying anti-
rheumatic drug (DMARD)-treated patients with RA in an
LDA state. Calprotectin was found to be more strongly
associated with US-detected synovitis than erythrocyte
sedimentation rate (ESR) or C-reactive protein (CRP)12, and
baseline calprotectin appeared to be predictive of clinical
response to methotrexate13. However, its predictive role as a
marker of response to biologic DMARD is conflicting14,15.
CXCL10 was correlated with multiple disease activity
measures in early RA16, while elevated baseline levels of
CXCL10 were associated with favorable response to tumor
necrosis factor (TNF) inhibitor therapy in RA10.
The aims of our study were 3-fold. First, we aimed to
describe the frequency of flares in a cohort of prospective
patients with RA in stable LDA states (including remission)
over 1 year. Second, we aimed to examine the predictive
value of a wide range of biomarkers (including clinical,
functional, serum, and imaging variables) for flare. And third,
we aimed to evaluate the effect of flare in RA patients with
LDA states.
MATERIALS AND METHODS
Study design and patients. The REMIRA study is a prospective cohort study
investigating RA patients with stable LDA states including clinical
remission. Clinical outcomes have been reported recently17. Adult patients
with RA were eligible for inclusion if they were diagnosed according to the
1987 revised American College of Rheumatology criteria with a disease
duration < 10 years, had stable DMARD treatment for > 6 months, and
28-joint count Disease Activity Score (DAS28) < 3.2 for at least 1 month
apart. Three centers across South London participated: Guy’s and St.
Thomas’ Hospital, King’s College Hospital, and University Hospital
Lewisham National Health Service Foundation Trusts. Patients were
managed as part of routine care. The study was approved by the local ethics
committee and conducted according to the guidelines of the Declaration of
Helsinki (REC:09/H0803/154). Written informed consent was obtained from
all patients.
Clinical assessments. At baseline, demographic, disease and treatment
characteristics were collected. Clinical assessments were carried out every
3 months for 1 year and included pain and fatigue (both on visual analog
scale 0–100), DAS28, CRP, and ESR. Questionnaires were used to assess
function and quality of life: HAQ-DI, EQ-5D-3L, Medical Outcomes Study
Short Form-36 [SF-36; including physical component score (PCS) and
mental component score (MCS)] and Functional Assessment of Chronic
Illness Therapy Fatigue scale (FACIT-F). Flare was defined according to
previously validated criteria: a DAS28 increase of > 1.2 compared with
baseline or a DAS28 increase of > 0.6 compared with baseline and
concurrent DAS28 ≥ 3.218. For patients with multiple flares, only the first
flare was considered in the analyses.
Serum biomarker measurements. Serum samples were obtained at each
timepoint and stored at –80°C until being shipped frozen to the Crescendo
Bioscience Clinical Laboratory (South San Francisco, California, USA) for
MBDA score, calprotectin, and CXCL10 measurement. The MBDA test
(Vectra DA, Crescendo Bioscience) combines the serum concentrations of
12 protein biomarkers [interleukin 6, TNF receptor type I, vascular cell
adhesion molecule 1, epidermal growth factor, vascular endothelial growth
factor A, YKL-40, matrix metalloproteinase 1, matrix metalloproteinase 3,
CRP, serum amyloid A (SAA), leptin, and resistin] in an algorithm to provide
a score that quantifies RA disease activity. The scores are on a scale of 1 to
100 with validated categories for low (≤ 30), moderate (30–44), and high
disease activity (> 44)19. Calprotectin and CXCL10 were measured by
ELISA (Buhlmann MRP 8/14 ELISA Product Code EK-MRP8/14m; R&D
Systems Human CXCL10/IP-10 Quantikine ELISA Product Code DIP100).
Imaging assessments. Ultrasonography of hands and wrists, and conven-
tional radiographs of hands and feet were carried out at baseline and 12
months. Erosive progression was defined as new or larger erosions over 1
year on radiographs. All sonographic assessments were performed using
high-sensitivity US equipment (GE Logiq 9) with a 2-dimensional M12L
transducer. A single experienced sonographer (TG), blinded to clinical or
laboratory data, scanned 10 metacarpophalangeal joints and 2 wrists from a
dorsal aspect for greyscale US (GSUS) synovial hypertrophy and intra-
articular PDUS signals20. GSUS and PDUS were graded on a scale of 0 to
3 using a validated semiquantitative scoring system21. The composite GSUS
and PDUS scores were the sum scores of the 12 individual joints.
Statistical analysis. Descriptive statistics were provided with mean (± SD),
median (interquartile range; IQR), or frequencies, depending on data distri-
bution. Cross-sectional correlations between all measurements (biomarkers
and DAS28 components) at time of flare were assessed by Spearman’s
correlation coefficient (rs), and interpreted according to commonly used
classification: very weak (rs < 0.20), weak (rs = 0.20–0.39), moderate
(rs = 0.40–0.59), strong (rs = 0.60–0.79), and very strong (rs > 0.80)
correlation22.
To identify predictors of time to flare, we performed univariate Cox
regression, in which time to flare was the dependent variable, and clinical,
functional, serum, and imaging measurements the independent variables.
Multivariate analyses were performed to identify factors that were independ-
ently associated with flare, adjusting for age, sex, DAS28, visual analog
scale (VAS) pain, CRP, ESR, and US scores (for HAQ model only), and
MBDA score (for EQ-5D model only).
Linear regression was used to determine the effect of flare on 12-month
clinical outcomes (i.e., disease activity and functional status). A multivariate
linear regression model was applied adjusting for baseline age, sex, disease
1516 The Journal of Rheumatology 2018; 45:11; doi:10.3899/jrheum.171375
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duration, erosive status, baseline DAS28, HAQ, and baseline variable of
interest. A p value ≤ 0.05 was regarded as significant. Because this was an
exploratory study, no correction for multiple hypothesis testing was
performed. Missing data were addressed using a multiple imputation module
(Supplementary Data 1, available from the authors on request). All analyses
were performed with STATA 14.1 statistical software.
RESULTS
Patient characteristics. In total, 152 patients were enrolled
in the REMIRA study. Baseline characteristics are depicted
in Table 1. The majority of patients were receiving DMARD
monotherapy (n = 69; 45%) and the median disease duration
was 3 (IQR 2–6) years. Ninety-seven patients (66%) fulfilled
DAS28 remission criteria (DAS28 < 2.6). All patients had
synovial hypertrophy (GSUS > 1) and 90% had detectable
PDUS activity at baseline.
Characteristics of flare. Forty-six patients (30%) experienced
at least 1 flare. Twelve patients had first flare by 3 months,
10 by 6 months, 11 by 9 months, and 13 by 12 months.
Seventeen patients experienced multiple flares; 11 patients
flared at 2 visits, 5 patients at 3 visits, and 1 patient at all 4
visits after baseline. When limiting the cohort to patients who
were in remission defined by DAS28 < 2.6 at baseline, 24
patients of a total 97 (25%) experienced at least 1 flare.
Serum biomarkers at time of flare. There were 70 individual
flare events. Seventeen percent (n = 12) of flares were driven
solely by increases in patient’s global assessment (PtGA) and
tender joint count (TJC), without any increase in swollen
joint count (SJC) or ESR.
In total, 33% of flares (n = 23) had a concurrent high
MBDA score (> 44), while 13% (n = 44) of visits without
flare had a high MBDA score. The levels of ESR, CRP,
MBDA score, and calprotectin were significantly higher at
flare visits than at nonflare visits [median ESR 14 mm/h (IQR
5–23) vs 6 mm/h (3–12); CRP 5 mg/l (5–9) vs 5 mg/l (5–5);
MBDA 38 (25–50) vs 28 (18–38); and calprotectin 2916
ng/ml (2002–4186) vs 2377 ng/ml (1504–3358)].
DAS28 significantly correlated with MBDA score
(rs= 0.5, p = 0.0002) at time of flare. The rsof 0.5 suggests
that the MBDA values explain only 25% of the variation in
DAS28. The correlation of MBDA was stronger with the
components ESR and SJC, and were nonsignificant for TJC
and PtGA. Similar findings were seen for calprotectin
(rs = 0.49, p = 0.0007). CXCL10 did not correlate with
DAS28 or its components at time of flare (Supplementary
Table 1, available from the authors on request).
Prediction of flare. Univariate Cox regression showed that
several baseline characteristics were associated with flare
(DAS28, ESR, CRP, PtGA, VAS pain, HAQ-DI, and EQ-5D;
Figure 1 and Supplementary Tables 2 and 3, available from
the authors on request). The strongest magnitude of associ-
ation was seen with HAQ-DI and EQ-5D. Baseline US
synovitis (GSUS or PDUS) and mental health (using the
SF-36 MCS) were not associated with flare. Baseline MBDA
scores were also not predictive of flare, although a sensitivity
analysis limited to flares with a rise in MBDA score to > 44
(high disease activity) did show a relationship between
baseline MBDA value and flare risk, with each unit rise in
baseline MBDA score associated with a 7% increase in flare
risk (1.07, 95% CI 1.02–1.11; p = 0.005; Supplementary
Tables 4 and 5). Analyzing each component of the MBDA
score identified SAA, leptin, and high-sensitivity CRP as the
strongest predictors of flare. The remaining 9 components of
the MBDA score did not individually predict flare.
The imputation model confirmed the association between
flare and baseline HAQ-DI and EQ-5D but did not demon-
strate any other associations. In multivariate analyses, only
baseline HAQ-DI remained a significant independent
1517
Bechman, et al: Flare in RA with LDA
Pers onal non -com merc ial use only. The Journal of Rheumatology Copyright © 2018. All rights reserved.
Table 1. Patient characteristics.
Characteristics Patients, n = 152
Age, yrs, mean (SD) 57 (14)
Female sex, n (%) 101 (66)
Disease duration, yrs 3 (2–6)
Treatment, n (%)
csDMARD monotherapy 69 (45)
csDMARD combination therapy 59 (39)
bDMARD therapy 24 (16)
Prednisolone 3 (2)
Seropositive (RF and/or ACPA), n (%) 103/137 (75)
Erosive, n (%) 67 (45)
TJC28 0 (0–1)
SJC28 0 (0–2)
PtGA, 0–100 mm 19 (10–36)
ESR 7 (4–13)
CRP, mg/l 5 (1–31)
DAS28-ESR, mean (SD) 2.1 (0.9)
DAS28 remission, n (%) 97/148 (66)
VAS pain, 0–100 mm 15 (3–34)
HAQ-DI 0.25 (0–0.86)
EQ-5D 0.76 (0.69–1.00)
SF-36 PCS, mean (SD) 46 (11)
SF-36 MCS, mean (SD) 51 (10)
FACIT-F 42 (34–47)
MBDA score, 1–100 31 (18–39)
Calprotectin, ng/ml 2358 (1487–3358)
CXCL10, pg/ml 198 (143–291)
No. (%) patients with GSUS > 0 104/104 (100)
Total GSUS score, /36 12 (8–14)
No. (%) patients with PDUS > 0 93 (90)
Total PDUS score, /36 2 (1–4)
Data are median (IQR) unless otherwise specified. IQR: interquartile range;
csDMARD: conventional synthetic disease-modifying antirheumatic drug;
bDMARD: biologic DMARD; RF: rheumatoid factor; ACPA: anticitrulli-
nated protein antibody; TJC28: tender joint count at 28 joints; SJC28:
swollen joint count at 28 joints; PtGA: patient’s global assessment; CRP:
C-reactive protein; ESR: erythrocyte sedimentation rate; DAS28: 28-joint
count Disease Activity Score; VAS: visual analog scale; HAQ-DI: Health
Assessment Questionnaire–Disability Index; SF-36 PCS: Medical Outcomes
Study Short Form-36 physical component summary; SF-36 MCS: Medical
Outcomes Study Short Form-36 mental component summary; FACIT-F:
Functional Assessment of Chronic Illness Therapy Fatigue scale; MBDA:
multibiomarker disease activity; GSUS: greyscale ultrasound synovial
hypertrophy; PDUS: intraarticular power Doppler ultrasound signals.
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predictor of flare (HR 1.76, 95% CI 1.05–2.93, p = 0.03;
Supplementary Table 2, available from the authors on
request).
Outcomes in flare versus sustained remission group.
Adjusting for baseline values, patients who had a flare experi-
enced significantly worse clinical outcomes at 12 months
than patients in sustained remission, reflected by higher
disease activity, worse functional outcomes, and higher
radiographic progression scores (Table 2). Having a flare was
associated with a larger than minimal clinically important
difference increase in HAQ-DI (β = 0.32, 95% CI 0.29–0.36;
p < 0.01) and decrease in EQ-5D (β = –0.11, 95% CI –0.12
to –0.09; p < 0.01). Both the physical and mental
performance measures from SF-36 were significantly worse
in patients who flared in the unadjusted model. This was
more marked with the PCS and did not remain significant
with the MCS in the adjusted model. Patients who flared were
3.6 times (95% CI 2.77–4.67; p < 0.01) more likely to have
erosive progression, defined as new or larger erosions over 1
year on radiographs.
DISCUSSION
In this prospective study, one-third of RA patients with LDA
states experienced a flare during 12 months of followup. This
is similar to flare rates reported in cohort studies, although
these included only patients in remission5,9 and in drug
tapering studies in patients who remain on stable therapy. In
both the DRESS23 and the POET24 studies, the rate of
short-lived flare was significantly higher in patients who
tapered or stopped their anti-TNF therapy compared to those
who continued treatment, although in the DRESS study, the
rate of major flares was similar between the 2 groups.
In our study, we have shown that the occurrence of a flare
is hard to predict, but undeniably associated with worse
clinical outcomes at 12 months. Our study highlights that
identification of predictors of flare in patients with LDA
states is challenging. In accordance with a previous remission
cohort study9, we found that HAQ-DI, a measure of
functional activity, reflected by difficulties in activities of
daily living, was predictive for flare. It is plausible that
patients with LDA and high functional disability are more
likely to flare. Functional impairment can herald a flare with
the onset of morning stiffness and fatigue. A high HAQ may
reflect severe rheumatoid arthritis with disease-related
damage and the likelihood of grumbling disease (persistent
low-grade disease activity).
Serum biomarkers were only modestly correlated with
DAS28 at the time of flare. This might be because a flare is
defined by worsening of the DAS28 composite score, and an
increase in TJC and PtGA alone may increase the DAS28
1518 The Journal of Rheumatology 2018; 45:11; doi:10.3899/jrheum.171375
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Figure 1. Univariate analyses of prediction of flare with baseline variables. DAS28: 28-joint count Disease Activity Score; PGA: patient’s global assessment;
VAS: visual analog scale; ESR: erythrocyte sedimentation rate; CRP: C-reactive protein; HAQ-DI: Health Assessment Questionnaire–Disability Index.
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score to a sufficient level to define a flare. It is possible that
a flare event is not solely the result of direct synovial inflam-
mation but may be driven by other pathways, for example
chronification of pain due to central sensitization and
abnormal regulatory mechanisms25. This heterogeneity may
partly explain why identifying predictors of flare is
challenging. The OMERACT RA flare group recognizes the
limitation of DAS28 in defining flare events. They are devel-
oping a consensus-based core domain set to identify and
measure flare in RA26,27. It is likely that improving the
definition of flare and establishing a scoring system may help
interpret predictors of flare in the future.
We found that a higher baseline CRP and ESR were
predictive of flare in the univariate analyses, while baseline
MBDA score, calprotectin, and CXCL10 were not. In the
sensitivity analysis limited to flare events with an associated
high MBDA score at the time of flare, a relationship between
baseline MBDA value and flare risk was established. This
may suggest that baseline MBDA score is only predictive of
flares that are driven directly by inflammation. Interestingly,
when each component of the MBDA score was analyzed
individually, only 3 of the 12 components (SAA, leptin, and
high-sensitivity CRP) predicted flare. Studies suggest a close
correlation between leptin levels and RA disease duration,
activity, and severity28. The rapid production of SAA and its
exceptionally wide dynamic range has proved advantageous
as a biomarker of disease activity, with superiority over CRP
in early RA studies29.
US variables, including PD signal, had no predictive value
in our study. This is likely a reflection of the high proportion
of patients in our cohort who had US activity at baseline. In
the POET study, only 63% of patients had US signs of
arthritis with positive PD signal30. This is partly explained
by our cohort, which included a greater proportion of patients
with LDA states above the DAS28 remission cutoff. A large
number of patients were taking DMARD monotherapy, and
only 3 were prescribed oral corticosteroids, which may
explain the difference in PD compared to other cohorts that
have achieved LDA states with combination DMARD and
corticosteroid therapy. Scoring of PD was also more stringent
in our cohort compared to others9, leading to a much higher
proportion of patients with PD signal being reported. The
major limitation of US is that it remains a user-dependent
technique. It is increasingly sensitive at demonstrating
evidence of incomplete suppression of inflammation. The
joints of healthy volunteers have been shown to display PD
signal31,32, and treatment escalation studies have argued
against very stringent US targets33. Others have also shown
that low-grade PD signal and synovial hypertrophy may not
necessarily reflect the presence of active synovitis in RA
joints34. In our cohort, a high proportion had PD activity at
baseline and did not go on to flare. It may be postulated that
a binary PD cutoff might be insensitive in discriminating
patients who are likely to flare.
Our study also found that patients who flare were more
likely to have erosive progression, worse quality of life, and
higher disease activity over 1 year. These findings are
consistent with previous studies7,9,35 and emphasize the
1519
Bechman, et al: Flare in RA with LDA
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Table 2. Outcomes at 1 year in patients who flare compared to patients who do not flare.
Measure Outcome β constant 95% CI p
HAQ-DI Unadjusted 0.59 0.37–0.80 < 0.01
Adjusted 0.19 0.04–0.32 0.01
Imputed (adjusted) 0.32 0.29–0.36 < 0.01
EQ-5D Unadjusted –0.19 –0.26 to –0.13 < 0.01
Adjusted –0.11 –0.18 to –0.05 < 0.01
Imputed (adjusted) –0.11 –0.12 to –0.09 < 0.01
SF-36 PCS Unadjusted –8.79 –12.4 to –5.18 < 0.01
Adjusted –3.92 –7.04 to –0.8 0.01
Imputed (adjusted) –5.17 –5.81 to –4.53 < 0.01
SF-36 MCS Unadjusted –5.42 –9.41 to –1.42 0.01
Adjusted –2.86 –6.83 to 1.12 0.16
Imputed (adjusted) –2.94 –3.7 to –2.18 < 0.01
FACIT-F Unadjusted –7.83 –11.6 to –4.06 < 0.01
Adjusted –4.07 –7.91 to –0.24 0.04
Imputed (adjusted) –5.09 –5.77 to –4.42 < 0.01
DAS28 Unadjusted 1.32 0.96–1.68 < 0.01
Adjusted 1.07 0.77–1.37 < 0.01
Imputed (adjusted) 1.00 0.94–1.06 < 0.01
Erosive progression Unadjusted 2.33* 0.87–6.27 0.09
Adjusted 3.51* 1.06–11.7 0.04
Imputed (adjusted) 3.60* 2.77–4.67 < 0.01
* OR values. HAQ-DI: Health Assessment Questionnaire–Disability Index; SF-36 PCS: Medical Outcomes Study Short Form-36 physical component summary;
MCS: mental component summary; FACIT-F: Functional Assessment of Chronic Illness Therapy Fatigue scale; DAS28: 28-joint count Disease Activity Score.
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importance of flare and its relationship with patient
outcomes. What remains unclear is whether flares are
causally implicated in clinical outcome or if they are merely
a biomarker of persistent low-grade disease. A flare may
imply persistent uncontrolled inflammation contributing to
disease progression or a transient episode of inflammation
(e.g., a 6-week flare within a stable 6-month period) that is
sufficient to affect longterm outcome, or signify negative
patient experience, and a lack of self-control and unpre-
dictability of the disease, which undoubtedly have psycho-
logical health implications.
There were several strengths of our study. The cohort was
selected from routine care, which is far more representative
than a highly selective clinical trial population. Using patients
in LDA states rather than remission enables access to a
broader range of patients and is more in keeping with routine
clinical care. Further, this was a deeply phenotyped cohort
with extensive clinical and laboratory data at multiple
timepoints across the study period.
There are potential limitations to our study. We must
acknowledge the limitation of the REMIRA study sample
size, and the limited number of predictors identified could
reflect a type 2 error. We also acknowledge issues with
missing data, particularly with incomplete available US
reports. However, the pattern of missing data met the assump-
tions of missing at random and we were able to successfully
construct an imputation model to address this. We only regis-
tered flares during a visit to a rheumatologist and the actual
flare rate might be higher. Potential flares between visits
could have been detected by a flare questionnaire36 or alter-
native tools that permit remote monitoring. However, we
would have missed only short-lived flares (< 3 mos), and
those are of less clinical importance because they are less
likely to lead to worse clinical outcomes (e.g., no
radiographic progression)23. REMIRA was an observational
study and any modifications in medications were carried out
according to the physicians’ and patients’ choices. Because
treatment was not protocolized, this may have affected the
rate of flares. A single failure model was used to identify
predictors of flare, and thus changes in therapy after a flare
event should not influence the analysis. It is, however,
possible that treatment modifications, for example, glucocor-
ticoids during a flare, may improve disease outcome at 12
months.
We have demonstrated that flares are common in RA
patients with LDA states and are strongly associated with
poor clinical outcomes. Therefore, preventing flares is clini-
cally relevant yet relatively challenging. HAQ-DI, a measure
of functional activity, was an important predictor of flare.
However, flares are complex events and not simply a
reflection of inflammatory disease activity. It is possible that
2 distinct subtypes of flare might exist: an “inflammatory”
flare predominately driven by an increase in SJC and ESR,
and a “noninflammatory” flare with a disproportionately
elevated TJC and a high PtGA score. Differentiating these 2
flare types may identify potential predictors. Further research
is needed to determine whether distinct flares exist and to
categorize the potential predictors of each.
ACKNOWLEDGMENT
We acknowledge the Crescendo Bioscience team, in particular Eric Sasso
and Nadine Defranoux, for processing the REMIRA blood samples and
assisting in the completion of this manuscript. We also acknowledge Dr.
Stephen Kelly for his advice on setting up the US protocols.
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