POS1300 PAIN IN CHILDREN WITH JUVENILE IDIOPATHIC ARTHRITIS TREATED TO TARGET: 24 MONTH RESULTS FROM A RANDOMISED TRIAL

Background:

Juvenile Idiopathic Arthritis (JIA) is the most common auto-immune disease in children and pain is a common symptom. Despite treatment advances in recent years, pain often persists when the disease is inactive. Treating JIA to target has been widely recommended1, but effectiveness in pain reduction has not been proven yet2.

Objectives:

To compare pain scores over two years in three treatment arms in JIA patients that were treated to target and to identify baseline characteristics predicting unfavorable pain outcomes.

Methods:

DMARD naïve children who participated in the BeSt for kids study3 with oligoarticular JIA, RF negative polyarticular JIA and juvenile psoriatic arthritis were included. Patient were treated to target aimed at inactive disease according to 1 of 3 different treatment groups; 1) initial sequential DMARD monotherapy 2) initial methotrexate (MTX) with prednisolone bridging or 3) initial MTX with etanercept. Pain intensity was measured using a 100 mm Visual Analogue Scale during 24 months of follow up with 3-monthly intervals. Potential differences in VAS pain scores over time between treatment arms were compared using linear mixed models with random intercept and random slope for visits clustered within patients. A similar multivariable mixed model was used to assess the ability of several baseline characteristics to predict the chance of high pain levels during follow-up.

Results:

92 patients were randomized into the three treatment groups. Overall, pain scores over time reduced from mean 55.3 (SD 21.7) at baseline to 19.5 (SD 25.3) after 24 months. When comparing pain over time per arm, pain scores decreased significantly over time β -1.37 (95% CI -1.726; -1.022). No significant difference was found in pain over time between treatment groups (interaction term treatment arm*time (months) β (95% CI) arm 1 0.13 (-0.36; 0.62) and arm 2 0.37 (-0.12; 0.86) compared to arm 3), Figure 1. Correction for sex and symptom duration as possible confounders yielded similar results. Multiple baseline characteristics demonstrated a significant predictive value for pain over time: VAS pain (scale 0-100) with β 0.44 (95% CI 0.25; 0.65), VAS physician (scale 0-100) with β -0.34 (-0.55; -0.06), number of active joints with β 0.77 (0.19; 1.34), Child Health Questionnaire Physical summary Score with β -0.42 (-0.72; -0.11) and Psychosocial summary Score β -0.42 (-0.77; -0.06). Symptom duration, VAS patient/parent and NSAID use were no significant predictors, Table 1.

Conclusion:

Treatment to target seems effective in pain reduction in non-systemic JIA patients irrespective of initial treatment strategy. Several baseline predictors for pain over time were identified, which could serve as an initial indication for non-systemic JIA-patients with a high risk of pain despite a strict treat-to-target strategy.

References:

[1]Ravelli A, Consolaro A, Horneff G, et al. Treating juvenile idiopathic arthritis to target: recommendations of an international task force. Ann Rheum Dis. 2018;77(6):819–828.

[2]Schoemaker, C.G., Swart, J.F. & Wulffraat, N.M. Treating juvenile idiopathic arthritis to target: what is the optimal target definition to reach all goals?. Pediatr Rheumatol. 18, 34 (2020)

[3]Hissink Muller P, Brinkman DMC, Schonenberg-Meinema D, et al. Treat to target (drug-free) inactive disease in DMARD-naive juvenile idiopathic arthritis: 24-month clinical outcomes of a three-armed randomised trial. Ann Rheum Dis. 2019 Jan;78(1):51-59.

Table 1.

Baseline Characteristics

βp-value95% Confidence IntervalVAS Pain0.450.0000.25 to 0.65VAS Physician-0.310.014-0.55 to -0.06VAS Patient/parent-0.020.873-0.21 to 0.18No. of active joints0.770.0090.19 to 1.34PhS*-0.420.008-0.72 to -0.11PsS**-0.420.022-0.77 to -0.06Symptom duration (mo.)8.090.118-2.08 to 18.26NSAID use-1.300.791-10.91 to 8.31

VAS Pain, VAS physician and VAS patient/parent was measures on a 100mm scale.

*PhS= Physical Summary Score of the Child Health Questionnaire Parent form 50 (scale 0-100).

**PsS= Psychosocial Summary Score of the CHQ-PF50 (scale 0-100).

Disclosure of Interests:

None declared

POS0178 GENE SIGNATURE FINGERPRINTS DIVIDE SLE PATIENTS IN SUBGROUPS WITH COMPARABLE BIOLOGICAL DISEASE PROFILES: A MULTICENTRE LONGITUDINAL STUDY

Background:

Even in the hands of experienced clinicians, clinical phenotyping and predicting treatment responses in Systemic Lupus Erythematosus (SLE) patients remains challenging. Therefore, the identification of biomarkers that can help physicians to divide patients into subgroups based upon aberrantly activated pathways is relevant and might guide future treatment strategies. Extensive blood transcriptional profiling has identified various gene modules that seem promising for stratification of SLE patients into subgroups (1). However, the feasibility to implement these complicated and expensive tests for use in the daily practice of routine clinical laboratories is challenging if not impossible.

Objectives:

The aim of this study was to develop gene signatures that stratify patients into groups with comparable disease profiles and are feasible to perform in routine clinical laboratories.

Methods:

To identify coordinated expression of a set of genes and reduce data complexity, genes from 4 previously described modules (Interferon M1.2, Interferon M5.12, Neutrophil- and Plasmablast (PB)(1)) were measured using real-time quantitative PCR expression on whole blood RNA samples. Subsequently, a principle component analysis was used to select 2-5 indicator genes, that represent a specific signature. Expression levels of these genes were measured in healthy donors (n=42) and samples from two independent childhood-onset SLE cohorts (n=51 and n=20). Scores higher than the mean + 2 S.D. score of healthy controls were defined as high gene signature scores. Based on their expression levels, gene signatures were divided over 14 clusters. Associated clusters were subsequently grouped into three gene fingerprints termed 1) all-signatures-low, 2) only high IFN (M1.2 and/or M5.12) and 3) high PB and/or Neutrophil. Disease activity was measured by the SELENA-SLEDAI score.

Results:

All four gene signatures were higher expressed in patients compared to healthy controls and showed a significant correlation with the SLEDAI. The PB signature showed the highest association with disease activity (r= 0.6512, P<0.0001). In longitudinally collected samples, the PB signature was reduced in patients who were on treatment and showed a significant trend with the SLEDAI. When patients were divided into the described gene fingerprints, the highest SLEDAI scores (median score=8) were observed in the high PB-Neutrophil group. The lowest disease activity (median score =2) was observed in the all-signatures-low group. The same distribution was seen when samples from a second time point were divided based on this stratification method and this was also reproduced in samples from an independent SLE cohort (figure 1).

Conclusion:

Various gene signatures are associated with disease activity, which underlines the involvement of different pathophysiological mechanisms in SLE. Combining these signatures into gene fingerprints can help to stratify patients into comparable groups and guide individualized treatment choices for patients in the future.

References:

[1]Banchereau R, Hong S, Cantarel B, Baldwin N, Baisch J, Edens M, et al. Personalized Immunomonitoring Uncovers Molecular Networks that Stratify Lupus Patients. Cell. 2016;165(6):1548-50.

Figure 1.

SELENA-SLEDAI scores based on gene fingerprint distribution. Blue indicates time point one of cohort 1 (n=51); pink indicates time point two of cohort 1 (n=45); red indicates time point one of the replication cohort (n=20)

Disclosure of Interests:

None declared

POS1311 SCLERODERMA PATTERN IN NAILFOLD CAPILLARIES OF (CHILDHOOD-ONSET) SYSTEMIC LUPUS ERYTHEMATOSUS: LESSONS FROM LONGITUDINAL FOLLOW-UP

Background:

It has been suggested that a capillary scleroderma pattern in patients with systemic lupus erythematosus (SLE)-patients predisposes for clinical signs of systemic sclerosis (SSc) or overlap disease (1). However, this was previously shown not to be the case in a cross-sectional study in childhood-onset SLE (cSLE) (2).

Objectives:

To assess if nailfold capillary patterns in cSLE change over time and if a capillary scleroderma pattern is associated with prospective development of clinical SSc-features, higher SLE disease activity or –damage.

Methods:

Prospective clinical and capillaroscopy data were used from a longitudinal cohort of cSLE patients. Patients with a disease onset before the age of 18 years and diagnosis according to SLICC 2012 criteria were included. Disease activity was defined by SLEDAI score and disease damage by the SLICC damage index. Nailfold images from eight fingers (excluding thumbs) were obtained by videocapillaroscopy. A scleroderma pattern was defined according to the ‘fast track algorithm’ (3). An abnormal capillary pattern that did not match the criteria for a scleroderma pattern was defined as ‘microangiopathy’.

Results:

Our longitudinal study cohort consisted of n=53 cSLE patients with a median disease onset of 14 years (IQR 12.5-15.5 years) and a median SLEDAI score at diagnosis of 11 (IQR 8-15.5). Clinical follow-up data were available from 0.5-16 years after disease onset. Median disease duration at first capillaroscopy was 17 months (IQR 5.5-51.5 months) and 17/53 (32.1%) of patients had Raynaud’s phenomenon. In total, n=9 (17%) showed a scleroderma pattern (at some point in time), n=37 (70%) had microangiopathy and n=7 (13%) showed a normal capillary pattern. N=27 patients had follow up with capillaroscopy (1-7 times over 1-5 years). In most patients (23/27) we did not observe any change in capillary pattern during follow-up. Two patients showed changes from microangiopathy to a scleroderma pattern, one patient from a scleroderma pattern to microangiopathy and one patient from microangiopathy to a normal pattern. Raynaud’s phenomenon was equally distributed among patients with different capillaroscopy patterns (p=0.487), as was median SLEDAI score at diagnosis (p=0.285). Follow-up patients with a capillary scleroderma pattern did not show any clinical features for SSc over time (follow-up over 1-5 years, Table 1 below. Patients with a capillary scleroderma pattern showed significantly more disease damage (Chi-square, p=0.008), also indicated by a survival analysis for disease damage (Figure 1, p=0.042).

Conclusion:

Our study indicates that a capillary scleroderma pattern in cSLE correlates with disease damage but not with clinical SSc features during follow-up period.

References:

[1]S. Pavlov-Dolijanovic et al. Is there a difference in systemic lupus erythematosus with and without Raynaud’s phenomenon? Rheum Int 2013;33: 859–865

[2]D. Schonenberg-Meinema et al. Nailfold capillary abnormalities in childhood-onset systemic lupus erythematosus. Revised manuscript after review re-submitted to Lupus in January 2021

[3]V. Smith et al. Fast track algorithm. Autoimm Rev 2019 Nov;18(11): 102394

Table 1.

Clinical characteristics of cSLE-patients (n=9/53) with a nailfold capillary scleroderma pattern

Butterfly rashPhotosensitive rashLupus nephritisAutoimmune cytopeniaPositive CoombsLow C3/C4SerositisDamageType of auto-antibodiesFollow-up in years1++-+++-+ANA, Anti-ds-DNA, anti-Sm, anti-RNP, anti-Ro52, anti-SS-A52++-+++-+ANA, Anti-ds-DNA, anti-Sm, anti-RNP, anti-SS-A53-+++++++ANA, Anti-ds-DNA, anti-Sm, anti-RNP, anti-SS-A104-++-++++ANA, Anti-ds-DNA, anti-Sm, anti-RNP, anti-Ro52, anti-SS-A95-+--+-+-ANA1 (lost)6-++++++-ANA, Anti-ds-DNA, anti-c1q37---+----ANA, Anti-ds-DNA, anti-Sm, anti-RNP18++-+----ANA99-+++++++ANA, Anti-ds-DNA, anti-RNP, anti-SS-A8Figure 1.

Occurrence of disease damage (with survival as ‘no damage’) in cSLE patients with microangiopathy (blue) and a capillary scleroderma pattern (red)

Disclosure of Interests:

None declared

A comparison of three treatment strategies in recent onset non-systemic Juvenile Idiopathic Arthritis: initial 3-months results of the BeSt for Kids-study

BACKGROUND

Combination therapy with prednisone or etanercept may induce earlier and/or more improvement in disease activity in Disease Modifying Anti Rheumatic Drug (DMARD) naïve non-systemic Juvenile Idiopathic Arthritis (JIA) patients. Here we present three months clinical outcome of initial treatments of the BeSt-for-Kids study.

METHODS

Included patients were randomized to either: 1. initial DMARD-monotherapy (sulfasalazine (SSZ) or methotrexate (MTX)), 2. Initial MTX / prednisolone-bridging, 3. Initial combination MTX/etanercept. Percentage inactive disease, adjusted (a) ACR Pedi30, 50 and 70 and JADAS after 6 and 12 weeks of treatment (intention to treat analysis) and side effects are reported.

RESULTS

94 patients (67% girls, 32 (arm 1), 32 (arm 2) and 30 (arm 3) with median (InterQuartileRange) age of 9.1 (4.7-12.9) years were included. 38% were ANA positive, 10 had oligo-articular disease, 68 polyarticular JIA and 16 psoriatic arthritis. Baseline median (IQR) ACRpedi-scores: VAS physician 49 (40-58) mm, VAS patient 54 (37-70) mm, ESR 6.5 (2-14.8)mm/hr, active joint count 8 (5-12), limited joint count 3 (1-5), CHAQ score 0.88 (0.63-1.5). In arm 1, 17 started with MTX, 15 with SSZ. After 3 months, aACR Pedi 50 was reached by 10/32 (31%), 12/32(38%) and 16/30 (53%) (p = 0.19) and aACR Pedi 70 was reached by 8/32 (25%), 6/32(19%) and 14/30(47%) in arms 1-3 (p = 0.04). Toxicity was similar. Few serious adverse events were reported.

CONCLUSION

After 3 months of treatment in a randomized trial, patients with recent-onset JIA achieved significantly more clinical improvement (aACRPedi70) on initial combination therapy with MTX / etanercept than on initial MTX or SSZ monotherapy.

TRIAL REGISTRATION

NTR1574 . Registered 3 December 2008.

Axillary and rectal temperature measurements poorly agree in newborn infants

AIM

Evaluation of the agreement between axillary temperature measurements and rectal temperature measurements in neonates.

METHODS

Rectal and axillary body temperatures were simultaneously measured for 3 min in 33 neonates (gestational age 25-42 weeks, weight 840-4,005 g). Two investigators performed paired measurements, one in each neonate. A single type of thermometer was used in this study: one thermometer for each rectal and another thermometer for each axillary measurement. The Bland-Altman method was used (95% 'limits of agreement': mean +/- 2 SD) to determine the level of agreement between axillary and rectal measurements.

RESULTS

The axillary temperature was significantly lower than the rectal temperature (mean +/- SD 0.27 +/- 0.20 degrees C, p < 0.05). The '95% limits of agreement' ranged from -0.13 to +0.67 degrees C. Increasing postnatal age (days) showed a significant increase in temperature difference (rectal minus axillary; r = 0.54; p < 0.05).

CONCLUSIONS

The mean difference between axillary and rectal temperature shows a wide variation. Axillary temperature measurements cannot be used interchangeably with rectal measurements in neonates.