Effect of adjuvant chemotherapy on localized dedifferentiated low-grade osteosarcoma: a systematic review

PURPOSE

Dedifferentiated low-grade osteosarcomas, which are considered high grade malignancies, can arise from the dedifferentiation of parosteal and low-grade osteosarcomas. Usually, localized dedifferentiated low-grade osteosarcomas are treated by wide resection, and the efficacy of adjuvant chemotherapy is controversial. We conducted a systematic review of studies that investigated the rates of mortality and significant events, such as recurrence and metastases, in localized dedifferentiated low-grade osteosarcoma patients who received wide resection only and in those who received wide resection and (neo-)adjuvant chemotherapy.

METHODS

We identified 712 studies through systematic searches of Embase, PubMed, and the Cochrane Central Register of Controlled Trials databases. Of those studies, seven were included in this review and none were randomized controlled trials. In the seven studies, 114 localized dedifferentiated low-grade osteosarcoma patients were examined.

RESULTS

Mortality rates of the resection plus chemotherapy (R + C) and the resection only (Ronly) groups were 20.3% and 11.4%, respectively [overall pooled odds ratio, 1.59 (P = 0.662); heterogeneity I2, 0%]. The local recurrence or distant metastasis rate in the R + C group was 36.7% and that in the Ronly group was 28.6% [overall pooled odds ratio, 1.37 (P = 0.484); heterogeneity I2 was 0%].

CONCLUSIONS

Results show a limited efficacy of adjuvant chemotherapy for localized dedifferentiated low-grade osteosarcoma. However, because this was a systematic review of retrospective studies that examined a small number of patients, future randomized controlled trials are needed.

Translational insights and overall survival in the U31402-A-U102 study of patritumab deruxtecan (HER3-DXd) in EGFR-mutated NSCLC

BACKGROUND

Human epidermal growth factor receptor 3 (HER3) is broadly expressed in non-small-cell lung cancer (NSCLC) and is the target of patritumab deruxtecan (HER3-DXd), an antibody-drug conjugate consisting of a HER3 antibody attached to a topoisomerase I inhibitor payload via a tetrapeptide-based cleavable linker. U31402-A-U102 is an ongoing phase I study of HER3-DXd in patients with advanced NSCLC. Patients with epidermal growth factor receptor (EGFR)-mutated NSCLC that progressed after EGFR tyrosine kinase inhibitor (TKI) and platinum-based chemotherapy (PBC) who received HER3-DXd 5.6 mg/kg intravenously once every 3 weeks had a confirmed objective response rate (cORR) of 39%. We present median overall survival (OS) with extended follow-up in a larger population of patients with EGFR-mutated NSCLC and an exploratory analysis in those with acquired genomic alterations potentially associated with resistance to HER3-DXd.

PATIENTS AND METHODS

Safety was assessed in patients with EGFR-mutated NSCLC previously treated with EGFR TKI who received HER3-DXd 5.6 mg/kg; efficacy was assessed in those who also had prior PBC.

RESULTS

In the safety population (N = 102), median treatment duration was 5.5 (range 0.7-27.5) months. Grade ≥3 adverse events occurred in 76.5% of patients; the overall safety profile was consistent with previous reports. In 78/102 patients who had prior third-generation EGFR TKI and PBC, cORR by blinded independent central review (as per RECIST v1.1) was 41.0% [95% confidence interval (CI) 30.0% to 52.7%], median progression-free survival was 6.4 (95% CI 4.4-10.8) months, and median OS was 16.2 (95% CI 11.2-21.9) months. Patients had diverse mechanisms of EGFR TKI resistance at baseline. At tumor progression, acquired mutations in ERBB3 and TOP1 that might confer resistance to HER3-DXd were identified.

CONCLUSIONS

In patients with EGFR-mutated NSCLC after EGFR TKI and PBC, HER3-DXd treatment was associated with a clinically meaningful OS. The tumor biomarker characterization comprised the first description of potential mechanisms of resistance to HER3-DXd therapy.

Computational dielectric spectroscopy on solid-solution interface by time-dependent voltage applied molecular dynamics simulation

A frequency-dependent dielectric constant characterizes the dielectric response of a medium and also represents the time scale of system's collective dynamics. Although it is valuable not only academically but also practically for developing advanced devices, getting the value of a solution at the interface with a solid or electrode surface is challenging both experimentally and computationally. Here, we propose a computational method that imitates the dielectric spectroscopy and AC impedance measurement. It combines a time-dependent voltage applied molecular dynamics simulation with an equivalent circuit representation of a system composed of a solution confined between two identical electrodes. It gives the frequency-dependent dielectric constants of the bulk solution and the interface simultaneously. Unlike the conventional method, it does not require computation of a dipole autocorrelation function and its Fourier transformation. Application of the method on a system of water confined between polarizable Pt electrodes gives the static dielectric constant and the relaxation time of the bulk water in good agreement with previous simulation results and experimental values. In addition, it gives a much smaller static dielectric constant at the interface, consistent with previous observations. The outline of the dielectric dispersion curve of the interface seems similar to that of the bulk, but the relaxation time is several times faster.

Modeling Complex EEG Data Distribution on the Riemannian Manifold Toward Outlier Detection and Multimodal Classification

OBJECTIVE

The usage of Riemannian geometry for Brain-computer interfaces (BCIs) has gained momentum in recent years. Most of the machine learning techniques proposed for Riemannian BCIs consider the data distribution on a manifold to be unimodal. However, the distribution is likely to be multimodal rather than unimodal since high-data variability is a crucial limitation of electroencephalography (EEG). In this paper, we propose a novel data modeling method for considering complex data distributions on a Riemannian manifold of EEG covariance matrices, aiming to improve BCI reliability.

METHODS

Our method, Riemannian spectral clustering (RiSC), represents EEG covariance matrix distribution on a manifold using a graph with proposed similarity measurement based on geodesic distances, then clusters the graph nodes through spectral clustering. This allows flexibility to model both a unimodal and a multimodal distribution on a manifold. RiSC can be used as a basis to design an outlier detector named outlier detection Riemannian spectral clustering (odenRiSC) and a multimodal classifier named multimodal classifier Riemannian spectral clustering (mcRiSC). All required parameters of odenRiSC/mcRiSC are selected in data-driven manner. Moreover, there is no need to pre-set a threshold for outlier detection and the number of modes for multimodal classification.

RESULTS

The experimental evaluation revealed odenRiSC can detect EEG outliers more accurately than existing methods and mcRiSC outperformed the standard unimodal classifier, especially on high-variability datasets.

CONCLUSION

odenRiSC/mcRiSC are anticipated to contribute to making real-life BCIs outside labs and neuroergonomics applications more robust.

SIGNIFICANCE

RiSC can work as a robust EEG outlier detector and multimodal classifier.

Effect of baseline urinary glucose levels on the relationship between sodium-glucose cotransporter 2 inhibitors and serum uric acid in Japanese patients with type 2 diabetes mellitus

In patients with type 2 diabetes mellitus (T2DM), controlling serum uric acid (SUA) and blood glucose levels is important. Moreover, sodium-glucose cotransporter 2 (SGLT2) inhibitors decrease SUA levels by accelerating urinary uric acid excretion. We investigated the effect of baseline urinary glucose levels on the relationship between SGLT2 inhibitors and SUA levels. We conducted a retrospective observational study using the electronic medical records of patients with T2DM of Kindai University Nara Hospital (April 2013 to March 2022). We divided the patients into two groups according to their baseline urinary glucose levels: the N-UG group, which included patients with negative urinary glucose strip test results (-), and the P-UG group, which included patients with positive urinary glucose strip test results (± or more). The changes in SUA levels before and after SGLT2 inhibitor administration were investigated. For comparison, the changes in SUA levels before and after the prescription of antidiabetic agents, excluding SGLT2 inhibitors, were also investigated. Our results revealed that SGLT2 inhibitors significantly decreased the SUA levels in patients in the N-UG group but tended to decrease its levels in those in the P-UG group. Regardless of the urinary glucose status at baseline, the administration of SGLT2 inhibitors may be useful for patients with T2DM to prevent the complications of hyperuricemia.

Development of a novel delivery quality assurance system based on simultaneous verification of dose distribution and binary multi-leaf collimator opening in helical tomotherapy

BACKGROUND

Intensity-modulated radiation therapy (IMRT) requires delivery quality assurance (DQA) to ensure treatment accuracy and safety. Irradiation techniques such as helical tomotherapy (HT) have become increasingly complex, rendering conventional verification methods insufficient. This study aims to develop a novel DQA system to simultaneously verify dose distribution and multi-leaf collimator (MLC) opening during HT.

METHODS

We developed a prototype detector consisting of a cylindrical plastic scintillator (PS) and a cooled charge-coupled device (CCD) camera. Scintillation light was recorded using a CCD camera. A TomoHDA (Accuray Inc.) was used as the irradiation device. The characteristics of the developed system were evaluated based on the light intensity. The IMRT plan was irradiated onto the PS to record a moving image of the scintillation light. MLC opening and light distribution were obtained from the recorded images. To detect MLC opening, we placed a region of interest (ROI) on the image, corresponding to the leaf position, and analyzed the temporal change in the light intensity within each ROI. Corrections were made for light changes due to differences in the PS shape and irradiation position. The corrected light intensity was converted into the leaf opening time (LOT), and an MLC sinogram was constructed. The reconstructed MLC sinogram was compared with that calculated using the treatment planning system (TPS). Light distribution was obtained by integrating all frames obtained during IMRT irradiation. The light distribution was compared with the dose distribution calculated using the TPS.

RESULTS

The LOT and the light intensity followed a linear relationship. Owing to MLC movements, the sensitivity and specificity of the reconstructed sinogram exceeded 97%, with an LOT error of - 3.9 ± 7.8%. The light distribution pattern closely resembled that of the dose distribution. The average dose difference and the pass rate of gamma analysis with 3%/3 mm were 1.4 ± 0.2% and 99%, respectively.

CONCLUSION

We developed a DQA system for simultaneous and accurate verification of both dose distribution and MLC opening during HT.

Imaging phonon eigenstates and elucidating the energy storage characteristics of a honeycomb-lattice phononic crystal cavity

We extend gigahertz time-domain imaging to a wideband investigation of the eigenstates of a phononic crystal cavity. Using omnidirectionally excited phonon wave vectors, we implement an ultrafast technique to experimentally probe the two-dimensional acoustic field inside and outside a hexagonal cavity in a honeycomb-lattice phononic crystal formed in a microscopic crystalline silicon slab, thereby revealing the confinement and mode volumes of phonon eigenstates-some of which are clearly hexapole in character-lying both inside and outside the phononic-crystal band gap. This allows us to obtain a quantitative measure of the spatial acoustic energy storage characteristics of a phononic crystal cavity. We also introduce a numerical approach involving toneburst excitation and the monitoring of the acoustic energy decay together with the integral of the Poynting vector to calculate the Q factor of the principal in-gap eigenmode, showing it to be limited by ultrasonic attenuation rather than by phonon leakage to the surrounding region.

Dosimetric Predictors of Toxicity after Prostate Stereotactic Body Radiotherapy: A Single-Institutional Experience of 145 Patients

The indications for stereotactic body radiotherapy (SBRT) for prostate cancer have increased. However, the relationships between adverse events and risk factors remain unclear. This study aimed to clarify associations between adverse events and dose index for prostate SBRT. Participants comprised 145 patients irradiated with 32-36 Gy in 4 fractions. Radiotherapy-related risk factors such as dose-volume histogram parameters and patient-related risk factors such as T stage and Gleason score were evaluated in a competing risk analysis. Median follow-up duration was 42.9 months. A total of 9.7% had acute Grade ≥ 2 GU toxicities and 4.8% had acute Grade ≥ 2 GI toxicities. A total of 11.1% had late Grade ≥ 2 GU toxicities and 7.6% had late Grade ≥ 2 GI toxicities. Two (1.4%) patients suffered from late Grade 3 GU toxicities. Similarly, two (1.4%) patients suffered from late Grade 3 GI toxicities. Acute GU and GI events correlated with prostate volume and dose to the hottest 10 cc volume (D10cc)/volumes receiving a minimum of 30 Gy (V30 Gy) of rectum, respectively. Late GI toxicity, frequency, and rectal hemorrhage correlated with rectal D0.1 cc/D1 cc, maximum dose to the bladder, and rectal D0.1 cc, respectively. Toxicities after prostate SBRT using 32-36 Gy/4 fractions were acceptable. Our analysis showed that acute toxicities correlated with volume receiving a medium dose level, and late toxicities correlated with highest point dose of organs at risk.

Clinical outcomes of medical treatments for progressive desmoid tumors following active surveillance: a systematic review

Approximately 80% of desmoid tumors (DTs) show spontaneous regression or disease stabilization during first-line active surveillance. Medical treatment can be considered in cases of disease progression. This systematic review aimed to evaluate the effectiveness and toxicity of each medical treatment by reviewing only the studies that included progressive disease as the inclusion criterion. We searched the EMBASE, PubMed, and CENTRAL databases to identify published studies for progressive DTs. The disease control rates of the medical treatments, such as low-dose chemotherapy with methotrexate plus vinblastine or vinorelbine, imatinib, sorafenib, pazopanib, nilotinib, anlotinib, doxorubicin-based agents, liposomal doxorubicin, hydroxyurea, and oral vinorelbine for progressive DTs were 71-100%, 78-92%, 67-96%, 84%, 88%, 86%, 89-100%, 90-100%, 75%, and 64%, respectively. Low-dose chemotherapy, sorafenib, pazopanib, nilotinib, anlotinib, and liposomal doxorubicin had similar toxicities. Sorafenib and pazopanib were less toxic than imatinib. Doxorubicin-based chemotherapy was associated with the highest toxicity. Hydroxyurea and oral vinorelbine exhibited the lowest toxicity. Stepwise therapy escalation from an initial, less toxic treatment to more toxic agents is recommended for progressive DTs. Sorafenib and pazopanib had limited on-treatment side effects but had the possibility to induce long-term treatment-related side effects. In contrast, low-dose chemotherapy has some on-treatment side effects and is known to have very low long-term toxicity. Thus, for progressive DTs following active surveillance, low-dose chemotherapy is recommended in young patients as long-term side effects are minor, whereas therapies such as sorafenib and pazopanib is recommended for older patients as early side effects are minor.

Clinical characteristics and outcomes of pheochromocytoma crisis: a literature review of 200 cases

PURPOSE

Pheochromocytoma crisis is a life-threatening endocrine emergency that requires prompt diagnosis and treatment. Because of its rarity, sudden onset, and lack of internationally uniform and validated diagnostic criteria, pheochromocytoma crisis remains to be fully clarified. Therefore, we aimed to describe the clinical characteristics and outcomes of pheochromocytoma crisis through a literature review.

METHODS

We performed a systematic literature search of PubMed/MEDLINE database, Igaku-Chuo-Zasshi (Japanese database), and Google Scholar to identify case reports of pheochromocytoma crisis published until February 5, 2021. Information was extracted and analyzed from the literature that reported adequate individual patient data of pheochromocytoma crisis in English or Japanese. Cases were also termed as pheochromocytoma multisystem crisis (PMC) if patients had signs of hyperthermia, multiple organ failure, encephalopathy, and labile blood pressure.

RESULTS

In the 200 cases of pheochromocytoma crisis identified from 187 articles, the mean patient age was 43.8 ± 15.5 years. The most common symptom was headache (39.5%). The heart was the most commonly damaged organ resulting from a complication of a pheochromocytoma crisis (99.0%), followed by the lungs (44.0%) and the kidney (21.5%). PMC accounted for 19.0% of all pheochromocytoma crisis cases. After excluding 12 cases with unknown survival statuses, the mortality rate was 13.8% (26/188 cases). Multivariable logistic regression analysis revealed that nausea and vomiting were significantly associated with a higher mortality rate.

CONCLUSION

Pheochromocytoma can present with different symptomatology, affecting different organ systems. Clinicians should be aware that patients with nausea or vomiting are at a higher risk of death because of pheochromocytoma crisis.

Anaesthetic management of an abdominal aortic aneurysmorrhaphy in Klippel-Trenaunay-Weber syndrome: a case report

Background

Klippel-Trenaunay-Weber syndrome (KTWS) is a rare congenital malformation. Although there have been few reports on anaesthetic management of patients with KTWS, there is a lack of data on anaesthetic management for abdominal aortic aneurysm (AAA) surgeries in these patients.

Case presentation

A 74-year-old man (height, 160 cm and body weight, 51.5 kg) with KTWS was scheduled for AAA replacement. Abdominal computed tomography (CT) showed prominent tortuosity below the abdominal aorta with an infrarenal abdominal aortic aneurysm, right common iliac artery aneurysm, and right external iliac artery aneurysm. Moreover, a remarkably noted arteriovenous fistula had developed between the aneurysm and peripheral artery. General anaesthesia was induced. Furthermore, a central venous catheter and an 8.5 French sheath in the left internal jugular vein were inserted. During the operation, bleeding from a collateral vessel in the cross-clamped aorta led the surgeon to decide to perform aneurysmorrhaphy. Intraoperatively, blood loss was 1500 ml, and 20 units of red blood cell concentrate were used.

Conclusions

Regarding AAA procedures in patients with KTWS, aortic cross-clamping may not sufficiently intercept blood flow due to collateral vessels. In these patients, the anaesthesiologist must be prepared to transfuse blood more rapidly and frequently than during normal AAA procedures.

Optimization of a Stacked-design Core-body-temperature Sensor for Long-period Human Trials

We fabricated a wearable sensor that can be attached to the skin surface and continuously measure core body temperature (CBT) wirelessly over a long period. CBT is calculated from skin-surface temperature and heat flux passing through the sensor. Since heat flux is lost to the surroundings of the probe, the slightest change in convection in daily life will degrade the measurement accuracy of the sensor. Accordingly, we previously proposed a heat-flux-path control structure to reduce the absolute amount of heat-flux loss. To make wearable sensors for long-term human trials, we proposed an integrated design in which a sensor probe, a circuit board, and a battery are stacked. We optimized the proposed design by computer simulation and evaluated the fabricated sensor by a phantom experiment in which the convectional state was changed. The evaluation results demonstrate that the sensor has limits of agreement (LOA) of [-0.13; 0.03]°C under 1-m/s-wind convection. Moreover, a preliminary human trial conducted under daily-life conditions (including convectional changes) demonstrated that the sensor has LOA of [-0.18; 0.22]°C. These results demonstrate that the fabricated sensor is suitable for CBT measurement.

P-603 Presence of an asymmetrical response to ovarian stimulation in patients with low ovarian reserve

Study question

Does ovarian reserve decline with a symmetrical manner between right and left ovaries in poor responders (POR) with diminished ovarian reserve (DOR)?

Summary answer

Asymmetrical ovarian response to ovarian stimulation with the left-side dominance was found in POR with DOR.

What is known already

Ovarian follicles are produced during fetal stage and not regenerated after birth. Thus, the number of ovarian follicles declines with age, resulting in infertile POR with DOR. In the morphometric study of human neonatal ovaries, no significant difference was found in the number of follicles between the right and left ovaries in the same individual. A previous study demonstrated that there is a difference in the number of follicles between right and left ovaries in patients with normal ovarian reserve with the right-side dominance, suggesting the asymmetrical activation and growth of follicles.

Study design, size, duration

A retrospective analysis was conducted in patients with POR with DOR based on the Bologna Criteria. Inclusion criteria was patients who received more than five times of ovarian stimulations followed by oocyte retrievals. Data were obtained from a total of 265 participants who received IVF-ET treatments from April 2015 to March 2021 after receiving written informed consents under an approval from the institutional ethical committee. Patients with the history of previous ovarian surgery were excluded.

Participants/materials, setting, methods

The enrolled patients were received ovarian simulation under short or GnRH antagonist protocols for oocyte retrieval. We collected the data of retrieved oocyte number as well as the outcome of IVF from medical chart. We defined the right-left asymmetry of ovarian reserve (%) based on the number of retrieved oocytes from dominant side ovary per total number of retrieved oocytes. Statistical significance was determined using Dunnett or chi-square tests, with P < 0.05 being statistically significant.

Main results and the role of chance

The average age of participants was 37.2±5.99 years of age exhibiting low serum AMH levels (average 0.09±0.20 ng/ml). We analyzed 2,181 cycles of ovarian stimulation (average 8.3±3.9 cycles/patient). The number of retrieved oocytes were 3, 882 in total cycles (average 12.8±7.1/patient). Among participants, 22 cases (8.4%) showed left and right equal in the number of retrieved oocytes, whereas >70% asymmetry was observed in 107 cases (40.7%) and >80% asymmetry was detected in 60 cases (22.8%). In 18 cases (6.9%), oocytes were collected from one side ovary only showing 100% asymmetry. In the cases with >70 and 100% asymmetry, the left-side dominance was 1.3-fold and 5.0-fold higher than right-side dominance, respectively. In cases with 100% asymmetry, there was no difference in the number of cryopreserved high-quality embryos between left and right sides of ovary.

Limitations, reasons for caution

Although we enrolled POR with DOR patients who received ovarian stimulations more than five times, the duration of ovarian stimulation was different among patients. It affects the numbers of ovarian stimulation cycles and retrieved oocytes in each patient.

Wider implications of the findings

Considering the finding of right-side dominance in the number of follicles with normal ovarian reserve, the activation and development of follicles might be accelerated in the right side due to asymmetric blood supply to the ovaries, and thus follicles are likely remained in the left-side ovary with low ovarian reserve.

Trial registration number

not applicable

LB0001 BIMEKIZUMAB IN BDMARD-NAIVE PATIENTS WITH PSORIATIC ARTHRITIS: 24-WEEK EFFICACY & SAFETY FROM BE OPTIMAL, A PHASE 3, MULTICENTRE, RANDOMISED, PLACEBO-CONTROLLED, ACTIVE REFERENCE STUDY

Background

Bimekizumab (BKZ) is a monoclonal IgG1 antibody that selectively inhibits IL-17F in addition to IL-17A.

Objectives

Assess BKZ efficacy and safety vs PBO in bDMARD-naïve pts with active PsA to Wk 24 of BE OPTIMAL.

Methods

BE OPTIMAL (NCT03895203) comprises 16 wks double-blind PBO-controlled and 36 wks treatment-blind. Pts were ≥18 yrs, bDMARD-naïve, with adult-onset, active PsA, ≥3 tender and ≥3 swollen joints. Pts randomised 3:2:1, subcutaneous BKZ 160 mg Q4W:PBO:adalimumab (ADA; reference arm) 40 mg Q2W. From Wk 16, PBO pts received BKZ 160 mg Q4W. Primary endpoint: ACR50 at Wk 16.

Results

821/852 (96.4%) pts completed Wk 16 and 806 (94.6%) Wk 24. Mean age 48.7 yrs, BMI 29.2 kg/m2; since diagnosis: 5.9 yrs; 46.8% male. BL characteristics comparable across arms. Primary endpoint met (Wk 16 ACR50: 43.9% BKZ vs 10.0% PBO, p<0.001; ADA: 45.7%; Figure 1). All ranked secondary endpoints met at Wk 16 (Table 1). As early as Wk 2, ACR20 was higher in BKZ vs PBO (27.1% vs 7.8%, nominal p<0.001; ADA: 33.6%). Outcomes continued to improve at Wk 24 (Table 1). To Wk 16, pts with ≥1 TEAE, BKZ: 59.9%; PBO: 49.5%; ADA: 59.3%. SAE rate low (1.6%; 1.1%; 1.4%). Most frequent (≥5%) AEs for all arms: nasopharyngitis (9.3%; 4.6%; 5.0%), URTI (4.9%; 6.4%; 2.1%), increased ALT (0.7%; 0.7%; 5.0%). Candida infections: 2.6%, 0.7%, 0%; no systemic candidiasis. 2 malignancies (BKZ: basal cell carcinoma; PBO: breast cancer stage 1); no MACE, uveitis, IBD or deaths.

Table 1.

Wk 16 and 24 efficacy

BLWk 16Wk 24PBO N=281BKZ 160 mg Q4W N=431ADA 40 mg Q2W N=140†PBO N=281BKZ 160 mg Q4W N=431ADA 40 mg Q2W N=140†p value (BKZ vs PBO)PBO→ BKZ 160 mg Q4WaN=281BKZ 160 mg Q4W N=431ADA 40 mg Q2W N=140†Ranked endpointsbACR50 [NRI],–––28189 (43.9)64<0.00110119666n (%)-10-45.7(35.9)(45.5)-47.1HAQ-DI CfB [MI],0.890.820.86−0.09 (0.03)−0.26 (0.02)−0.33<0.001c−0.28−0.30−0.34mean (SE)-0.04-0.03-0.05(0.04)(0.03)(0.02)(0.05)PASI90d [NRI],–––4133 (61.3)f28<0.00186 (61.4)e158 (72.8)f32n (%)(2.9)e(41.2)g(47.1)gSF-36 PCS CfB [MI],36.938.137.62.36.36.8<0.001c6.27.37.3mean (SE)-0.6-0.5-0.7-0.5-0.4-0.8-0.5-0.4-0.8MDA [NRI],51413719463<0.00110620967n (%)-1.8-3.2-0.7-13.2(45.0)-45(37.7)(48.5)-47.9vdHmTSS CfB (subgroup)h [MI], mean (SE)15.67 (1.80)i15.56 (1.69)j17.39 (2.89)k0.36 (0.10)i−0.01 (0.04)j−0.06 (0.08)k<0.001c–––vdHmTSS CfB [MI],mean (SE)13.31 (1.56)l13.44 (1.47)m14.55 (2.44)n0.31 (0.09)l0(0.04)m−0.03 (0.07)n0.001c–––Other endpointsACR20 [NRI],–––6726896<0.001o17528299n (%)-23.8(62.2)-68.6(62.3)(65.4)-70.7ACR70 [NRI],–––1210539<0.001o5312642n (%)-4.3(24.4)-27.9-18.9(29.2)-30PASI100d [NRI],–––3103f14<0.001o6012226n (%)(2.1)e(47.5)(20.6)g(42.9)e (56.2)f(38.2)gTJC CfB [MI],17.116.817.5−3.2−10.0−10.9<0.001o−9.4−11.5−11.8mean (SE)-0.7-0.6-1.1(0.7) (0.5)-1(0.7)(0.5)-0.9SJC CfB [MI],9.599.6−3.0 (0.5)−6.6 (0.3)−7.5<0.001o−6.8 (0.4)−7.2 (0.3)−7.9mean (SE)-0.4-0.3-0.6-0.6-0.6

Randomised set. Interim results.

†Reference arm; study not powered for statistical comparisons of ADA to BKZ or PBO.

aPBO→BKZ pts received PBO to Wk 16, switched to BKZ 160 mg Q4W through Wk 24 (8 wks BKZ);

bResolution of enthesitis/dactylitis in pts with LEI>0/LDI>0 at BL pooled with BE COMPLETE (Wk 16 LEI=0 BKZ: 124/249 [49.8%], PBO: 37/106 [34.9%], p=0.008; LDI=0 BKZ: 68/90 [75.6%], PBO: 24/47 [51.1%], p=0.002);

cContinuous outcome p values calculated with RBMI data;

dPts with PSO and ≥3% BSA at BL;

en=140;

fn=217;

gn=68;

hPts with hs-CRP ≥6 mg/L and/or bone erosion at BL;

in=221;

jn=357;

kn=108;

ln=261;

mn=416;

nn=131;

oNominal, not powered for multiplicity.

Conclusion

Dual inhibition of IL-17A and IL-17F with BKZ in bDMARD-naïve pts with active PsA resulted in rapid, clinically relevant improvements in musculoskeletal and skin outcomes vs PBO. No new safety signals observed.1,2

References

[1]Ritchlin CT Lancet 2020;395(10222):427–40; 2. Coates LC Ann Rheum Dis 2021;80:779–80(POS1022).

Disclosure of Interests

Iain McInnes Consultant of: AbbVie, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, Novartis, and UCB Pharma, Grant/research support from: BMS, Boehringer Ingelheim, Celgene, Janssen, UCB Pharma, Laura Coates Consultant of: AbbVie, Amgen, Boehringer Ingelheim, BMS, Celgene, Domain, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer, and UCB Pharma, Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Robert B.M. Landewé Consultant of: Abbott, Ablynx, Amgen, AstraZeneca, BMS, Centocor, GSK, Novartis, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Speakers bureau: Abbott, Amgen, BMS, Centocor, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Grant/research support from: Abbott, Amgen, Centocor, Novartis, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Philip J Mease Consultant of: AbbVie, Amgen, BMS, Boehringer Ingelheim, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: AbbVie, Amgen, BMS, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Christopher T. Ritchlin Consultant of: AbbVie, Amgen, Eli Lilly, Gilead, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: AbbVie, Amgen and UCB Pharma, Yoshiya Tanaka Consultant of: AbbVie, Ayumi, Daiichi-Sankyo, Eli Lilly, GSK, Sanofi, and Taisho, Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer-Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Akihiko Asahina Grant/research support from: AbbVie, Amgen, Eisai, Eli Lilly, Janssen, Kyowa Kirin, LEO Pharma, Maruho, Mitsubishi Tanabe Pharma, Pfizer, Sun Pharma, Taiho Pharma, Torii Pharmaceutical, and UCB Pharma, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Celltrion, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer and UCB Pharma, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, Sandoz and UCB Pharma, Alice B Gottlieb Consultant of: Amgen, AnaptsysBio, Avotres Therapeutics, Boehringer Ingelheim, BMS, Dermavant, Eli Lilly, Incyte, Janssen, Novartis, Pfizer, Sanofi, Sun Pharma, UCB Pharma, and XBiotech, Grant/research support from: Boehringer Ingelheim, Janssen, Novartis, Sun Pharma, UCB Pharma, and XBiotech: all funds go to Mount Sinai Medical School, Richard B. Warren Consultant of: AbbVie, Almirall, Amgen, Arena, Astellas, Avillion, Biogen, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, GSK, Janssen, LEO Pharma, Novartis, Pfizer, Sanofi, and UCB Pharma, Paid instructor for: Astellas, DiCE, GSK, and Union, Grant/research support from: AbbVie, Almirall, Janssen, LEO Pharma, Novartis, and UCB Pharma, Barbara Ink Shareholder of: GSK, UCB Pharma, Employee of: UCB Pharma, Deepak Assudani Shareholder of: UCB Pharma, Employee of: UCB Pharma, Jason Coarse Shareholder of: UCB Pharma, Employee of: UCB Pharma, Rajan Bajracharya Shareholder of: UCB Pharma, Employee of: UCB Pharma, Joseph F. Merola Consultant of: AbbVie, Amgen, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma, and UCB Pharma, Paid instructor for: Amgen, Abbvie, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma, and UCB Pharma

POS0734 THE CLINICAL JUDGMENT FOR THE ACCEPTABILITY OF PREGNANCY IN PATIENTS WITH SEROLOGICALLY ACTIVE SLE IN JAPAN: A NATIONWIDE ONLINE SURVEY FROM THE VIGNETTE STUDY

Background

The risk of pregnancy complications, such as gestational hypertension is high in pregnancies with SLE. In addition, the risk of flare is elevated if pregnancy occurs during the high disease activity. The EULAR recommendation provides a checklist for preconception counseling, in which patients with SLE desiring pregnancy were required the condition that the disease activity prior to pregnancy should be stable for 6-12 months in terms of serological activity (1). However, it does not provide specific criteria for serological activity so that physicians should evaluate the risk of pregnancy in each case by their clinical intuitions.

Objectives

In order to uncover the present clinical situation for the acceptability of pregnancy in patients with SLE, we performed questionnaire survey to physicians regarding to the degree of serological activity.

Methods

This cross-sectional study was performed to physicians registered with the Japanese College of Rheumatology from December 2020 to January 2021 using the online survey. The questionnaire asked about the characteristics of physicians, facilities and the permission of pregnancies with SLE using vignette scenarios. In this study, data from vignettes of women visiting a regular outpatient clinic were used. The vignettes varied in age (28 or 35 years), duration of stable disease and serological activity. Analysis methods were descriptive statistics, chi-square test. generalized estimating equations (GEE) was performed to investigate the relationship between the determining permission for pregnancy and the scenario patient’s characteristics (age, period of stable disease, titer of anti ds-DNA antibody)

Results

The questionnaire was distributed to 4946 physicians, and 463 responded. Completion rate (ratio agreed to participate/finished survey) of survey was 91.1%. The median age of physicians was 46 (interquartile range (IQR) 2-10). The specialty was rheumatology (84.9%), other internal medicine (8%), and pediatrics (5.6%). There were no significant differences in patient’s age about the acceptability of pregnancy (coeffficianet -0.02, 95% CI -0.17 -0.01, p=0.42). Case who had been stable for 6 months were more tolerant of pregnancy than case who had been stable for 3 months (coeffficianet 0.12, 95% CI 0.09-0.15, P<0.001) Pregnancy was not allowed in case with mild or high serological activity (mild: coefficient -0.49, 95% CI -0.29- -0.22, p <0.001, high: -0.64, 95% CI -0.65 - -0.61, p <0.001). In contrast, as many as 92 (19.2%) physicians tolerated pregnancy even in the presence of residual high anti ds-DNA antibody titers. Female physicians are significantly more cautious about pregnancy than male when patients have a serologically high activity (12% vs 37.5%, p<0.001). There were no significant differences in specialty status or clinical experience.

Conclusion

We found that even mild serological activity alone had a significant negative effect on the physician’s decision to allow pregnancy. We conclude that current physicians make cautious decisions about pregnancies of patients with SLE following the recommendation. On the other hand, an additional investigation should be performed about the results of pregnancies in patients with serological abnormalities, since there are some physicians who thought that pregnancy may be acceptable for patients with only serological abnormalities if the clinical symptoms are stable.

References

[1]Ann Rheum Dis．2017 Mar;76(3):476-485

Acknowledgements

I would like to express my gratitude to the members of Japan College of Rheumatology who cooperated in filling out the questionnaire.

Disclosure of Interests

Sakiko Isojima: None declared, Nobuyuki Yajima: None declared, Ryo Yanai: None declared, Yoko Miura: None declared, Shingo Fukuma: None declared, Kayoko Kaneko: None declared, Keishi Fujio: None declared, Kenji Oku: None declared, Masakazu Matsushita: None declared, Takako Miyamae: None declared, Takashi Wada: None declared, Yuko Kaneko: None declared, Yoshiya Tanaka Speakers bureau: Y. Tanaka has received speaking fees and/or honoraria from Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Grant/research support from: Y. Tanaka has received research grants from Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, and consultant fee from Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie., Ayako Nakajima: None declared, ATSUKO MURASHIMA: None declared

POS0676 EFFICACY AND SAFETY OF FILGOTINIB IN PATIENTS AGED ≥75 YEARS: A POST HOC SUBGROUP ANALYSIS OF THE FINCH 4 LONG-TERM EXTENSION (LTE) STUDY

Background

Filgotinib (FIL) is a Janus kinase 1 preferential inhibitor for the treatment of moderate to severe rheumatoid arthritis (RA)1. The recommended dose for adults with RA is 200 mg (FIL200); however, a starting dose of 100 mg (FIL100) is recommended for those aged ≥75 years (y) in view of limited clinical experience1. An important consideration is the generally higher incidence of adverse events (AEs) in the elderly due to comorbidities.

Objectives

To evaluate the efficacy and safety of FIL100 and FIL200 in patients with RA aged ≥75 y.

Methods

FINCH 4 (NCT03025308) is an ongoing phase 3 open-label LTE study of FIL100 and FIL200 for RA. Eligible patients completed a prior phase 3 randomized double-blind study of FIL lasting 52 weeks (FINCH 1 or 3) or 24 weeks (FINCH 2). In this post hoc analysis, safety and efficacy were assessed in patients aged <75 and ≥75 y in FINCH 4. Efficacy measures were American College of Rheumatology (ACR)20/50/70 responses, clinical disease activity index (CDAI) ≤10/≤2.8, disease activity score (DAS)28 <2.6/≤3.2 and health assessment questionnaire-disability index (HAQ-DI).

Results

At LTE Week 48, 52% and 44% of patients aged <75 and ≥75 y, respectively, were on methotrexate. In both age groups, response rates for key efficacy measures at LTE Week 48 were generally maintained from LTE baseline (Figure 1) in patients with and without prior FIL exposure in FINCH 1–3, and were numerically higher with FIL200 vs FIL100. Mean change from baseline in HAQ-DI with FIL200 and FIL100 was 0.61 and 0.74 in those aged <75 y and 1.04 and 0.98 in those aged ≥75 y, respectively.

Figure 1.

The exposure-adjusted incidence rate (EAIR) of serious AEs and AEs of special interest (AESI) was generally higher in patients aged ≥75 y than <75 y. In those aged ≥75 y, the EAIR of AEs leading to premature study discontinuation, treatment-emergent AEs (TEAEs), and serious TEAEs was higher with FIL200 vs FIL100; the incidence of major adverse cardiovascular events, venous thrombotic and embolic events, serious infections, herpes zoster and malignancies was low in both dose groups (Table 1). Three patients died, all from the FIL200 group; each had a medical history relevant to the cause of death.

Table 1.

Exposure-adjusted incidence rate (95% CI) of AEs at Week 48 as events per 100 years of exposure

FIL200FIL100Age, years<75≥75<75≥75n=1469n=61n=1136n=63(PYE 2253.9)(PYE 92.2)(PYE 1753.7)(PYE 98.4)With prior FIL exposure, n (%)1142 (77.7)53 (86.9)830 (73.1)33 (52.4)TEAE48.3 (45.5, 51.3)55.3 (42.1, 72.8)48.7 (45.5, 52.1)42.7 (31.6, 57.8)Serious TEAE6.8 (5.8, 8.0)17.4 (10.6, 28.3)7.4 (6.2, 8.7)14.2 (8.4, 24.0)AE leading to premature study discontinuation2.9 (2.3, 3.7)9.8 (5.1, 18.8)3.9 (3.1, 5.0)4.1 (1.5, 10.8)AE leading to death0.5 (0.3, 0.9)3.3 (0.7, 9.5)*0.3 (0.2, 0.8)0.0 (0.0, 3.8)Infections28.8 (26.6, 31.1)29.3 (20.1, 42.7)27.4 (25.0, 29.9)26.4 (18.0, 38.8)Serious infections1.6 (1.2, 2.2)2.2 (0.5, 8.7)1.7 (1.1, 2.4)3.1 (1.0, 9.5)Herpes zoster1.6 (1.2, 2.3)2.2 (0.5, 8.7)1.0 (0.6, 1.6)3.1 (1.0, 9.5)Adjudicated major adverse cardiovascular event0.4 (0.2, 0.7)2.2 (0.5, 8.7)0.5 (0.2, 0.9)1.0 (0.1, 7.2)Venous thrombotic and embolic events0.3 (0.1, 0.6)2.2 (0.5, 8.7)0.2 (0.1, 0.5)1.0 (0.1, 7.2)Malignancy excluding NMSC0.7 (0.4, 1.2)4.3 (1.6, 11.6)0.7 (0.4, 1.2)3.1 (1.0, 9.5)NMSC0.4 (0.2, 0.8)1.1 (0.0, 6.0)0.2 (0.1, 0.6)0.0 (0.0, 3.8)

*Cause of death: esophageal carcinoma; cardiovascular; unknown. FIL(100/200), filgotinib (100/200 mg); NMSC, nonmelanoma skin cancer; PYE, patient years of exposure; (TE)AE, (treatment-emergent) adverse event

Conclusion

In the ≥75 y group, response rates for key efficacy measures remained stable to Week 48 and were generally higher with FIL200 vs FIL100. The incidence of serious AEs and AESI was higher in those aged ≥75 than <75 y. Patient numbers/exposure time may have been insufficient to show potential between-group differences in safety/efficacy outcomes.

References

[1]Filgotinib SmPC

Acknowledgements

The FINCH studies were funded by Gilead Sciences (Foster City, CA, United States). We thank the physicians and patients who participated in the studies. Medical writing support was provided by Debbie Sherwood, BSc (Aspire Scientific Ltd, Bollington, UK) and funded by Galapagos NV (Mechelen, Belgium).

Disclosure of Interests

Daniel Aletaha Speakers bureau: AbbVie, Amgen, Lilly, Janssen, Merck, Novartis, Pfizer, Roche, and Sandoz, Consultant of: AbbVie, Amgen, Lilly, Janssen, Merck, Novartis, Pfizer, Roche, and Sandoz, Grant/research support from: AbbVie, Amgen, Lilly, Novartis, Roche, SoBi, and Sanofi, Rene Westhovens Speakers bureau: Celltrion, Galapagos, and Gilead, Consultant of: Celltrion, Galapagos, and Gilead, Bernard Combe Speakers bureau: AbbVie, BMS, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, MSD, Novartis, Pfizer, and Roche-Chugai, Consultant of: AbbVie, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, and Roche-Chugai, Jacques-Eric Gottenberg Consultant of: AbbVie, BMS, Galapagos, Gilead, Lilly, and Pfizer, Grant/research support from: BMS and Pfizer, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Galapagos, Gilead, and Pfizer, Grant/research support from: Gilead and Pfizer, Roberto Caporali Speakers bureau: AbbVie, Amgen, BMS, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sandoz, and UCB, Consultant of: AbbVie, Amgen, BMS, Celltrion, Fresenius-Kabi, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Sandoz, and UCB, José A Gómez-Puerta Speakers bureau: AbbVie, BMS, Galapagos, GSK, Lilly, MSD, Novartis, Pfizer, Roche, and Sanofi, Consultant of: GSK, Roche, and Sanofi, Paul Van Hoek Employee of: Galapagos, Vijay Rajendran Employee of: Galapagos, Pieter-Jan Stiers Shareholder of: Galapagos, Employee of: Galapagos, Thijs Hendrikx Employee of: Galapagos, Gerd Rüdiger Burmester Consultant of: AbbVie, Amgen, BMS, Galapagos, Lilly, MSD, Pfizer, Roche, and Sanofi, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, Astra-Zeneca, Boehringer-Ingelheim, BMS, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Consultant of: AbbVie, Ayumi, Daiichi-Sankyo, Eli Lilly, GSK, Sanofi, and Taisho, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda

POS1014 IMPACT OF SERUM INTERLEUKIN 22 AS A BIOMARKER FOR THE DIFFERENTIAL USE OF MOLECULAR TARGETED DRUGS FOR PSORIATIC ARTHRITIS

Background

Although each bDMARD target different molecules, no optimal drug selection method has been established. Because studies directly comparing TNF-i and IL-17-i have shown that these drugs are equally effective, the establishment of an optimal selection method for these drugs can contribute to better patient outcomes. We reported the possibility of stratification of patients by peripheral blood lymphocytes phenotyping and precision medicine based on the selective use of bDMARDs in psoriatic arthritis (PsA). However, since peripheral blood lymphocytes phenotyping is complex, the development of simple methods using biomarkers to stratify patients and simple treatment strategies based on such methods is needed to promote precision medicine in a real-world clinical setting.

Objectives

We explored whether serum cytokines could be used as biomarkers for optimal use TNF-i and IL-17-i in patients with PsA.

Methods

In cohort 1 (IL-17-i [n=23] or TNF-i [n=24] for ≥1 year), we identified serum cytokines that predicted the achievement of DAPSA remission (REM), PASI 90 and Minimal Disease Activity after 1 year of TNF-i or IL-17-i therapy. Subsequently, we developed treatment strategies based on the identified cytokines. In cohort 2, treatment responses were compared between the strategic treatment group (n=17), which was treated based on the treatment strategies, and the mismatched treatment group (n=17) to verify the validity of the treatment strategies developed using serum cytokines as biomarkers.

Results

In cohort 1, serum IL-22 concentrations were statistically identified as a predictor of DAPSA remission after 1 year of IL-17-i therapy. However, no baseline serum cytokines were identified as factors contributing to achievement of DAPSA-REM in the TNF-i-treated group or achievement of PASI90 and Minimal Disease Activity in either group. Using a cut-off value of 0.61376 (sensitivity, 81.8%; specificity, 91.7%; area under the curve, 0.848) determined by a ROC analysis, we stratified 47 patients into the IL-22 high group (n=25) (0.61376<) and the IL-22 low group (n=22) (< 0.61376). Serum IL-17 concentrations were significantly higher in both the IL-22 high and IL-22 low groups than in the healthy control (HC), whereas no significant difference was observed between the IL-22 high and IL-22 low groups. The serum TNF-α concentrations did not significantly differ between the IL-22 low and HC; however, they were significantly higher in the IL-22 high group than in the HC and IL-22 low groups. Based on these results, we created treatment strategies using TNF-i and IL-17-i based on serum IL-22 concentrations, that is, initiation of IL-17-i therapy in patients with low IL-22 concentrations and TNF-i therapy in patients with high IL-22 concentrations. To validate the efficacy of the treatment strategies, we retrospectively compared the efficacy of the bDMARDs at 1 year between the following groups in cohort 2. The strategic treatment group (n=17) included patients with low IL-22 concentrations who were treated with IL-17-i and those with high IL-22 concentrations who were treated with TNF-i. The mismatched treatment group (n=17) included patients with low IL-22 concentrations who were treated with TNF-i and those with high IL-22 concentrations who were treated with IL-17-i. No statistically significant differences were observed between the two groups in baseline characteristics at the initiation of bDMARD. After initiation of bDMARD, tender joint counts, swollen joint counts, CRP, DAPSA, and PASI were significantly improved in both groups. When the treatment responses over 1 year were compared between the two groups, the rate of achieving DAPSA-REM (58.8% vs. 25.3%, P=0.0399) and Minimal Disease Activity (82.3% vs. 41.2%, P=0.0162) at M12 was significantly higher in the strategic treatment group. There were no statistically significant differences in the rates of achieving PASI75 or PASI90 at M 6 or 12.

Conclusion

We verified that serum IL-22 can be used as a simple biomarker for the proper selection of TNF-i and IL-17-i.

Acknowledgements

The authors thank the study participants, without whom this study could not have been

accomplished, and all medical staff at all participating institutions for providing the data,

especially Ms. Hiroko Yoshida, Ms. Youko Saitou, Ms. Machiko Mitsuiki and Ms. Ayumi

Maruyama for the excellent data management. The authors thank Ms. M.

Hirahara for providing excellent technical assistance. We also thank Dr Kazuyoshi Saito at

Tobata General Hospital; Dr Kentaro Hanami and Dr Shunsuke Fukuyo at Wakamatsu Hospital

of the University of Occupational and Environmental Health; Dr Keisuke Nakatsuka at Fukuoka

Yutaka Hospital, and all staff members at Kitakyushu General Hospital and Shimonoseki

Saiseikai Hospital. Nakama Municipal Hospital, and Steel Memorial Yawata Hospital for their

engagement in data collection.

Disclosure of Interests

Ippei Miyagawa: None declared, Shingo Nakayamada Speakers bureau: consulting fees, speaking fees, and/or honoraria from Bristol-Myers, Pfizer, GlaxoSmithKline, Sanofi, Astellas, Asahi-kasei, and Boehringer Ingelheim and research grants from Mitsubishi-Tanabe and Novartis., Masanobu Ueno: None declared, Yusuke Miyazaki: None declared, Yoshiya Tanaka Speakers bureau: speaking fees and/or honoraria from Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, and Janssen, Consultant of: consultant fees from Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, and Abbvie., Grant/research support from: research grants from Abbvie, Mitsubishi-Tanabe, Chugai, Asahi-Kasei, Eisai, Takeda, and Daiichi-Sankyo

POS0579 ABSENCE OF ASSOCIATION BETWEEN ABATACEPT EXPOSURE LEVELS AND INITIAL INFECTION IN PATIENTS WITH RA: A POST HOC ANALYSIS OF THE RANDOMIZED, PLACEBO-CONTROLLED AVERT-2 STUDY

Background

Infections are the most commonly reported AE observed in patients with RA treated with immunosuppressive therapies and can be clinically significant. A recent review reported differences in the risk of infection for some biologics such as tocilizumab and TNF inhibitors.1 Abatacept selectively modulates T-cell co-stimulation and is approved for the treatment of RA. In patients with polyarticular-course juvenile idiopathic arthritis, no association was found between higher serum abatacept exposure and the incidence of infection.2 This has not been evaluated for adult patients with RA.

Objectives

To determine if higher serum abatacept exposure during treatment with SC abatacept was associated with increased risk of infection in adult patients with RA.

Methods

AVERT-2 (Assessing Very Early Rheumatoid arthritis Treatment-2) was a randomized, placebo-controlled study of SC abatacept + MTX vs abatacept placebo + MTX in MTX-naive, anti-citrullinated protein antibody–positive patients with early, active RA.3 A post hoc population pharmacokinetic (PK) analysis was performed using PK-evaluable patient data from the induction period (year 1) of AVERT-2. Association between steady-state abatacept exposure (min plasma concentration [Cmin], max plasma concentration [Cmax], and average plasma concentration [Cavg]) and first infection was evaluated using Kaplan–Meier plots of probability vs time on treatment by abatacept exposure quartiles and Cox proportional-hazards models.

Results

PK of SC abatacept was defined as a linear 2-compartment model with first-order absorption and first-order elimination. The findings of the updated PK analysis were consistent with those reported in prior population analyses of abatacept PK in adults with RA. The final model included effects of baseline body weight, estimated glomerular filtration rate, sex, age, albumin, MTX use, NSAID use, SJC, and race on abatacept clearance. The only covariate with a clinically relevant effect was higher body weight, which caused an increase in clearance and volume. Infections occurred in a total of 330/693 (47.6%; serious, 1.6%) patients treated with abatacept, and 134/301 (44.5%; serious, 1.3%) with placebo during the first year of AVERT-2. In patients taking abatacept, the mean (SD) study exposure to abatacept was 376 (60) days, while mean (SD) prednisone equivalent dose was 6.7 (3.8) mg/day and mean (SD) MTX dose was 9.6 (3.0) mg/week. No exposure–response relationship was observed between the probability of first infection and steady-state abatacept exposure quartiles (Cavg, Cmin, and Cmax), or compared with placebo (Figure 1A–C). Kaplan–Meier assessment also showed no increase in risk of infection with concomitant use of MTX and glucocorticoids.

Conclusion

No association was found between initial infection and steady-state abatacept exposure (Cavg, Cmin, Cmax) or MTX and glucocorticoid use in patients with RA treated with SC abatacept.

References

[1]Jani M, et al. Curr Opin Rheumatol 2019;31:285–92.

[2]Ruperto N, et al. J Rheumatol 2021;48:1073–81.

[3]Emery P, et al. Arthritis Rheumatol 2019;71(suppl 10):L11.

Acknowledgements

This study was sponsored by Bristol Myers Squibb. Writing and editorial assistance were provided by Fiona Boswell, PhD, of Caudex, and was funded by Bristol Myers Squibb. Support was provided by Sandra Overfield as Protocol Manager, and Prema Sukumar and Renfang Hwang as Data Science Leads.

Disclosure of Interests

Paul Emery Consultant of: AbbVie, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Samsung, Grant/research support from: AbbVie, Bristol Myers Squibb, Eli Lilly, Novartis, Pfizer, Roche, Samsung, Roy Fleischmann Consultant of: Amgen, AbbVie, Bristol Myers Squibb, Gilead, GlaxoSmithKline, Novartis, Pfizer, Grant/research support from: Amgen, AbbVie, Arthrosi, Biosplice, Bristol Myers Squibb, Gilead, GlaxoSmithKline, Horizon, Novartis, Pfizer, Regeneron, TEVA, UCB, Robert Wong Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi Tanabe, YL Biologics, Consultant of: AbbVie, Ayumi, Daiichi Sankyo, Eli Lilly, GlaxoSmithKline, Taisho, Sanofi, Grant/research support from: AbbVie, Asahi Kasei, Boehringer Ingelheim, Chugai, Corrona, Daiichi Sankyo, Eisai, Kowa, Mitsubishi Tanabe, Takeda, Vivian Bykerk Consultant of: Amgen, Bristol Myers Squibb, Genzyme Corporation, Gilead, Regeneron, UCB, Grant/research support from: Amgen, Bristol Myers Squibb, Genzyme Corporation, Pfizer, Regeneron, Sanofi Aventis, UCB, Clifton Bingham Consultant of: AbbVie, Bristol Myers Squibb, Eli Lilly, Janssen, Pfizer, Sanofi, Grant/research support from: Bristol Myers Squibb, Thomas Huizinga Speakers bureau: Abblynx, Abbott, Biotest AG, Bristol Myers Squibb, Crescendo Bioscience, Eli Lilly, Epirus, Galapagos, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi- Aventis, UCB, Consultant of: Abblynx, Abbott, Biotest AG, Bristol Myers Squibb, Crescendo Bioscience, Eli Lilly, Epirus, Galapagos, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi- Aventis, UCB, Grant/research support from: Abblynx, Abbott, Biotest AG, Bristol Myers Squibb, Crescendo Bioscience, Eli Lilly, Epirus, Galapagos, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi- Aventis, UCB, Gustavo Citera Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Pfizer, Sandoz, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Pfizer, Grant/research support from: Pfizer, Yedid Elbez Consultant of: Bristol Myers Squibb, Employee of: Signifience, Vidya Perera Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Bindu Murthy Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Kelly Maxwell Consultant of: Bristol Myers Squibb, Employee of: Cognigen Corporation, Julie Passarell Consultant of: Bristol Myers Squibb, Employee of: Cognigen Corporation, William Hedrich: None declared, Daphne Williams Consultant of: Black Diamond Network, Joule, Syneos, Employee of: Bristol Myers Squibb.

POS0714 POOLED SAFETY ANALYSIS OF BARICITINIB IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: RESULTS FROM THREE RANDOMISED, DOUBLE-BLIND, PLACEBO-CONTROLLED, CLINICAL TRIALS

Background

Baricitinib (BARI), an oral selective inhibitor of Janus kinase 1 and 2 approved for the treatment of rheumatoid arthritis and atopic dermatitis, has been evaluated in clinical studies in patients with systemic lupus erythematosus (SLE).

Objectives

To assess the safety profile of BARI in patients with SLE.

Methods

Patients with SLE receiving stable background therapy were randomised 1:1:1 to BARI 2-mg, 4-mg, or placebo (PBO) once daily in one 24-week, phase 2 (NCT02708095) and two 52-week, phase 3, PBO controlled studies (NCT03616912 and NCT03616964).

Results

A total of 1,849 patients were included in this pooled analysis, representing 1,463.5 patient years of exposure (PYE). The incidence rates per 100 PYR at risk (IR/100 PYR) for serious adverse events (SAEs) were 9.5, 14.7, and 14.1 respectively for PBO, BARI 2-mg, and BARI 4-mg. There were no clinically meaningful differences between treatment groups for discontinuations due to AEs or death (Table 1).

Table 1.

Overview of safety measures of baricitinib in patients with SLE

Safety measurePBOBARI 2-mgBARI 4-mgPooled-BARIN=614N=621N=614N=1235PYE=488.1PYE=494.0PYE=481.4PYE=975.4n(%)n(%)n(%)n(%)PYRPYRPYRPYR[IR; 95%CI][IR; 95%CI][IR; 95%CI][IR; 95%CI]SAEs45 (7.3)70 (11.3)*65 (10.6)*135 (10.9)*473.2476.6461.9938.5[9.5; 6.9, 12.7][14.7; 11.5, 18.6][14.1; 10.9, 17.9][14.4; 12.1, 17.0]Discontinuation of study drug due to AE48 (7.8)58 (9.3)57 (9.3)115 (9.3)485.3492.3480.6973.0[9.9; 7.3, 13.1][11.8; 8.9, 15.2][11.9; 9.0, 15.4][11.8; 9.8, 14.2]Death4 (0.7)1 (0.2)4 (0.7)5 (0.4)488.2494.0481.5975.5[0.8; 0.2, 2.1][0.2; 0.0, 1.1][0.8; 0.2, 2.1][0.5; 0.2, 1.2]Serious infections12 (2.0)22 (3.5)28 (4.6)*50 (4.0)*484.3487.2472.5959.7[2.5; 1.3, 4.3][4.5; 2.8, 6.8][5.9; 3.9, 8.6][5.2; 3.9, 6.9]Herpes Zoster18 (2.9)17 (2.7)29 (4.7)46 (3.7)481.1486.5468.6955.1[3.7; 2.2, 5.9][3.5; 2.0, 5.6][6.2; 4.1, 8.9][4.8; 3.5, 6.4]VTEs#6 (1.2)3 (0.6)1 (0.2)4 (0.4)444.0450.2438.1888.3[1.4; 0.5, 2.9][0.7; 0.1, 1.9][0.2; 0.0, 1.3][0.5; 0.1, 1.2]MACE#01 (0.2)3 (0.6)4 (0.4)443.9450.1438.1888.3[0.0; NA, 0.8][0.2; 0.0, 1.2][0.7; 0.1, 2.0][0.5; 0.1, 1.2]Malignancy excluding NMSC2 (0.3)3 (0.5)2 (0.3)5 (0.4)488.0494.1481.4975.5[0.4; 0.0, 1.5][0.6; 0.1, 1.8][0.4; 0.1, 1.5][0.5; 0.2, 1.2]NMSC2 (0.3)000*486.7494.0481.4975.4[0.4; 0.0, 1.5][0.0; NA, 0.7][0.0; NA, 0.8][0.0; NA, 0.4]

Data are n (%) patients PYR [IR; 95% CI]. #Phase 2 study data not included. AE=adverse event; CI=confidence interval; MACE=major adverse cardiac event; NMSC=non-melanoma skin cancers; VTE=venous thrombotic event (includes deep vein thrombosis and pulmonary embolism); IR=incidence rate (100 times the number of patients reporting an adverse event divided by the event-specific exposure to treatment); N=number of patients in the analysis population; n=number of patients in the specified category; PYE=patient-year of exposure; PYR=patient years at risk; SAE=serious adverse event. *p≤0.05 vs placebo.

The IR/100 PYR for serious infections were 2.5, 4.5, and 5.9 respectively for PBO, BARI 2-mg, and BARI 4-mg. The risk of Herpes Zoster was higher in BARI 4-mg (4.7%) vs PBO (2.9%) (Table 1).

The IR/100 PYR for positively adjudicated venous thrombotic events (VTEs) were 1.4, 0.7, and 0.2 respectively for PBO, BARI 2-mg, and BARI 4-mg. The IR/100 PYR for positively adjudicated major adverse cardiac event (MACE) was numerically higher in BARI 2-mg (0.2) and BARI 4-mg (0.7) vs PBO (0.0), however the pooled-BARI IR/PYR (0.5) was within the range of background disease (1). No increased risk for malignancies was observed.

Conclusion

The safety profile of BARI in SLE patients was consistent with the known BARI safety profile. There was no increased risk of VTE in BARI treatment groups.

References

[1]Barbhaiya M, Feldman CH, et al. Arthritis Rheumatol. 2017;69(9):1823-31.

Disclosure of Interests

Thomas Dörner Speakers bureau: Eli Lilly and Company and Roche, Consultant of: AbbVie, Celgene, Eli Lilly and Company, Janssen, Novartis, Roche, Samsung and UCB, Grant/research support from: Chugai, Janssen, Novartis and Sanofi, Yoshiya Tanaka Speakers bureau: Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Consultant of: Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie, Grant/research support from: Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, Marta Mosca Speakers bureau: Eli Lilly, GSK, Astra Zeneca, Consultant of: Eli Lilly, GSK, Astra Zeneca, Ian N. Bruce Speakers bureau: GSK, Astra Zeneca, UCB, Consultant of: Eli Lilly, GSK, UCB, BMS, Merck Serono, Astra Zeneca, IL-TOO, Aurinia, Grant/research support from: GSK, Janssen, Mario Cardiel Speakers bureau: Eli Lilly, Pfizer, Abbvie, Consultant of: Eli Lilly, Pfizer, Grant/research support from: Pfizer, Gilead, Roche, Janssen, Eric F. Morand Speakers bureau: AstraZeneca, Eli Lilly, Novartis, Consultant of: Amgen, AstraZeneca, Asahi Kasei, Biogen, BristolMyersSquibb, Capella, Eli Lilly, EMD Serono, Genentech, GlaxoSmithKline, Janssen, Neovacs, Sanofi, Servier, UCB, Wolf, Grant/research support from: Janssen, AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, GlaxoSmithKline, Michelle A Petri Consultant of: Eli Lilly, Grant/research support from: Eli Lilly, Maria Silk Shareholder of: Eli Lilly, Employee of: Eli Lilly, christina dickson Shareholder of: Eli Lilly, Employee of: Eli Lilly, Gabriella Meszaros Shareholder of: Eli Lilly, Employee of: Eli Lilly, Maher Issa Shareholder of: Eli Lilly, Employee of: Eli Lilly, Lu Zhang Shareholder of: Eli Lilly, Employee of: Eli Lilly, Daniel J. Wallace Consultant of: Amgen, Eli Lilly and Company, EMD Merck Serono and Pfizer

POS0704 EFFICACY AND SAFETY OF FILGOTINIB IN PATIENTS WITH INADEQUATE RESPONSE TO METHOTREXATE, WITH 4 OR <4 POOR PROGNOSTIC FACTORS: A POST HOC ANALYSIS OF THE FINCH 1 STUDY

Background

Patients (pts) with rheumatoid arthritis (RA) and poor prognostic factors1 (PPF) are at risk for progression without adequate treatment. Filgotinib (FIL) is a once daily Janus kinase 1 preferential inhibitor. In FINCH 1 (NCT02889796), FIL 200 mg (FIL200) was effective vs placebo (PBO) and noninferior to adalimumab (ADA) in pts with RA and inadequate response to methotrexate (MTX-IR); FIL200 and FIL 100 mg (FIL100) were well tolerated.2

Objectives

This post hoc, exploratory analysis examined efficacy and safety of FIL in MTX-IR pts with 4 or <4 PPF.

Methods

The FINCH 1 52-week (W), double-blind trial randomised MTX-IR pts with moderate–severe RA to FIL200 or FIL100, ADA, or PBO; all received background MTX. PBO pts were rerandomised, blinded, at W24 to FIL200 or FIL100. We examined pts with 4 PPF at baseline (BL): erosions on X-ray, seropositivity for rheumatoid factor or anticyclic citrullinated peptide, high-sensitivity C-reactive protein (hsCRP) ≥6 mg/L, and disease activity score in 28 joints with CRP (DAS28[CRP]) >5.1, along with those with <4 PPF. Efficacy included DAS28(CRP) <2.6 and modified Total Sharp Score (mTSS) change from baseline (CFB). Fisher’s exact test was used for DAS28(CRP); the mixed-effects model was used to generate least squares mean mTSS CFB. P values were nominal, not adjusted for multiplicity.

Results

At BL, of 1755 randomized, treated pts, 687 had 4 PPF, and 1068 had <4 PPF. Among pts with <4PPF, 804 [75%] had erosions, 810 [76%] were seropositive, 377 [35%] had hsCRP ≥6 mg/L, 638 [60%] had DAS28[CRP] >5.1). Pts with 4 vs <4 PPF were aged 53 vs 52 years, had RA duration 8.3 vs 7.4 years, DAS28(CRP) 6.3 vs 5.4, and SDAI 45.6 vs 37.7. In pts with 4 or <4 PPF, higher proportions receiving FIL200 or FIL100 achieved DAS28(CRP) <2.6 at W12 vs PBO (nominal P <.001); proportions with DAS28(CRP) <2.6 increased with FIL200, FIL100, or ADA at W52 (Figure 1). DAS28(CRP) responses for FIL200 at W52 were similar in 4 vs <4 PPF pts; FIL100 and ADA responses were numerically higher in <4 vs 4 PPF pts. At W24, mTSS CFB in pts with 4 PPF was 0.21, 0.23, 0.30, and 0.66 for FIL200, FIL100, ADA, and PBO (P <.05 for FIL200 and FIL100 vs PBO); corresponding changes in <4 PPF pts were 0.08, 0.10, 0.11, and 0.24 (P >.05). At W52, mTSS CFB in 4 PPF pts was 0.29, 0.84, and 0.80 for FIL200, FIL100, and ADA, respectively, and 0.14, 0.25, and 0.53 in <4 PPF pts. Rates of adverse events (AEs), including AEs of interest, were comparable for pts with 4 PPF and <4 PPF for all treatment arms (Table 1).

Table 1.

AEs and AEs of interest in BL 4 PPF and <4 PPF subgroups

4 PPF<4 PPFFIL200FIL100ADAPBO beforeFIL200FIL100ADAPBO(n = 191)(n = 189)(n = 126)W24 switch (n = 181)(n = 284)(n = 291)(n = 199)before W24 switch (n = 294)All AEs146 (76.4)136 (72.0)85 (67.5)90 (49.7)206 (72.5)214 (73.5)154 (77.4)164 (55.8)AEs of interestSerious infectious AE5 (2.6)4 (2.1)6 (4.8)2 (1.1)8 (2.8)9 (3.1)4 (2.0)2 (0.7)Opportunistic infections001 (0.8)0001 (0.5)0Active tuberculosis0000001 (0.5)0Herpes zoster1 (0.5)1 (0.5)1 (0.8)05 (1.8)3 (1.0)1 (0.5)2 (0.7)Hepatitis B or C01 (0.5)001 (0.5)01 (0.5)0MACE01 (0.5)01 (0.6)01 (0.3)1 (0.5)1 (0.3)VTE001 (0.8)1 (0.6)1 (0.4)001 (0.3)DVT001 (0.8)1 (0.6)0001 (0.3)PE00001 (0.4)000Malignancy0003 (1.7)2 (0.7)2 (0.7)2 (1.0)0(non-NMSC)GI perforation00001 (0.4)000

Values are n (%). ADA, adalimumab; AE, adverse event; BL, baseline; DVT, deep vein thrombosis; FIL100, filgotinib 100 mg; FIL200; filgotinib 200 mg; GI, gastrointestinal; MACE, major adverse cardiac event; NMSC, nonmelanoma skin cancer; PBO, placebo; PE, pulmonary embolism; PPF, poor prognostic factor; VTE, venous thromboembolism; W, week.

Conclusion

In high-risk (4 PPF) pts with MTX-IR RA, FIL200 and FIL100 showed similar reductions in disease activity vs PBO at W12 as in pts with <4 PPF; mTSS in FIL200 pts changed little from W24 to W52. Tolerability was comparable across treatment arms, regardless of presence of 4 or <4 PPF.

References

[1]Smolen JS et al. Ann Rheum Dis. 2020;79:685–99.

[2]Combe B et al. Ann Rheum Dis. 2021;80:848–58.

Acknowledgements

This study was funded by Gilead Sciences, Inc., Foster City, CA. Medical writing support was provided by Rob Coover, MPH, of AlphaScientia, LLC, San Francisco, CA, and was funded by Gilead Sciences, Inc., Foster City, CA. Funding for this analysis was provided by Gilead Sciences, Inc. The sponsors participated in the planning, execution, and interpretation of the research.

Disclosure of Interests

Bernard Combe Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and Roche-Chugai, Consultant of: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and Roche-Chugai, Grant/research support from: Pfizer and Roche-Chugai, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, Behringer-Ingelheim, Bristol-Myers, Chugai, Eisai, Eli Lilly, Gilead Sciences, Inc., Mitsubishi-Tanabe, and YL Biologics, Paid instructor for: AbbVie, Amgen, Astellas, AstraZeneca, Behringer-Ingelheim, Bristol-Myers, Chugai, Eisai, Eli Lilly, Gilead Sciences, Inc., Mitsubishi-Tanabe, and YL Biologics, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Maya H Buch Speakers bureau: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Paid instructor for: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Gerd Rüdiger Burmester Speakers bureau: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc., Consultant of: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc., Beatrix Bartok Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Ling Han Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Kahaku Emoto Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences K.K., Shungo Kano Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences K.K., Thijs Hendrikx Employee of: Galapagos BV, Daniel Aletaha Speakers bureau: Bristol-Myers Squibb, Merck Sharp & Dohme, and UCB; AbbVie, Amgen, Celgene, Eli Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, and Sanofi/Genzyme., Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, and Sanofi/Genzyme; Janssen, Grant/research support from: from AbbVie, Merck Sharp & Dohme, Novartis, and Roche

POS0708 EVALUATING THE HYPERSENSITIVITY PROFILE OF ANIFROLUMAB AND THE NEED FOR PREINFUSION PROPHYLACTIC TREATMENT IN PATIENTS WITH SLE

Background

Anifrolumab, a human monoclonal antibody (mAb), is approved in Canada, Japan, and the United States for the treatment of patients with systemic lupus erythematosus (SLE) based on results from the phase 2b MUSE and the phase 3 TULIP-1/-2 trials.1–3 Anaphylactic reactions (ARs), hypersensitivity reactions (HSRs), and infusion-related reactions (IRRs) are risks of mAb infusions, so physicians prescribing anifrolumab may wish to understand the hypersensitivity profile and whether prophylactic pretreatments are required to mitigate HSR/IRRs.

Objectives

To evaluate the hypersensitivity profile of anifrolumab and the need for pretreatment.

Methods

Pooled data were analyzed from patients with moderate to severe SLE despite standard therapy who received intravenous infusions (every 4 weeks, 48 weeks) of anifrolumab or placebo in the randomized, 52-week MUSE (NCT01438489),1 TULIP-1 (NCT02446912),2 and TULIP-2 (NCT02446899)3 trials. An AR (analyzed in the anifrolumab 150/300/1000 mg and placebo groups) was defined as acute illness onset within minutes to several hours of infusion with involvement of skin and/or mucosal tissue, and/or respiratory compromise, and/or reduced blood pressure, and/or persistent gastrointestinal symptoms. HSRs and IRRs were analyzed in the anifrolumab 300 mg group (as this is the approved dose) and the placebo group. An HSR was defined as acute illness onset with involvement of skin and/or mucosal tissue during infusion (not meeting the AR definition); IRR was defined as any other reaction occurring during/within 24 hours of infusion. Patients did not receive pretreatment unless they had experienced a previous IRR/HSR in the program. Pretreatment was assumed if a patient received prophylactic antihistamine, corticosteroid, non-steroidal anti-inflammatory drug, and/or dopamine antagonist 1 day before/on the day of infusion.

Results

Of patients who received anifrolumab 300 mg (n=459), anifrolumab 1000 mg (n=105), or placebo (n=466), none experienced ARs; 1 patient who received anifrolumab 150 mg (n=93) experienced an AR. HSRs occurred in 3% (n=12) of anifrolumab 300 mg-treated patients (of whom 4 had a history of HSRs) vs 1% (n=3) in the placebo group. IRRs occurred in 9% (n=43) of anifrolumab-treated patients vs 7% (n=33) in the placebo group. All HSRs and IRRs were mild/moderate in intensity. There were no discontinuations due to HSRs or IRRs in the anifrolumab group, while there were 2 in the placebo group (HSR: n=1; IRR: n=1). In the anifrolumab 300 mg and placebo groups, more patients experienced HSR/IRRs with the initial (1–6) vs later infusions (Figure 1). In the anifrolumab group, the median (median absolute deviation) time to first HSR or IRR was 30.5 (29.5) days or 27.0 (26.0) days, respectively. Of the 12 anifrolumab-treated patients with ≥1 HSR, 3 received subsequent pretreatment, and none had any HSR after the use of pretreatment. Of the 43 anifrolumab-treated patients with ≥1 IRR, 2 received pretreatment, of whom 1 had an IRR after pretreatment and anifrolumab dosage remained unchanged.

Conclusion

Following anifrolumab infusion, ARs were uncommon, and few (3%) patients experienced HSRs. HSRs and IRRs with the approved anifrolumab 300 mg dose were mild to moderate, occurred early in treatment, did not lead to discontinuation, and only rarely required pretreatment. Our data support a safe and manageable hypersensitivity profile for anifrolumab.

References

[1]Furie R, et al. Arthritis Rheumatol. 2017;69:376–86.

[2]Furie R, et al. Lancet Rheumatol. 2019;1:e208–19.

[3]Morand E, et al. N Engl J Med. 2020;382:211–21.

Acknowledgements

Writing assistance was provided by Rosie Butler, PhD, of JK Associates Inc., part of Fishawack Health. This study was sponsored by AstraZeneca.

Disclosure of Interests

Kenneth C Kalunian Consultant of: Aurinia, Equillium, Kezar, BMS, Chemocentryx, Eli Lilly, Biogen, Roche/Genentech, Grant/research support from: Horizon, UCB, Yoshiya Tanaka Speakers bureau: Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Consultant of: Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie, Grant/research support from: Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, Ihor Hupka Employee of: AstraZeneca, Lijin (Jinny) Zhang Shareholder of: AstraZeneca, Employee of: AstraZeneca, Manish Shroff Employee of: AstraZeneca, Shanti Werther Shareholder of: AstraZeneca, Employee of: AstraZeneca, Gabriel Abreu Employee of: AstraZeneca AB, Catharina Lindholm Employee of: AstraZeneca, Raj Tummala Shareholder of: AstraZeneca, Employee of: AstraZeneca

POS0190 EFFICACY AND SAFETY OF BARICITINIB IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: RESULTS FROM TWO RANDOMISED, DOUBLE-BLIND, PLACEBO-CONTROLLED, PARALLEL-GROUP, PHASE 3 STUDIES

Background

In a 24-week, phase 2 clinical study (NCT02708095) in patients with systemic lupus erythematosus (SLE), baricitinib (BARI), an oral selective inhibitor of Janus kinase 1 and 2 approved for the treatment of rheumatoid arthritis and atopic dermatitis, inhibited the type l interferon gene signature, multiple other cytokine pathways, and improved disease activity (1) (2).

Objectives

To further evaluate the efficacy and safety of BARI in patients with SLE.

Methods

Patients with active SLE receiving stable background therapy were randomised 1:1:1 to BARI 2-mg, 4-mg, or placebo (PBO) once daily in two identically designed, 52-week, phase 3 randomised, PBO-controlled studies. In SLE-BRAVE-I (NCT03616912) and -II (NCT03616964), 760 and 775 patients, respectively were enrolled in a balanced manner across regions, although different countries per region participated in each study. The primary endpoint for both studies was the proportion of patients achieving an SLE Responder Index-4 (SRI-4) response at week 52. Glucocorticoid tapering was encouraged but not required per protocol.

Results

The mean Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) at baseline was 10.1 for both SLE-BRAVE-I and -II participants; musculoskeletal and mucocutaneous domains were the most common domains involved at baseline. In SLE-BRAVE-I, the proportion of SRI-4 responders at week 52 among patients treated with BARI 4-mg (56.7%), but not BARI 2-mg (49.8%), was significantly greater than in patients treated with PBO (45.9%, p = 0.016) (Table 1). No difference was seen in SLE-BRAVE-II (47.1%, 46.3%, and 45.6%, BARI 4-mg, 2-mg, and PBO, respectively). None of the key secondary endpoints, including glucocorticoid tapering or time to first severe flare (SFI), were met in either study. The proportions of patients with serious adverse events (SAEs) were 7.1% and 8.6% for PBO, 9.4% and 13.4% for BARI 2-mg and 10.3% and 11.2% for BARI 4-mg in SLE-BRAVE-I and II, respectively.

Table 1.

Efficacy and safety of baricitinib in patients with SLE-BRAVE-I and -II

SLE-BRAVE-ISLE-BRAVE-IIEfficacy measurePBO (N=253)BARI 2-mg (N=255)BARI 4-mg (N=252)PBO (N=256)BARI 2-mg (N=261)BARI 4-mg (N=258)SRI-4 (W52)116 (45.9)126 (49.8)142 (56.7)*116 (45.6)120 (46.3)121 (47.1)SRI-4 (W24)99 (39.1)114 (44.8)117 (46.5)98 (38.6)104 (40.0)108 (42.1)Severe Flares (n, events)38 (15.0)34 (13.3)26 (10.3)26 (10.2)29 (11.1)29 (11.2)HR for time to first severe flare (SFI) HR [CI]NA0.8 [0.52, 1.32]0.65 [0.40, 1.08]NA1.1 [0.65, 1.89]1.1 [0.67, 1.94]Glucocorticoid sparing36 (30.8)31 (29.2)36 (34.0)33 (31.7)34 (29.8)36 (34.3)LLDAS (W52)66 (26.2)65 (25.7)74 (29.7)59 (23.2)62 (24.0)65 (25.4)Safety measureTEAE210 (83.0)210 (82.4)208 (82.5)198 (77.3)199 (76.2)200 (77.5)SAE18 (7.1)24 (9.4)26 (10.3)22 (8.6)35 (13.4)29 (11.2)

Data are n (%) patients, unless otherwise indicated. BARI=baricitinib; CI=confidence interval; HR=hazard ratio compared with PBO; LLDAS=lupus low disease activity state; N=number of patients in the analysis population; n=number of patients in the specified category; PBO=placebo; TEAE=treatment-emergent adverse event; SAE=serious adverse event; W=week. *p≤0.05 vs PBO.

Conclusion

Although phase 2 data suggested BARI as a potential treatment for patients with SLE (2), the SLE-BRAVE-I and -II phase 3 study results were discordant for the primary outcome measure, with only SLE-BRAVE-I positive, making it difficult to elucidate benefit. Additional analyses are being performed to understand this discordance. No new safety signals were observed.

References

[1]Dörner T, Tanaka Y, et al. Lupus Sci Med. 2020;7(1).

[2]Wallace DJ, Furie RA, et al. Lancet. 2018;392(10143):222-31.

Disclosure of Interests

Eric F. Morand Speakers bureau: Astra Zeneca, Eli Lilly, Novartis, Sanofi, Consultant of: Amgen, AstraZeneca, Asahi Kasei, Biogen, BristolMyersSquibb, Capella, Eli Lilly, EMD Serono, Genentech, Glaxosmithkline, Janssen, Neovacs, Sanofi, Servier, UCB, Wolf, Grant/research support from: Janssen, AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, GlaxoSmithKline, Yoshiya Tanaka Speakers bureau: Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Consultant of: Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie, Grant/research support from: Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, Richard Furie Consultant of: Eli Lilly, Edward Vital Consultant of: Eli Lilly (consultant and honoraria), Ronald van Vollenhoven Consultant of: Abbvie, Biotest, BMS, Celgene, Crescendo, Eli Lilly and Company, GSK, Janssen, Merck, Novartis, Pfizer, Roche, UCB, Vertex, Grant/research support from: Abbvie, Amgen, BMS, GSK, Pfizer, Roche, UCB, Kenneth Kalunian Consultant of: Eli Lilly, Marta Mosca Consultant of: Eli Lilly, GSK, Astra Zeneca, Thomas Dörner Speakers bureau: AbbVie, Eli Lilly, BMS, Novartis, BMS/Celgene, Janssen, Consultant of: AbbVie, Eli Lilly, BMS, Novartis, BMS/Celgene, Janssen, Daniel J. Wallace Consultant of: Amgen, Eli Lilly and Company, EMD Merck Serono, and Pfizer, Maria Silk Shareholder of: Eli Lilly, Employee of: Eli Lilly, christina dickson Shareholder of: Eli Lilly, Employee of: Eli Lilly, Inmaculada De La Torre Shareholder of: Eli Lilly, Employee of: Eli Lilly, Gabriella Meszaros Shareholder of: Eli Lilly, Employee of: Eli Lilly, Bochao Jia Shareholder of: Eli Lilly, Employee of: Eli Lilly, Brenda Crowe Shareholder of: Eli Lilly, Employee of: Eli Lilly, Michelle A Petri Consultant of: Eli Lilly

POS0235 INTEGRATED SAFETY ANALYSIS UPDATE FOR FILGOTINIB (FIL) IN PATIENTS (PTS) WITH MODERATELY TO SEVERELY ACTIVE RHEUMATOID ARTHRITIS (RA) RECEIVING TREATMENT OVER A MEDIAN OF 2.2 YEARS (Y)

Background

The preferential Janus kinase-1 inhibitor FIL significantly improved signs and symptoms of RA in Phase 2 and 3 trials.1–5 FIL is approved for treatment of moderate to severe active RA in Europe and Japan. Integrated safety analysis of FIL with patient data through 2019 was presented at the 2020 ACR virtual meeting.6

Objectives

To report updated, as-treated data from the FIL integrated safety analysis with increased study drug exposure.

Methods

Data were integrated from 2 Phase 2 (NCT01668641, NCT01894516), 3 Phase 3 (NCT02889796, NCT02873936, NCT02886728), and 2 long-term extension (LTE) (NCT02065700, NCT03025308) trials. Phase 2 and 3 LTE data were through Nov 2020 and Jan 2021, respectively. The as-treated analysis set included all available data for pts receiving ≥1 dose FIL 200 (FIL200) or 100 mg (FIL100), including those rerandomized to FIL for LTE. Exposure-adjusted incidence rates (EAIR)/100 patient-y exposure (PYE) of treatment-emergent adverse events (TEAEs; onset after first dose and no later than 30 days after last dose or new drug first dose date −1 day) and TEAEs of special interest (AESIs) are presented.

Results

3691 pts received FIL200 or FIL100 for 8085.1 PYE (median 2.2, maximum 6.8 y). In the as-treated set, 61% of FIL200 and 45% of FIL100 pts received FIL for ≥2 y, 19% and 5% for ≥3 y, and 11% and 0.5% for ≥4.5 y, respectively. EAIR for TEAEs was higher with FIL100 than FIL200; EAIRs for deaths were 0.5 and 0.3 for FIL200 and FIL100 (Figure 1). Incidences of infections and serious infections were numerically greater for FIL100 vs FIL200, while EAIRs for other AESIs were comparable between doses (Table 1). EAIRs for AESIs tended to decrease since the previous update, except for venous thromboembolism (total FIL 0.1 to 0.2) and malignancies excluding NMSC (total FIL 0.5 to 0.6).

Table 1.

TEAEs of special interest, as-treated set

TEAE, n (%) and EAIR per 100 PYE (95% CI)FIL 200 mgn=2267PYE=5302.5FIL 100 mgn=1647PYE=2782.6Total FILN=3691PYE=8085.1Infectious AEs1206 (53.2)747 (45.4)1927 (52.2)EAIR21.1 (19.7, 22.5)30.2 (26.8, 34.0)21.0 (19.9, 22.3)Serious infectious AEs80 (3.5)57 (3.5)137 (3.7)EAIR1.5 (1.1, 1.9)2.7 (1.9, 3.9)1.6 (1.3, 2.0)Opportunistic infections5 (0.2)4 (0.2)9 (0.2)EAIR0.1 (0, 0.2)*0.1 (0.1, 0.4)*0.1 (0.1, 0.2)*Active tuberculosis03 (0.2)3 (<0.1)EAIR00.1 (0, 0.3)*0 (0, 0.1)*Herpes zoster84 (3.7)30 (1.8)114 (3.1)EAIR1.6 (1.2, 2.0)1.1 (0.8, 1.5)*1.4 (1.1, 1.7)Major adverse cardiovascular eventsa19 (0.8)14 (0.9)33 (0.9)EAIR0.3 (0.2, 0.5)0.5 (0.3, 0.8)*0.4 (0.2, 0.6)Venous thromboembolismb11 (0.5)4 (0.2)15 (0.4)EAIR0.2 (0.1, 0.4)*0.1 (0.1, 0.4)*0.2 (0.1, 0.3)*Atrial systemic thrombotic eventsa1 (<0.1)1 (<0.1)2 (<0.1)EAIR0 (0, 0.1)0 (0, 0.3)0 (0, 0.1)Malignancy excluding NMSC32 (1.4)17 (1.0)49 (1.3)EAIR0.6 (0.4, 0.9)0.6 (0.4, 1.0)*0.6 (0.4, 0.8)NMSC15 (0.7)5 (0.3)20 (0.5)EAIR0.3 (0.2, 0.5)*0.2 (0.1, 0.4)*0.2 (0.2, 0.4)*Gastrointestinal perforations3 (0.1)1 (<0.1)4 (0.1)EAIR0.1 (0, 0.2)*0 (0, 0.3)*0 (0, 0.1)*

*Except when any study had 0 event within the treatment, the Poisson model was not adjusted by study. PYE was defined as (last dose date − first dose date + 1)/365.25.

a

Positively adjudicated.

b

Adjudicated as deep vein thrombosis or pulmonary embolism.

NMSC, nonmelanoma skin cancer

Conclusion

With 1 additional year of exposure since the 2020 report, FIL continues to be well tolerated with no new safety concerns emerging. EAIRs of TEAEs, including deaths, and AESIs remained stable or decreased since the 2020 report, except for slight increases in rates of NMSC and malignancies excluding NMSC. In the context of demonstrated efficacy, both FIL doses had an acceptable risk/benefit profile.

References

[1]Westhovens R et al. Ann Rheum Dis 2017;76:998–1008.

[2]Kavanaugh A et al. Ann Rheum Dis 2017;76:1009–19.

[3]Combe B et al. Ann Rheum Dis 2021;80:848–58.

[4]Genovese MC et al. JAMA 2019;322:315–25.

[5]Westhovens R et al. Ann Rheum Dis 2021;80:727–38.

[6]Winthrop K et al. Arthritis Rheumatol 2020;72(suppl 10); abstract 0229.

Acknowledgements

Funding for DARWIN 1 and 2 was provided by Galapagos NV, and funding for DARWIN 3, FINCH 1, 2, 3, and 4 was provided by Gilead Sciences, Inc., Foster City, CA. Funding for this analysis was provided by Gilead Sciences, Inc. The sponsors participated in the planning, execution, and interpretation of the research. Medical writing support was provided by Gregory Bezkorovainy, MA, of AlphaScientia, LLC, San Francisco, CA; and funded by Gilead Sciences, Inc., Foster City, CA.

Disclosure of Interests

Kevin Winthrop Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly and Co., Galapagos NV, Gilead Sciences, Inc., GlaxoSmithKline, Pfizer, Roche, Regeneron, Sanofi, and UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, and Pfizer, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol Myers Squibb, Eisai, Chugai, AbbVie, Astellas, Pfizer, Sanofi, Asahi-Kasei, GSK, Mitsubishi-Tanabe, Gilead Sciences, Inc., and Janssen, Consultant of: AbbVie, Ayumi, Daiichi-Sankyo, Eli Lilly, GSK, Taisho, and Sanofi, Grant/research support from: AbbVie, Asahi-Kasei, Chugai, Daiichi-Sankyo, Eisai, Mitsubishi-Tanabe, and Takeda, Tsutomu Takeuchi Speakers bureau: AbbVie, AYUMI, Bristol Myers Squibb, Chugai, Daiichi Sankyo, Dainippon Sumitomo, Eisai, Eli Lilly Japan, Gilead Sciences, Inc., Mitsubishi-Tanabe, Novartis, Pfizer Japan, and Sanofi, Consultant of: Astellas, Chugai, and Eli Lilly Japan, Grant/research support from: AbbVie, Asahi Kasei, Astellas, Chugai, Daiichi Sankyo, Eisai, Mitsubishi-Tanabe, Shionogi, Takeda, and UCB Japan, Alan Kivitz Shareholder of: Amgen, Gilead Sciences, Inc., GlaxoSmithKline, Pfizer, and Sanofi, Speakers bureau: AbbVie, Celgene, Flexion, Genzyme, Horizon, Merck, Novartis, Pfizer, Regeneron, and Sanofi, Paid instructor for: Celgene, Genzyme, Horizon, Merck, Novartis, Pfizer, Regeneron, and Sanofi, Consultant of: AbbVie, Boehringer Ingelheim, Flexion, Genzyme, Gilead Sciences, Inc., Janssen, Novartis, Pfizer, Regeneron, Sanofi, and SUN Pharma Advanced Research, Mark C. Genovese Shareholder of: Gilead Sciences, Inc., Consultant of: AbbVie, Amgen, Beigene, Eli Lilly and Co., Genentech, Inc., Gilead Sciences, Inc., Sanofi Genzyme, RPharm, and SetPoint, Employee of: Gilead Sciences, Inc., Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Franziska Matzkies Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Beatrix Bartok Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Kun Chen Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Deyuan Jiang Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Iyabode Tiamiyu Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos BV, Employee of: Galapagos BV, Sander Strengholt Shareholder of: Galapagos BV, Employee of: Galapagos BV, Gerd Rüdiger Burmester Speakers bureau: AbbVie, Eli Lilly and Co., Galapagos, Gilead Sciences, Inc., and Pfizer, Consultant of: AbbVie, Eli Lilly and Co., Galapagos, Gilead Sciences, Inc., and Pfizer, Jacques-Eric Gottenberg Speakers bureau: AbbVie, Eli Lilly and Co., Galapagos BV, Gilead Sciences, Inc., Roche, Sanofi Genzyme, and UCB, Consultant of: Bristol Myers Squibb, Sanofi Genzyme, and UCB, Grant/research support from: Bristol Myers Squibb and Pfizer

OP0142 COMPARISON OF ATTAINMENT AND PROTECTIVE EFFECTS OF THE LUPUS LOW DISEASE ACTIVITY STATE IN PATIENTS WITH NEWLY DIAGNOSED VERSUS ESTABLISHED SLE - A MULTICENTRE PROSPECTIVE STUDY

Background

Lupus low disease activity state (LLDAS) attainment has been reported to be associated with reduced damage accrual, flare, and mortality, as well as improved quality of life, in cohorts of SLE patients with established disease. Whether these associations are present in recent-onset disease is less well known.

Objectives

To evaluate the associations of LLDAS attainment with outcomes in patients with recent onset SLE.

Methods

Data from a 13-country longitudinal SLE cohort (ACR/SLICC criteria) were collected prospectively between 2013 and 2020 using standard templates. Organ damage and flare were captured using SLICC Damage Index and SELENA-SLEDAI Flare Index, respectively. LLDAS was defined as Golder et al., 2019 [1]. An inception cohort was defined based on duration since SLE diagnosis<1 year at enrolment. Patient characteristics between inception and non-inception cohorts were compared using Wilcoxon rank-sum (continuous variables) or Pearson’s Chi-squared tests (categorical variables). Survival analyses were performed to examine the association between LLDAS attainment and damage accrual and flare.

Results

The study cohort included 4,106 patients of whom 680 (16%) were recruited within 1 year of SLE diagnosis (inception cohort). Compared to the non-inception cohort, inception cohort patients were significantly younger, had higher disease activity (SLEDAI-2K and physician global assessment), used more glucocorticoids and immunosuppressants but had less organ damage at enrolment and only 88 (13.6%) patients accrued damage during a median 2.2 years follow-up (Table 1).

Table 1.Non-inception cohortInception cohortp-valuen=3426n=680Age at enrolment (years), median [IQR]40 [31, 51]33 [25, 44]<0.001Age at diagnosis (years), median [IQR]28 [21, 38]33 [25, 43]<0.001SLE duration at enrolment (years), median [IQR]10 [5, 16]1 [0, 1]<0.001Study duration (years), median [IQR]2.5 [1.0, 5.4]2.2 [0.9, 3.7]<0.001Females, n (%)3155 (92.1%)623 (91.6%)0.68Asian ethnicity, n (%)3037 (89.1%)595 (88.1%)0.49Prednisolone (PNL) use - ever, n (%)2865 (83.6%)620 (91.2%)<0.001Time adjusted mean (TAM)-PNL, median [IQR]5.0 [2.2, 8.6]6.2 [3.2, 10.3]<0.001Cumulative PNL (g), median [IQR]3.4 [0.5, 9.7]3.8 [1.1, 8.5]0.26Anti-Malarial use - ever, n (%)2669 (77.9%)569 (83.7%)<0.001Immunosupressant use -ever, n (%)2367 (69.1%)521 (76.6%)<0.001AMS (TAM-SLEDAI-2K), median [IQR]2.8 [1.2, 4.6]3.1 [1.6, 5.0]0.002TAM-PGA, median [IQR]0.4 [0.2, 0.7]0.4 [0.3, 0.8]<0.001Mild/moderate/severe flare ever, n (%)1789 (52.2%)391 (57.5%)0.012Organ damage accrual, n (%)629 (20.8%)88 (13.6%)<0.001LLDAS at baseline, n (%)1730 (50.5%)195 (28.7%)<0.001LLDAS-ever (at least once), n (%)2637 (78.2%)492 (73.9%)0.014≥50% time in LLDAS (LLDAS-5), n (%)1612 (50.6%)256 (41.1%)<0.001

Significantly fewer inception cohort patients were in LLDAS at enrolment than the non-inception cohort (29% vs. 51%, p<0.001). However, 74% of inception and 78% of non-inception cohort patients achieved LLDAS at least once during follow-up. Limiting analysis only to patients not in LLDAS at enrolment, time to first LLDAS attainment was assessed: inception cohort patients were 60% more likely to attain their first LLDAS (HR = 1.60 (95%CI: 1.40, 1.82), p<0.001) than non-inception cohort patients. LLDAS attainment was significantly protective against flare in the inception (HR, 95% CI) and non-inception (HR, 95% CI) cohorts. Trends towards protection against damage accrual in association with LLDAS in the inception cohort were not significant.

Conclusion

LLDAS attainment is protective from flare in recent onset SLE. Significant protection from damage accrual was not observed, due to low rates of damage accrual in the first years after SLE diagnosis.

References

[1]Golder, V., et al., Lupus low disease activity state as a treatment endpoint for systemic lupus erythematosus: a prospective validation study. The Lancet Rheumatology, 2019. 1(2): p. e95-e102.

Acknowledgements

We thank all patients participating in the Asia Pacific Lupus Collaboration (APLC) cohort, and all data collectors for their ongoing support for APLC research activities.

The APLC has received unrestricted project grants from AstraZeneca, BMS, Eli Lily, Janssen, Merck Serono, and UCB to support data collection contributing to this work.

Disclosure of Interests

Vera Golder: None declared, Rangi Kandane-Rathnayake: None declared, Worawit Louthrenoo: None declared, Yi-Hsing Chen Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra and Zeneca, Sanofi, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead, Grant/research support from: Yes. Clinical trials and/or research grants from Pfizer, Norvatis, BMS, Abbevie, Johnson & Johnson, Roche,Sanofi, Guigai, Roche, Boehringer Ingelheim, UCB, MSD, Astra-Zeneca,Astellas, Gilead, Jiacai Cho: None declared, Aisha Lateef: None declared, Laniyati Hamijoyo Speakers bureau: Pfizer, Novartis, Abbot, Shue Fen Luo: None declared, Yeong-Jian Jan Wu Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, Sandra Navarra Speakers bureau: Pfizer, Johnson & Johnson, Novartis, Astellas, Grant/research support from: Astellas, Johnson & Johnson, Leonid Zamora: None declared, Zhanguo Li Speakers bureau: Eli, Lilly, Novartis, GSK, AbbVie, Paid instructor for: Pfizer, Roche, Johnson, Consultant of: Lilly, Pfizer, Grant/research support from: Pfizer, Yuan An: None declared, Sargunan Sockalingam Speakers bureau: Yes. Pfizer, Roche, Novartis, Grant/research support from: Roche and Novartis, Yasuhiro Katsumata Speakers bureau: Chugai Pharmaceutical Co., Ltd., Glaxo-Smithkline K.K., and Sanofi K.K., Masayoshi Harigai Speakers bureau: MH has received speaker’s fee from AbbVie Japan GK, Ayumi Pharmaceutical Co., Boehringer Ingelheim Japan, Inc.,Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Ltd., Eisai Co., Ltd., Eli Lilly Japan K.K., GlaxoSmithKline K.K., Kissei Pharmaceutical Co., Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd, Consultant of: MH is a consultant for AbbVie, Boehringer-ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co.,Ltd. and Teijin Pharma., Grant/research support from: MH has received research grants from AbbVie Japan GK, Asahi Kasei Corp., Astellas Pharma Inc., Ayumi Pharmaceutical Co., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Daiichi-Sankyo, Inc.,Eisai Co., Ltd., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Nippon Kayaku Co., Ltd., Sekiui Medical, Shionogi & Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd., Yanjie Hao: None declared, Zhuoli Zhang Speakers bureau: Norvatis, GSK, Pfizer, BMDB Basnayake: None declared, Madelynn Chan Speakers bureau: AbbVie, Novartis, Consultant of: Advisory Board member for Pfizer, Eli-Lilly, Jun Kikuchi: None declared, Tsutomu Takeuchi Speakers bureau: AbbVie AYUMI Pharmaceutical Corp. Bristol-Myers Squibb Chugai Pharmaceutical Co, Ltd. Daiichi Sankyo Co., Ltd. Eisai Co., Ltd. Eli Lilly Japan, Gilead Sciences, Inc. Mitsubishi-Tanabe Pharma Corp. Pfizer Japan Inc. Sanofi K.K., Consultant of: Astellas Pharma, Inc. Chugai Pharmaceutical Co, Ltd. Eli Lilly Japan, Mitsubishi-Tanabe Pharma Corp., Grant/research support from: AbbVie Asahikasei Pharma Corp. Chugai Pharmaceutical Co, Ltd. Mitsubishi-Tanabe Pharma Corp. Sanofi K.K, Sang-Cheol Bae: None declared, Sean O’Neill Paid instructor for: Advisory board member for GSK, Fiona Goldblatt: None declared, Shereen Oon: None declared, Kathryn Gibson Speakers bureau: UCB, Consultant of: Novartis – co-chair for NSW and steering committee member for ARISE meeting Feb 2021

Janssen Pharmaceuticals – advisory board, Grant/research support from: Novartis, Employee of: Eli Lilly, Kristine Ng Speakers bureau: speaker fees and advisory board (Abbvie, Novartis, Janssen), Annie Law: None declared, Nicola Tugnet: None declared, Sunil Kumar: None declared, Cherica Tee: None declared, Michael Tee: None declared, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, Grant/research support from: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, C.S. Lau Shareholder of: Pfizer, Sanofi and Janssen, Mandana Nikpour Speakers bureau: Actelion, GSK, Janssen, Pfizer, UCB, Paid instructor for: UCB, Consultant of: Actelion, Boehringer Ingelheim, Certa Therapeutics, Eli Lilly, GSK, Janssen, Pfizer, UCB, Grant/research support from: Actelion, Astra Zeneca, BMS, GSK, Janssen, UCB, Alberta Hoi Consultant of: AH is on the advisory board for Abbvie and GSK, Grant/research support from: AH has received research support from AstraZeneca, GSK, BMS, Janssen, and Merck Serono, Eric F. Morand Speakers bureau: AstraZeneca, Paid instructor for: Eli Lilly, Consultant of: AstraZeneca, Amgen, Biogen, BristolMyersSquibb, Eli Lilly, EMD Serono, Genentech, Janssen, Grant/research support from: AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, Janssen

POS0387 RISK STRATIFICATION APPROACHES PERFORM DIFFERENTLY IN SSc-ASSOCIATED PAH IN EUSTAR

Background

Pulmonary arterial hypertension (PAH) is a major clinical challenge in systemic sclerosis (SSc), and is associated with high mortality. Risk stratification provides an estimate for individual patient risk of 1-year mortality. The aim is to detect patients with the worst prognosis to optimize management strategies. Nine risk stratification approaches have been proposed in PAH, but have not been validated in SSc-PAH.

Objectives

To assess four risk stratification models and their performance to predict 1- and 3- year mortality and to identify the best risk assessment approach for SSc-PAH.

Methods

We included all patients with SSc diagnosed with PAH by right heart catheterization (RHC) from the European scleroderma trial and research (EUSTAR) database from 2001 to February 2021. PAH was defined as mean pulmonary arterial pressure (mPAP) ≥25 mmHg, pulmonary artery wedge pressure (PAWP) ≤15mmHg, and pulmonary vascular resistance (PVR) >3 Wood units (WU) in the absence of significant interstitial lung disease. We applied four different approaches for risk stratification at time of PAH diagnosis. Risk parameters included New York Heart Association (NYHA) class, 6-minute walk distance (6MWD), NT-proBNP or BNP, and echocardiographic and hemodynamic parameters with cut-off values based on the 2015 ESC/ERS Guidelines. Model 1 and 2 stratified patients into low, intermediate and high-risk categories; while Model 3 and 4 stratified the patients into four categories (low, intermediate-low, intermediate-high and high).

Model 1: Patients with ≥ 1 high-risk parameter were considered at high risk; with ≥ 1 intermediate-risk parameter at intermediate risk, otherwise at low risk1

Model 2: Each variable was graded from 1 to 3 representing low to high risk. The mean of available risk parameters was rounded to the nearest integer to define the risk category2

Model 3: Equals Model 2, but the intermediate risk group was divided into intermediate-low and intermediate-high based on the mean score3

Model 4: Stratifies patients into four risk categories based on the proportion of low-risk parameters3

We performed analysis of 1- and 3- year mortality in patients with a minimum follow-up of 1 and 3 years, respectively.

Results

Of 911 patients who conducted RHC, 273 (30%) were diagnosed with SSc-PAH according to the inclusion criteria (Table 1). Median follow-up time was 2.8 years (IQR 1.3-5.3). The models varied in their ability to predict mortality (Figure 1). Model 1 and 4 either over- or underestimated mortality. Model 2 stratified patients according to the expected 1-year mortality of <5%, 5-10% and >10% suggested by the ESC/ERS Guidelines. Model 3, which divided the intermediate risk group in two different risk groups, segregated the risk of mortality further within this group.

Table 1.

Demographic and clinical characteristics of patients segregated by risk stratification (Model 3)

NAll patients (n=273)Low-risk (n=78)Intermediate-low (n=118)Intermediate-high (n=56)High-risk (n=21)Age, years (SD)27365 (10.7)65 (10.3)65 (10.7)65 (10.8)67 (12.8)Female sex, n (%)273230 (84)64 (82)98 (83)48 (86)20 (95)lcSSc, n (%)263221 (84)60 (80)99 (86)47 (90)15 (71)NYHA 3 or 4, n (%)261155 (59)12 (16)75 (68)49 (89)19 (95)NT-proBNP, pg/ml (IQR)1111941 (230-1485)215 (103-377)763 (325-1418)1926 (1051-5681)3314 (1129-6553)6MWD, m (SD)196321 (124.1)404 (119.7)314 (99.9)262 (128.6)215 (96.0)RHC:- mPAP, mmHg (SD)27340 (11.0)35 (8.8)41 (11.5)41 (10.8)45 (11.6)- PAWP, mmHg (SD)2739 (3.2)9 (3.0)9 (3.4)9 (3.2)8 (3.1)- Cardiac index, l/min/m2(SD)2602.8 (0.8)3.2 (0.7)2.7 (0.8)2.6 (1.0)2.0 (0.5)- PVR, WU (SD)2737.4 (4.1)5.3 (2.8)7.9 (4.0)7.9 (4.2)11.3 (4.7)Figure 1.

1- and 3-year mortality according to risk category in the four different models

Conclusion

Model 3 provides signals for a better risk stratification of patients with newly diagnosed SSc-PAH, with progressively increasing mortality across the categories. This may provide guidance for optimized management in clinical practice.

References

[1]Hoffmann-Vold, Rheum 2018

[2]Kylhammar, Eur Heart J 2018

[3]Kylhammar, ERJ open 2021

Acknowledgements

The authors thank all EUSTAR collaborators.

Disclosure of Interests

Hilde Jenssen Bjørkekjær: None declared, Cosimo Bruni Speakers bureau: Actelion, Consultant of: Boehringer-Ingelheim, Patricia Carreira: None declared, Paolo Airò Speakers bureau: Boehringer Ingelheim, Bristol-Myers-Squibb, Consultant of: Bristol-Myers-Squibb, Grant/research support from: Bristol-Myers-Squibb, Roche, Janssen, CSL Behring, Carmen Pilar Simeón-Aznar Speakers bureau: Janssen, Boehringer Ingelheim and MSD, Consultant of: Janssen, Boehringer Ingelheim, Marie-Elise Truchetet: None declared, Alessandro Giollo: None declared, Alexandra Balbir-Gurman: None declared, Mickael Martin: None declared, Christopher P Denton Speakers bureau: Boehringer Ingelheim; Janssen, Consultant of: Boehringer Ingelheim; GSK; Corbus; Sanofi; Roche; Horizon; CSL Behring; Acceleron, Grant/research support from: CSL Behring; Horizon; GSK; Servier, Armando Gabrielli: None declared, Håvard Fretheim Consultant of: Bayer, GSK, Actelion, Imon Barua: None declared, Helle Bitter Speakers bureau: Boehringer Ingelheim, Øyvind Midtvedt: None declared, Kaspar Broch: None declared, Arne Andreassen: None declared, Yoshiya Tanaka Speakers bureau: Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Consultant of: Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie, Grant/research support from: Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, Gabriela Riemekasten: None declared, Ulf Müller-Ladner: None declared, Marco Matucci-Cerinic: None declared, Ivan Castellví: None declared, Elise Siegert: None declared, Eric Hachulla Speakers bureau: Johnson & Johnson, GlaxoSmithKline, Roche-Chugai, Consultant of: Bayer, Boehringer Ingelheim, GlaxoSmithKline, Johnson & Johnson, Roche-Chugai, Sanofi-Genzyme, Grant/research support from: CSL Behring, GlaxoSmithKline, Johnson & Johnson, Roche-Chugai, Sanofi-Genzyme, Oliver Distler Speakers bureau: Bayer, Boehringer Ingelheim, Janssen, Medscape, Consultant of: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, AstraZeneca, Baecon, Blade, Bayer, Boehringer Ingelheim, Corbus, CSL Behring, 4P Science, Galapagos, Glenmark, Horizon, Inventiva, Kymera, Lupin, Miltenyi Biotec, Mitsubishi Tanabe, MSD, Novartis, Prometheus, Roivant, Sanofi and Topadur, Grant/research support from: Kymera, Mitsubishi Tanabe, Boehringer Ingelheim, Anna-Maria Hoffmann-Vold Speakers bureau: Actelion, Boehringer Ingelheim, Jansen, Lilly, Medscape, Merck Sharp & Dohme, Roche, Consultant of: Actelion, ARXX, Bayer, Boehringer Ingelheim, Jansen, Lilly, Medscape, Merck Sharp & Dohme, Roche, Grant/research support from: Boehringer Ingelheim

OP0112 THE EVER-LARGEST ASIAN GWAS FOR SYSTEMIC SCLEROSIS AND TRANS-POPULATION META-ANALYSIS IDENTIFIED SEVEN NOVEL LOCI AND A CANDIDATE CAUSAL SNP IN A CIS-REGULATORY ELEMENT OF THE FCGR REGION

Background

Genome-wide association studies (GWASs) have identified 29 disease-associated single nucleotide polymorphisms (SNPs) for systemic sclerosis (SSc) in non-human leukocyte antigen (HLA) regions (1-7). While these GWASs have clarified genetic architectures of SSc, study subjects were mainly Caucasians limiting application of the findings to Asians.

Objectives

The study was conducted to identify novel causal variants for SSc specific to Japanese subjects as well as those shared with European population. We also aimed to clarify mechanistic effects of the variants on pathogenesis of SSc.

Methods

A total of 114,108 subjects comprising 1,499 cases and 112,609 controls were enrolled in the two-staged study leading to the ever-largest Asian GWAS for SSc. After applying a strict quality control both for genotype and samples, imputation was conducted using the reference panel of the phase 3v5 1,000 genome project data combined with a high-depth whole-genome sequence data of 3,256 Japanese subjects. We conducted logistic regression analyses and also combined the Japanese GWAS results with those of Europeans (6) by an inverse-variance fixed-effect model. Polygenicity and enrichment of functional annotations were evaluated by linkage disequilibrium score regression (LDSC), Haploreg and IMPACT programs. We also constructed polygenic risk score (PRS) to predict SSc development.

Results

We identified three (FCRLA-FCGR, TNFAIP3, PLD4) and four (EOMES, ESR1, SLC12A5, TPI1P2) novel loci in Japanese GWAS and a trans-population meta-analysis, respectively. One of Japanese novel risk SNPs, rs6697139, located within FCGR gene clusters had a strong effect size (OR 2.05, P=4.9×10-11). We also found the complete LD variant, rs10917688, was positioned in cis-regulatory element and binding motif for an immunomodulatory transcription factor IRF8 in B cells, another genome-wide significant locus in our trans-ethnic meta-analysis and the previous European GWAS. Notably, the association of risk allele of rs10917688 was significant only in the presence of the risk allele of the IRF8. Intriguingly, rs10917688 was annotated as one enhancer-related histone marks, H3K4me1, in B cells, implying that FCGR gene(s) in B cells may play an important role in the pathogenesis of SSc. Furhtermore, significant heritability enrichment of active histone marks and a transcription factor C-Myc were found in B cells both in European and Japanese populations by LDSC and IMPACT, highlighting a possibility of a shared disease mechanism where abnormal B-cell activation may be one of the key drivers for the disease development. Finally, PRS using effects sizes of European GWAS moderately fit in the development of Japanese SSc (AUC 0.593), paving a path to personalized medicine for SSc.

Conclusion

Our study identified seven novel susceptibility loci in SSc. Downstream analyses highlighted a novel disease mechanism of SSc where an interactive role of FCGR gene(s) and IRF8 may accelerate the disease development and B cells may play a key role on the pathogenesis of SSc.

References

[1]F. C. Arnett et al. Ann Rheum Dis, 2010.

[2]T. R. Radstake et al. Nat Genet, 2010.

[3]Y. Allanore et al. PLoS Genet, 2011.

[4]O. Gorlova et al. PLoS Genet, 2011.

[5]C. Terao et al. Ann Rheum Dis, 2017.

[6]E. López-Isac et al. Nat Commun, 2019.

[7]W. Pu et al. J Invest Dermatol, 2021.

Disclosure of Interests

None declared

POS0679 CLINICAL OUTCOMES UP TO WEEK (W) 48 IN THE ONGOING FILGOTINIB (FIL) LONG-TERM EXTENSION (LTE) TRIAL OF RHEUMATOID ARTHRITIS (RA) PATIENTS (pts) WITH INADEQUATE RESPONSE (IR) TO METHOTREXATE (MTX) INITIALLY TREATED WITH FIL OR ADALIMUMAB (ADA) DURING THE PHASE 3 PARENT STUDY (PS)

Background

The preferential Janus kinase-1 inhibitor FIL is approved for treatment of moderate to severe active RA in Europe and Japan.

Objectives

Efficacy and safety of FIL were assessed in pts with IR to MTX who completed a Phase 3 trial (NCT02889796)1 and enrolled in an LTE (NCT03025308).

Methods

Pts completing the PS1 on study drug were eligible to enter the LTE (data cutoff: June 1, 2020). Median exposure: 2.2 years (y). Efficacy data to W48 are reported for 4 treatment groups (all with background MTX): pts receiving FIL 200 mg (FIL200) or FIL 100 mg (FIL100) in the PS and continuing their dose in LTE (FIL200/FIL200, FIL100/FIL100) and ADA pts rerandomized, double blind, to FIL200 or FIL100 for LTE (ADA/FIL200, ADA/FIL100); safety data are reported.

Results

As of June 1, 2020, 522/571 (91%) FIL200/FIL200, 502/570 (88%) FIL100/FIL100, 118/128 (92%) ADA/FIL200, and 115/130 (89%) ADA/FIL100 pts remained on study drug. LTE baseline disease characteristics were similar between groups: mean duration of RA approximately 8.7 y; DAS28(CRP) 2.55, and mean concurrent MTX dosage was 15.0 mg/week. Proportions of pts achieving ACR20/50/70, DAS28(CRP) ≤3.2, <2.6, and CDAI ≤10, ≤2.8 were generally maintained in all LTE groups through W48 (Figure 1). Numerically greater proportions of pts met response criteria at W48 in the FIL200 groups vs FIL100, regardless of PS treatment. Treatment-emergent AEs (TEAE), serious AEs, and AEs Grade ≥3 were largely comparable between groups and lowest in ADA/FIL100. There were 10 deaths (Table 1). Exposure-adjusted incidence rates (EAIRs)/100 pt-y of exposure for deaths were lower for FIL/FIL vs ADA/FIL.

Table 1.

EAIRs of TEAEs in LTE, as of June 1, 2020

1TEAE, n (%)3FIL200+MTX → FIL200+MTX6ADA+MTX → FIL200+MTX9FIL100+MTX → FIL100+MTX12ADA+MTX → FIL100+MTX2EAIR (95% CI)4n=5717n=12810n=57013n=1305PYE=859.48PYE=197.811PYE=852.314PYE=192.6TEAE429 (75.1)91 (71.1)443 (77.7)88 (67.7)49.9 (45.4, 54.9)46.0 (37.5, 56.5)52.0 (47.4, 57.0)45.7 (37.1, 56.3)TEAE Grade ≥364 (11.2)15 (11.7)72 (12.6)7 (5.4)7.4 (5.8, 9.5)7.6 (4.6, 12.6)8.4 (6.7, 10.6)3.6 (1.7, 7.6)TE serious AE52 (9.1)13 (10.2)60 (10.5)9 (6.9)6.1 (4.6, 7.9)6.6 (3.8, 11.3)7.0 (5.5, 9.1)4.7 (2.4, 9.0)Death3 (0.5)2 (1.6)3 (0.5)2 (1.5)0.3 (0.1, 1.1)1.0 (0.3, 4.0)0.4 (0.1, 1.1)1.0 (0.3, 4.2)TE infections243 (42.6)52 (40.6)249 (43.7)43 (33.1)28.3 (24.9, 32.1)26.3 (20.0, 34.5)29.2 (25.8, 33.1)22.3 (16.6, 30.1)TE serious infections7 (1.2)2 (1.6)13 (2.3)1 (0.8)0.8 (0.4, 1.7)1.0 (0.3, 4.0)1.5 (0.9, 2.6)0.5 (0.1, 3.7)Opportunistic infections2 (0.4)02 (0.4)00.2 (0, 0.8)0 (0, 1.9)0.2 (0, 0.8)0 (0, 1.9)TE herpes zoster16 (2.8)5 (3.9)13 (2.3)1 (0.8)1.9 (1.1, 3.0)2.5 (1.1,6.1)1.5 (0.9, 2.6)0.5 (0.1, 3.7)TE MACE (adjudicated)1 (0.2)03 (0.5)3 (2.3)01 (0, 0.6)0 (0, 1.9)0.4 (0.1, 1.1)1.6 (0.5, 4.8)TE DVT/PE (adjudicated)3 (0.5)03 (0.5)00.3 (0.1, 1.0)0 (0, 1.9)0.4 (0.1, 1.0)0 (0, 1.9)Malignancies (excluding NMSC)5 (0.9)3 (2.3)4 (0.7)00.6 (0.2, 1.4)1.5 (0.5, 4.7)0.5 (0.1, 1.2)0 (0, 1.9)NMSC3 (0.5)02 (0.4)00.3 (0.1, 1.0)0 (0, 1.9)0.2 (0, 0.8)0 (0, 1.9)

DVT, deep vein thrombosis; MACE, major adverse cardiovascular event; NMSC, nonmelanoma skin cancer; PE, pulmonary embolism; TE, treatment-emergent

Figure 1.

Conclusion

During the LTE through W48, response rates generally were maintained for FIL/FIL and ADA/FIL pts. Though there were differences between LTE groups, safety was largely comparable and consistent with PS observations1 and previously reported results from 7 trials2: rates of AEs of special interest were low; all confidence intervals were overlapping. Limitation: the LTE was not formally randomized for comparison between FIL/FIL and ADA/FIL treatment groups, the groups were of unequal size, and the switch from ADA to FIL for LTE was by design, rather than based on disease activity.

References

[1]Combe B et al. Ann Rheum Dis 2021;80:848–58.

[2]Winthrop K et al. Arthritis Rheumatol 2020;72(suppl 10); abstract 0229.

Acknowledgements

This study was funded by Gilead Sciences, Inc., Foster City, CA. Medical writing support was provided by Claudine Bitel, PhD, of AlphaScientia, LLC, San Francisco, CA; and funded by Gilead Sciences, Inc., Foster City, CA.

Disclosure of Interests

Bernard Combe Speakers bureau: BMS, Eli Lilly & Co., Gilead Sciences, Inc., MSD, Pfizer, Roche-Chugai, and UCB, Consultant of: AbbVie, Eli Lilly & Co., Gilead Sciences, Inc., Janssen, Pfizer, Roche-Chugai, and Sanofi, Grant/research support from: Novartis, Pfizer, and Roche-Chugai, Yoshiya Tanaka Speakers bureau: AbbVie, Asahi-Kasei, Astellas, Bristol-Myers, Chugai, Daiichi- Sankyo, Eli Lilly, Eisai, Gilead, GSK, Janssen, Mitsubishi-Tanabe, Novartis, Pfizer, Sanofi, and YL Biologics, Consultant of: AbbVie, Ayumi, Daiichi- Sankyo, Eli Lilly, GSK, Sanofi, and Taisho, Grant/research support from: AbbVie, Asahi-Kasei, Chugai, Daiichi-Sankyo, Eisai, Mitsubishi-Tanabe, and Takeda, Paul Emery Consultant of: AbbVie, BMS, Celltrion, Gilead, Lilly, Novartis, Roche, Samsung, and Sandoz, Grant/research support from: AbbVie, BMS, Lilly, and Samsung, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Albert Kuo Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Qi Gong Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Katrien Van Beneden Shareholder of: Galapagos NV, Employee of: Galapagos NV, Vijay Rajendran Shareholder of: Galapagos NV, Employee of: Galapagos NV, Hendrik Schulze-Koops Speakers bureau: AbbVie, Amgen, BMS, Celgene, Celltrion, Chugai, Gilead, Janssen, Eli Lilly and Company, Merck Sharp & Dohme, Novartis-Sandoz, Pfizer, Roche, and Sanofi, Consultant of: AbbVie, Amgen, BMS, Celgene, Celltrion, Chugai, Gilead, Janssen, Eli Lilly and Company, Merck Sharp & Dohme, Novartis-Sandoz, Pfizer, Roche, and Sanofi, Grant/research support from: AbbVie and Novartis

POS0664 RADIOGRAPHIC CHANGE IN PATIENTS WITH RHEUMATOID ARTHRITIS AND ESTIMATED BASELINE YEARLY PROGRESSION ≥5 OR <5: POST HOC ANALYSIS OF TWO PHASE 3 TRIALS OF FILGOTINIB

Background

In some patients (pts) with rheumatoid arthritis (RA), especially those with joint damage early in the disease, first-line methotrexate (MTX) treatment may not suffice to prevent further rapid radiographic progression (RRP).1 In FINCH 1 (NCT02889796), filgotinib 200 mg (FIL200) and 100 mg (FIL100) reduced change in modified total Sharp score (mTSS) vs placebo (PBO) in pts with RA and inadequate response to MTX (MTX-IR).2 In FINCH 3 (NCT02886728), FIL200 and FIL100 reduced change in mTSS vs MTX monotherapy (MTX mono) in MTX-naïve pts.3

Objectives

To evaluate, via post hoc analysis of 2 trials, filgotinib’s effects on radiographic progression vs MTX mono in pts with estimated baseline (BL) yearly progression ≥5 or <5 mTSS units/year.

Methods

The double-blind 52-week (W) FINCH 1 study randomised MTX-IR pts with moderate–severe active RA to FIL200 or FIL100, subcutaneous adalimumab (ADA) 40 mg, or PBO; at W24, PBO pts were rerandomised blinded to FIL200 or FIL100; all took stable background MTX.2 In FINCH 3, MTX-naïve pts were randomised, blinded, to FIL200 + MTX, FIL100 + MTX, FIL200 alone, or MTX mono for up to W52.3 This analysis examined subgroups by estimated BL yearly progression (BL mTSS/duration in years of RA diagnosis), based on ≥5 or <5 mTSS units/year,4 a threshold commonly used to define RRP. We assessed effects of filgotinib vs ADA or PBO in mTSS change from BL (CFB) at W24/W52 (using a mixed model for repeated measures) and percentages with no W24 progression (mTSS change ≤0, ≤0.5, ≤smallest detectable change [SDC], using Fisher’s exact test).

Results

At BL, 558/1755 MTX-IR and 787/1249 MTX-naïve pts had BL estimated yearly progression ≥5. Median mTSS in pts with BL yearly progression ≥5 and <5 was 53.25 vs 5.00 respectively in the MTX-IR trial and 6.00 vs 2.50 in the MTX-naïve trial. At W24, the mTSS CFB in pts with BL yearly progression ≥5 and <5 was 0.84 and 0.22 in MTX-IR pts taking PBO + MTX, and 0.67 and 0.25 in MTX-naïve pts taking MTX mono. At W52, in pts with BL yearly progression ≥5, FIL200 + MTX reduced mTSS change vs PBO + MTX in the MTX-IR trial and vs MTX mono in the MTX-naïve trial (Figure 1). At W24, among pts with estimated BL yearly progression ≥5, FIL200 + MTX increased odds of no progression (≤0.5 or ≤0) vs PBO + MTX in MTX-IR pts and vs MTX mono in MTX-naïve pts (Table 1).

Table 1.

Ratio of no radiographic progression at W24

FINCH 1: MTX-IRFIL200 + MTXFIL100 + MTXADA + MTXPBO + MTXBL yearly progression≥5(n = 138)<5(n = 267)≥5(n = 139)<5(n = 265)≥5(n = 91)<5(n = 180)≥5(n = 101)<5(n = 250)% with no progression (≤0.5)87.797.088.592.587.993.976.291.6OR2.22*2.97*2.40*1.12††††% with no progression (≤0)80.491.881.388.380.289.467.386.4OR2.00*1.752.11*1.19††††% with no progression (≤SDC [1.36])91.398.192.196.692.395.681.294.0OR2.43*3.35*2.70*1.82††††FINCH 3: MTX-naïveFIL200 + MTXFIL100 + MTXFIL200 monoMTXBL yearly progression≥5<5≥5<5≥5<5≥5<5(n = 221)(n = 134)(n = 121)(n = 63)(n = 115)(n = 58)(n = 224)(n = 132)% with no progression (≤0.5)86.994.083.593.789.689.778.687.9OR1.81*2.171.382.032.34*1.20††% with no progression (≤0)78.783.672.784.180.087.967.980.3OR1.75*1.251.261.31.89*1.79††% with no progression (≤SDC [1.53])93.797.891.796.895.796.689.395.5OR1.772.081.331.452.641.33††

MTX-IR ORs are FIL vs PBO + MTX; MTX-naïve are FIL vs MTX. *Nominal P<.05. †Not applicable.

ADA, adalimumab; FIL, filgotinib; IR, inadequate response; mTSS, modified total Sharp score; MTX, methotrexate; OR, odds ratio; SDC, smallest detectable change; W, week.

Conclusion

These data suggest filgotinib’s inhibition of radiographic progression was numerically greater than MTX monotherapy in RA pts with high estimated BL yearly progression. In those with a more moderate estimated rate of progression, filgotinib suppressed progression comparably to ADA and/or MTX.

References

[1]Smolen J et al. Ann Rheum Dis 2018;77:1566–1572.

[2]Combe B et al. Ann Rheum Dis 2021;80:848–858.

[3]Westhovens R et al. Ann Rheum Dis 2021;80:727–738.

[4]Vastesaeger N et al. Rheumatology. 2009;48:1114–1121.

Acknowledgements

This study was funded by Gilead Sciences, Inc., Foster City, CA. Medical writing support was provided by Rob Coover, MPH, of AlphaScientia, LLC, San Francisco, CA; and funded by Gilead Sciences, Inc., Foster City, CA. Funding for this analysis was provided by Gilead Sciences, Inc. The sponsors participated in the planning, execution, and interpretation of the research.

Disclosure of Interests

Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, Behringer-Ingelheim, Bristol-Myers Squibb, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Tatsuya Atsumi Paid instructor for: Gilead Sciences, Inc.; Mitsubishi Tanabe; Chugai; Astellas Pharma; Takeda; Pfizer; AbbVie: Eisai; Daiichi Sankyo; Bristol-Myers Squibb; UCB Japan Co. Ltd.; Eli Lilly Japan K.K., Otsuka Pharmaceutical Co., Ltd.; and Alexion Inc., Grant/research support from: Gilead Sciences, Inc.; Mitsubishi Tanabe; Chugai; Astellas Pharma; Takeda; Pfizer; AbbVie: Eisai; Daiichi Sankyo; Bristol-Myers Squibb; UCB Japan Co. Ltd.; Eli Lilly Japan K.K., Otsuka Pharmaceutical Co., Ltd.; and Alexion Inc., Daniel Aletaha Speakers bureau: AbbVie; Amgen; Celgene; Eli Lilly; Medac; Merck; Novartis; Pfizer; Roche; Sandoz; and Sanofi/Genzyme; Bristol-Myers Squibb, Merck Sharp & Dohme, and UCB, Consultant of: Janssen; AbbVie; Amgen; Celgene; Eli Lilly; Medac; Merck; Novartis; Pfizer; Roche; Sandoz; and Sanofi/Genzyme, Grant/research support from: AbbVie, Merck Sharp & Dohme, Novartis, and Roche, Robert B.M. Landewé Paid instructor for: AbbVie, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Galapagos NV, Novartis, Pfizer, and UCB, Consultant of: AbbVie, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Galapagos NV, Novartis, Pfizer, and UCB, Beatrix Bartok Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Zhaoyu Yin Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Ling Han Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Kahaku Emoto Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences K.K., Shungo Kano Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences K.K., Vijay Rajendran Employee of: Galapagos BV, Tsutomu Takeuchi Speakers bureau: AbbVie, Ayumi Pharmaceutical Corporation, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Dainippon Sumitomo Eisai, Eli Lilly Japan, Mitsubishi-Tanabe, Novartis, Pfizer Japan, Sanofi, and Gilead Sciences, Inc., Consultant of: Astellas, Chugai, and Eli Lilly Japan, Grant/research support from: AbbVie, Asahi Kasei, Astellas, Chugai, Daiichi Sankyo, Eisai, Mitsubishi-Tanabe, Shionogi, Takeda, and UCB Japan

OP0255 BIMEKIZUMAB IN PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS AND AN INADEQUATE RESPONSE TO TUMOUR NECROSIS FACTOR INHIBITORS: 16-WEEK EFFICACY & SAFETY FROM BE COMPLETE, A PHASE 3, MULTICENTRE, RANDOMISED PLACEBO-CONTROLLED STUDY

Background

Bimekizumab (BKZ) is a monoclonal IgG1 antibody that selectively inhibits IL-17F in addition to IL-17A. BKZ has shown sustained efficacy and tolerability up to 152 wks in a phase 2b study in patients (pts) with active psoriatic arthritis (PsA).1,2

Objectives

To assess efficacy and safety of BKZ vs placebo (PBO) in pts with active PsA and prior inadequate tumour necrosis factor inhibitor (TNFi) response in the 16-wk pivotal phase 3 study, BE COMPLETE.

Methods

BE COMPLETE (NCT03896581) comprises a 16-wk double-blind, PBO-controlled period. Pts were aged ≥18 yrs, had a diagnosis of adult-onset, active PsA with ≥3 tender joints and ≥3 swollen joints, and inadequate response or intolerance to treatment with 1 or 2 TNFi. Pts were randomised 2:1 to BKZ 160 mg Q4W or PBO. From Wk 16, pts were eligible to enter an open-label extension, receiving BKZ 160 mg Q4W. The primary endpoint was a ≥50% improvement in American College of Rheumatology response criteria (ACR50) at Wk 16. Primary and ranked secondary efficacy endpoints were assessed at Wk 16.

Results

Of 400 randomised pts (BKZ: 267; PBO: 133), 388 (97.0%) completed Wk 16 (BKZ: 263 [98.5%]; PBO: 125 [94.0%]). Baseline characteristics were comparable between groups: mean age 50.5 yrs, weight 86.0 kg, BMI 29.8 kg/m2, time since diagnosis 9.5 yrs; 47.5% pts were male.

At Wk 16, the primary endpoint (ACR50: 43.4% BKZ vs 6.8% PBO; p<0.001; Figure 1) and all ranked secondary endpoints (HAQ-DI CfB, PASI90, SF-36 PCS CfB and MDA response) were met (all p<0.001; Table 1). The ACR50 response was rapid with separation from PBO observed from Wk 4 (nominal p<0.001). Additional outcomes, including ACR20/70, TJC and SJC CfB, and PASI75/100, demonstrated numerical improvement with BKZ compared to PBO at Wk 16 (all nominal p<0.001; Table 1).

Table 1.

Disease characteristics at baseline and efficacy at Wk 16

PBO N=133BKZ 160 mg Q4W N=267p valueBaseline characteristicsTJCmean (SD)19.3 (14.2)18.4 (13.5)-SJCmean (SD)10.3 (8.2)9.7 (7.5)-PtGA-PsAmean (SD)63.0 (22.0)60.5 (22.5)-PtAAPmean (SD)61.7 (24.6)58.3 (24.2)-Psoriasis BSAn (%)<3%45 (33.8)91 (34.1)-≥3 to ≤10%63 (47.4)109 (40.8)->10%25 (18.8)67 (25.1)-PASIamean (SD)8.5 (6.6)b10.1 (9.1)c-Prior TNFin (%)Inadequate response to 1 TNFi103 (77.4)204 (76.4)-Inadequate response to 2 TNFi15 (11.3)29 (10.9)-Intolerance to TNFi15 (11.3)34 (12.7)-Current cDMARDsn (%)63 (47.4)139 (52.1)-Ranked endpoints in hierarchical orderACR50* [NRI] n (%)9 (6.8)116 (43.4)<0.001HAQ-DI CfB† [RBMI] mean (SE)–0.1 (0.0)–0.4 (0.0)<0.001PASI90†a [NRI]n (%)6 (6.8)b121 (68.8)c<0.001SF-36 PCS CfB† [RBMI]mean (SE)1.4 (0.7)7.3 (0.5)<0.001MDA Response† [NRI]n (%)8 (6.0)118 (44.2)<0.001Other endpointsACR20† [NRI]n (%)21 (15.8)179 (67.0)<0.001‡ACR70† [NRI] n (%)1 (0.8)71 (26.6)<0.001‡TJC CfB [MI] mean (SE)–2.4 (0.9)–10.9 (0.8)<0.001‡SJC CfB [MI] mean (SE)–2.0 (0.5)–7.0 (0.4)<0.001‡PASI75a [NRI]n (%)9 (10.2)b145 (82.4)c<0.001‡PASI100a [NRI]n (%)4 (4.5)b103 (58.5)c<0.001‡

Randomised set (N=400). *Primary endpoint; †Secondary endpoint; ‡Nominal p value. aIn patients with ≥3% BSA with PSO at BL; bn=88; cn=176.

Over 16 wks, 107/267 (40.1%) pts on BKZ had ≥1 TEAE vs 44/132 (33.3%) pts on PBO; the three most frequent TEAEs on BKZ were nasopharyngitis (BKZ: 3.7%; PBO: 0.8%), oral candidiasis (BKZ: 2.6%; PBO: 0%) and upper respiratory tract infection (BKZ: 2.2%; PBO: 1.5%). Incidence of SAEs was low (BKZ: 1.9%; PBO: 0%); none led to discontinuation. 2 pts on BKZ discontinued due to a TEAE (BKZ: 0.7%; PBO: 0%). No systemic candidiasis, cases of IBD, MACE, uveitis, VTE or deaths were reported.

Conclusion

Dual inhibition of IL-17A and IL-17F with BKZ in pts with active PsA and prior inadequate TNFi response resulted in rapid, clinically relevant and statistically significant improvements in efficacy outcomes vs PBO. No new safety signals were observed.1,2

References

[1]Ritchlin C.T. Lancet 2020;395(10222):427–40; 2. Coates L.C. Ann Rheum Dis 2021;80:779–80(POS1022).

Acknowledgements

This study was funded by UCB Pharma. Editorial services were provided by Costello Medical.

Disclosure of Interests

Joseph F. Merola Paid instructor for: Amgen, Abbvie, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma and UCB Pharma, Consultant of: Amgen, Abbvie, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma and UCB Pharma, Iain McInnes Consultant of: AbbVie, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, Novartis, and UCB Pharma, Grant/research support from: BMS, Boehringer Ingelheim, Celgene, Janssen, UCB Pharma, Christopher T. Ritchlin Consultant of: Amgen, AbbVie, Eli Lilly, Gilead, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: AbbVie, Amgen and UCB Pharma, Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer and UCB Pharma, Consultant of: AbbVie, Amgen, BMS, Boehringer Ingelheim, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Grant/research support from: AbbVie, Amgen, BMS, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Robert B.M. Landewé Speakers bureau: Abbott, Amgen, BMS, Centocor, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Consultant of: Abbott, Ablynx, Amgen, AstraZeneca, BMS, Centocor, GSK, Novartis, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Grant/research support from: Abbott, Amgen, Centocor, Novartis, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Akihiko Asahina Grant/research support from: AbbVie, Amgen, Eisai, Eli Lilly, Janssen, Kyowa Kirin, LEO Pharma, Maruho, Mitsubishi Tanabe Pharma, Pfizer, Sun Pharma, Taiho Pharma, Torii Pharmaceutical, and UCB Pharma, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer-Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Consultant of: AbbVie, Ayumi, Daiichi-Sankyo, Eli Lilly, GSK, Sanofi, and Taisho, Grant/research support from: Asahi-Kasei, AbbVie, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Richard B. Warren Paid instructor for: Astellas, DiCE, GSK, and Union, Consultant of: AbbVie, Almirall, Amgen, Arena, Astellas, Avillion, Biogen, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, GSK, Janssen, LEO Pharma, Novartis, Pfizer, Sanofi, and UCB Pharma, Grant/research support from: AbbVie, Almirall, Janssen, LEO Pharma, Novartis, and UCB Pharma, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, and UCB Pharma, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, and Sandoz, Dafna D Gladman Consultant of: AbbVie, Amgen, BMS, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, and UCB Pharma, Frank Behrens Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Chugai, Eli Lilly, Genzyme, Janssen, MSD, Novartis, Pfizer, Roche, and Sanofi, Barbara Ink Shareholder of: GSK, UCB Pharma, Employee of: UCB Pharma, Deepak Assudani Shareholder of: UCB Pharma, Employee of: UCB Pharma, Rajan Bajracharya Shareholder of: UCB Pharma, Employee of: UCB Pharma, Jason Coarse Shareholder of: UCB Pharma, Employee of: UCB Pharma, Laura Coates Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer, and UCB Pharma, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, BMS, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB Pharma

[Successful R0 Resection of Hilar Cholangiocarcinoma Invading the Inferior Vena Cava through Left Trisegmentectomy with Combined Resection of the Portal Vein and Inferior Vena Cava after Gemcitabine/Cisplatin Combination Chemotherapy-A Case Report]

A 65-year-old woman was admitted to our institution with sonography results indicating a caudate lobe mass. CT showed a large low-density mass in the caudate lobe, extensively involving the inferior vena cava and main portal vein. Moderately differentiated adenocarcinoma was found on transcutaneous biopsy. We therefore regarded this tumor as a severe locally advanced hilar cholangiocarcinoma and initiated gemcitabine/cisplatin combined chemotherapy. The tumor gradually reduced in size. However, after 28 courses of treatment, CT showed persistent tumor invasion in the left trunk of the portal vein and inferior vena cava invasion in succession in the middle; the tumor had not yet invaded the left hepatic vein. Owing to myelosuppression and general malaise, it was difficult to continue chemotherapy. After 32 courses of treatment, the patient underwent a left trisegmentectomy with combined resection of the portal vein and inferior vena cava. Postoperative microscopic findings revealed no apparent invasion of the tumor in the inferior vena cava, thus suggesting successful R0 resection. The patient is alive without recurrence 18 months postoperatively.

Cutaneous ischemia-reperfusion injury is exacerbated by IL-36 receptor antagonist deficiency

BACKGROUND

Loss-of-function homozygous or compound heterozygous mutations in IL36RN, which encodes interleukin-36 receptor antagonist (IL-36Ra), has been implicated in the pathogenesis of skin disorders. However, the pathogenic role of IL-36Ra in cutaneous ischemia-reperfusion (I/R) injury remains unclear.

OBJECTIVES

We investigated the role of IL36Ra in cutaneous I/R injury.

METHODS

We examined I/R injury in Il36rn^-/- mice. The area of wounds, numbers of infiltrated cells, apoptotic cells and neutrophil extracellular trap (NET) formation were assessed. The expression levels of various genes were analysed using real-time RT-PCR. The expression of high mobility group box 1 (HMGB1), an endogenous toll-like receptor (TLR) 4 ligand, was confirmed using immunohistology, and serum HMGB1 levels were measured by ELISA. Cytokine production by stimulated cultured J774A.1 and HaCaT cells was examined.

RESULTS

IL-36Ra deficiency resulted in significantly delayed wound healing and increased neutrophil and macrophage infiltration into the wound tissues. Il36rn^-/- mice had increased mRNA expression levels of CXCL1, CXCL2, CCL4, TNF-α, TGF-β, IL-1β, IL-6 and IL-36γ relative to wild-type mice. Apoptosis was identified in keratinocytes by TUNEL assay. HMGB1 expression in the I/R site was decreased in both keratinocytes and adnexal cells, while serum HMGB1 levels were significantly elevated after reperfusion. The mRNA levels of various cytokines, including IL-1β, were elevated in J774A.1 cells through TLR4 signalling by HMGB1 stimulation. In addition, HaCaT cells stimulated with IL-1β showed significantly increased CXCL1, TNF-α, IL-6, IL-36β and IL-36γ mRNA expression. Furthermore, NET formation was increased by IL-36Ra deficiency. Finally, either the blockade of TLR4 signalling by TAK-242 or inhibition of NET formation by Cl-amidine normalized exacerbated I/R injury in Il36rn^-/- mice.

CONCLUSIONS

This study indicated that IL-36Ra deficiency exacerbates cutaneous I/R injury due to excessive inflammatory cell recruitment, NET formation, and excessive cytokine and chemokine production via the TLR4 pathway by HMGB1 released from epidermal apoptotic cells.

Long time psychological distress affected by the Great East Japan Earthquake after four years

Background

On March 11th, 2011, the Great East Japan Earthquake hit the Tohoku area, and more than 15,000 people lost their lives by the tsunami and earthquake. People who survived natural disasters, terrors, or serious diseases reported long-time psychological distress such as PTSD (Post Traumatic Stress Syndrome) or depression. This study aims to elaborate on factors associated with PTSD post the Great East Japan Earthquake after four years.

Methods

Quantitative and qualitative analysis from a questionnaire survey conducted after four years of the earthquake in 2015. The questionnaires included participants' attributes, IES-R scale to evaluate PTSD, loss of their families by tsunami and earthquake, their own tsunami experience, many relocations after the earthquake, lost job after the earthquake. The open-ended question asked them to write about their challenges in their lives and others.

Results

We received 3465 responses. Among those who responded, the IES-R scale was significantly larger in women (n = 1397) (aOR=1.55, p = 0.001) than men (n = 1966). Higher in those with more their own tsunami experience (aOR=1.35, p = 0.014), in those with lost loved ones (aOR=2.1, p &lt; 0.01), and in those with more economic difficulties (aOR=1.6, p &lt; 0.001). In addition, those with less social connectedness (aOR=1.34, p = 0.017) and forced to live separately with family members after the earthquake(aOR=1.36, p = 0.014) were significantly higher in the scale. From a quality analysis, we observed much psychological distress from participants.

Discussion and Conclusions

In this study, more than half in the PTSD risk group reported that they had never cared for mental pain after the earth quake. We overlook PTSD frequently. However, long-range monitoring and care are necessary for those affected by a significant disaster.

Key messages

PTSD after disasters have been overlooked frequently. A long-range monitoring and care are necessary after a significant disaster.

Mother's hesitancy of vaccinating their children in Japan – Text analysis survey

Background

the world is facing a novel coronavirus pandemic, and the role of vaccination and vaccination acceptance is playing an important role under current vaccination deployment. Japan's vaccination system has progressed these days greatly; however, the non-mandatory vaccination rate for children such as mumps, influenza is still low due to mothers' hesitancy. Given this circumstance, we conducted a qualitative analysis using text analysis methods for Japanese mothers with children about their hesitancy to vaccinate their children in Japan.

Methods

We used the data of a questionnaire survey first conducted in 2012, where two hundred and twenty-six mothers participated with an average age of 44.7 years (SD ± 5.02). The questionnaire included open-ended questions, where mothers wrote their opinion freely about vaccination about their children. We conducted text analysis focusing on the keywords of ‘hesitancy' (IBM SPSS Text Analytics for Surveys 4.0).

Results

The keywords that extracted frequently included; vaccination (n = 160), hesitancy (n = 66), difficulty in access to vaccination (n = 57), knowledge/information scarcity (n = 31), fear for side effect (n = 30), complexity of vaccination schedule (n = 23) and government subsidies (n = 20). The most related keyword with hesitancy was; side effect (n = 20), expensive cost (n = 12), and non-mandatory (n = 10). A keyword of having natural immunity was also closely connected (n = 8).

Discussion and Conclusions

To ameliorate hesitancy among mothers against vaccination of their children, local government notification and subsidy as mandatory vaccination, providing the correct information about diseases and side effects of vaccinations would work as plus factors.

Key messages

For pandemic preparedness, it is necessary to research vaccine acceptance among children.

This research is to explore vaccine hesitancy among mothers and factors related to their unwillingness.

URAT1-selective inhibition ameliorates insulin resistance by attenuating diet-induced hepatic steatosis and BAT whitening in mice

Background

Accumulating evidence suggests that high uric acid is strongly associated with obesity and metabolic syndrome and drives the development of non-alcoholic fatty liver disease (NAFLD) and insulin resistance. Although urate transporter-1 (URAT1), which is primarily expressed in the kidney, plays a critical role in the development of hyperuricemia, its pathophysiological implication in NAFLD and insulin resistance remains unclear.

Objectives

We hypothesizes that URAT1 plays an important role in obesity-induced metabolic disorders, and URAT1-selective inhibitor treatment ameliorates systemic insulin resistance, NAFLD and adipose tissue dysfunction using diet-induced obese mice.

Methods

Mice fed a high-fat diet (HFD) for 16 to 18 weeks or a normal-fat diet (NFD) were treated with or without a novel oral URAT1-selective inhibitor (dotinurad [50 mg/kg/day]) for another 4 weeks.

Results

Dotinurad administration significantly ameliorated HFD-induced obesity and insulin resistance. We found that URAT1 was also expressed in the liver and brown adipose tissue (BAT) other than kidney. HFD markedly induced NAFLD, which was characterized by severe hepatic steatosis, as well as the elevation of serum ALT activity and tissue inflammatory cytokine genes (Ccl2 and TNFα), all of which were attenuated by dotinurad. Likewise, HFD significantly increased URAT1 expression in BAT, resulting in the lipid accumulation (whitening of BAT) and increased production of tissue reactive oxygen species, which were reduced by dotinurad via UCP1 activation.

Conclusions

A novel URAT1-selective inhibitor, dotinurad, ameliorates insulin resistance by attenuating hepatic steatosis and promoting rebrowning of lipid-rich BAT in HFD-induced obese mice. URAT1 serves as a key regulator of the pathophysiology of metabolic syndrome, and may be a new therapeutic target for insulin-resistant individuals, particularly those with concomitant NAFLD.

Funding Acknowledgement

Type of funding sources: None.

Effects of an elemental diet to reduce adverse events in patients with esophageal cancer receiving docetaxel/cisplatin/5-fluorouracil: a phase III randomized controlled trial-EPOC 2 (JFMC49-1601-C5)

Background

Oral mucositis (OM) is an unpleasant adverse event in patients receiving chemotherapy. A prospective feasibility study showed that elemental diet (ED), an oral supplement that does not require digestion, may prevent OM. Based on this, we established a central review system for oral cavity assessment by dental oncology specialists blinded to background data. We used this system to elucidate the preventive effect of an ED against OM in patients with esophageal cancer receiving docetaxel, cisplatin, and 5-fluorouracil (DCF) therapy.

Patients and methods

In this phase III, multicenter, parallel-group, controlled trial, patients consuming a normal diet orally were randomly assigned (1 : 1) to receive two cycles of DCF with (group A) or without (group B) an ED (Elental® 160 g/day). We assessed the incidence of grade ≥2 OM evaluated by two reviewers, changes in body weight, prealbumin, C-reactive protein, and DCF completion rate based on ED compliance.

Results

Of the 117 patients randomly assigned to treatment, four failed to start treatment and were excluded from the primary analysis; thus, groups A and B comprised 55 and 58 patients, respectively. There were no significant differences in background characteristics. Grade ≥2 OM was observed in eight (15%) and 20 (34%) patients in groups A and B, respectively (P = 0.0141). Changes in body weight and prealbumin during the two DCF cycles were significantly higher in group A than B (P = 0.0022 and 0.0203, respectively). During the first cycle, changes in C-reactive protein were significantly lower in group A than B (P = 0.0338). In group A (receiving ED), the DCF completion rate was 100% in patients with 100% ED compliance and 70% in patients failing ED completion (P = 0.0046).

Conclusions

The study findings demonstrate that an ED can prevent OM in patients with esophageal cancer receiving chemotherapy.

•

Patients receiving docetaxel, cisplatin, and 5-fluorouracil (DCF) chemotherapy commonly develop oral mucositis (OM).

•

An elemental diet (ED) was able to prevent OM in patients with esophageal cancer receiving DCF.

•

Grade ≥2 OM was observed in 15% of patients receiving the ED versus 34% of those not receiving the ED (P = 0.0141).

•

Body weight was maintained in the ED group, and hematologic toxicities were lower, compared with the non-ED group.

•

The DCF completion rate significantly correlated with ED compliance (P = 0.0046).

P–678 Increased luteinizing hormone in ovarian dysfunction attenuates follicle development and oocyte quality in human

Study question

Can increased luteinizing hormone impair follicular development and oocyte quality in patients with ovarian dysfunction?

Summary answer

Increased luteinizing hormone attenuates follicular development and oocyte quality, resulting in arrest of follicle growth and empty follicles and low-quality embryos.

What is known already

Patients with ovarian dysfunction exhibit elevated gonadotropins and low estrogen levels reflecting their low ovarian reserve. For ovarian stimulation in these patients, natural or mild stimulation protocols are likely used, but we often experienced the arrest of follicle growth and empty follicles at oocyte retrieval. Animal studies demonstrated that chronic high LH exposure impaired the growth of antral follicles by suppressing the expression of FSHR in granulosa cells via a modulation of intraovarian regulators, including the LH-induced thecal factors. Study design, size, duration: Retrospective analysis was conducted in 72 patients with ovarian dysfunction who received ovarian stimulations followed by IVF-ET from April 2018 to March 2020 after obtaining written informed consents under an approval from the ethical committee of our hospital.

Participants/materials, setting, methods

The data of hormonal levels, transvaginal ultrasound during ovarian stimulation and clinical outcome of IVF were extracted from electric chart. For evaluation of embryo, high quality embryos referred to embryos having Veeck classification &gt;grade 3 and &gt;4 blastomeres. Statistical significance was determined using Dunnett or chi-square tests, with P &lt; 0.05 being statistically significant.

Main results and the role of chance

The median age of participants was 42 years of age (range 26–49) with low serum AMH levels (median 0.9 ng/ml, range 0–1.83). We analyzed 361 cycles of ovarian stimulation in total (median 4 cycles/patient, range 1–21). These stimulation cycles were classified into 3 groups; group A (n = 230): normal LH level, group B (n = 93): elevated LH level (&gt; 10 mIU/ml) after ovarian stimulation and group C (n = 33): elevated LH level from the initiation of ovarian stimulation. Among 361 cycles, the arrest of follicle growth was detected in 5 cycles (group A: 0%, group B: 60%, group C: 40%). The proportions of empty follicle in group A, B and C were 17.3±2.0%, 20.9±3.3%and 38.6±7.2%, respectively. The rate of empty follicle was significantly high in group C. Although there was no significant difference in the rates of oocyte degeneration and fertilization, the rate of high-quality embryos in group C was 0.8-fold lower than that of group A.

Limitations, reasons for caution

Due to limitation of participants, we could not determine the appropriate LH level for ovarian stimulation in patients with ovarian dysfunction based on receiver operatorating characteristic curve.

Wider implications of the findings: Normalization of LH levels for ovarian simulation in patients with ovarian dysfunction could improve follicle development and oocyte quality.

Trial registration number

Not applicable

POS0670 ROUTINE ASSESSMENT OF PATIENT INDEX DATA 3 (RAPID3) IN PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH LONG-TERM UPADACITINIB THERAPY

Background:

Routine Assessment of Patient Index Data 3 (RAPID3) is a pooled index of 3 patient-reported measures: patient global assessment, pain, and physical function. RAPID3 was shown to correlate with other composite measures of disease activity1 and is recommended by the American College of Rheumatology for use in clinical practice.2

Objectives:

To evaluate the impact of upadacitinib (UPA) versus comparators on RAPID3 over 60 weeks, as well as the correlation of RAPID3 scores with other disease measures in the UPA phase 3 SELECT clinical program.

Methods:

This post hoc analysis included placebo-controlled (SELECT-NEXT, -BEYOND, and -COMPARE) and active comparator-controlled (SELECT-EARLY, -MONOTHERAPY, and -COMPARE) trials. Patients received UPA as monotherapy or in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). Mean change from baseline in RAPID3 and the proportion of patients reporting RAPID3 remission (≤3), low (LDA, >3 to ≤6), moderate (MDA, >6 to ≤12), and high disease activity (HDA, >12) were assessed. Correlations between absolute scores for RAPID3 and Clinical Disease Activity Index (CDAI), Simplified Disease Activity Index (SDAI), and 28-joint Disease Activity Score with C-reactive protein (DAS28[CRP]) were assessed using Spearman correlation coefficients. All data are as observed.

Results:

A total of 661, 498, 648, 1629, and 945 patients were included from SELECT-NEXT, -BEYOND, -MONOTHERAPY, -COMPARE, and -EARLY. At baseline, the majority of patients across all studies were in RAPID3 HDA (mean baseline RAPID3 [across all studies], 17.2–19.2) (Table 1 and Figure 1). Improvements from baseline in RAPID3 were observed with UPA 15 mg and 30 mg through Week 60, with numerically greater improvements observed with UPA compared with active comparators (Table 1). Across studies, mean improvements in RAPID3 exceeded the minimal clinically important difference (MCID) with UPA and adalimumab (ADA) treatment (MCID=3.83). By Week 60, approximately one-half of UPA-treated patients were in RAPID3 remission or LDA, with only 10–25% remaining in HDA, except for the more refractory population in SELECT-BEYOND, in which ~38% of patients remained in HDA (Figure 1). RAPID3 scores moderately to strongly correlated with CDAI (ρ=0.69–0.83), SDAI (ρ=0.69–0.82), and DAS28(CRP) (ρ=0.58–0.77), across all studies, at Week 60 (all p<0.001).

Conclusion:

UPA, as monotherapy or in combination with csDMARDs, was associated with improvements in patient-reported disease activity, pain, and physical function, as assessed by RAPID3 over 60 weeks in the phase 3 SELECT clinical program. RAPID3 continues to be an important tool in clinical practice to assess disease activity, as it was shown to correlate to other disease activity measures and allows for rapid scoring.

References:

[1]Pincus T, et al. Arthritis Care Res (Hoboken) 2010;62:181–9.

[2]England BR, et al. Arthritis Care Res (Hoboken) 2019;71:1540–55.

[3]Ward MM, et al. J Rheumatol 2019;46:27–30.

Table 1.

Change from BL in RAPID3 at Week 60 (as observed)

Phase 3 studyGroupnaMean (SD) BL scoreMean (SD) change from BLbSELECT-EARLYc(MTX-naïve)MTX23618.5 (5.6)−9.6 (7.5)UPA 15 mg QD26918.9 (5.6)−12.0 (7.6)UPA 30 mg QD25318.2 (5.6)−13.4 (7.2)SELECT-NEXT(csDMARD-IR)UPA 15 mg QD17217.7 (5.1)−11.1 (7.3)UPA 30 mg QD17217.6 (5.3)−10.4 (6.8)SELECT-MONOTHERAPY(MTX-IR)UPA 15 mg QD17217.4 (5.8)−9.6 (7.4)UPA 30 mg QD18017.2 (5.9)−10.6 (7.2)SELECT-COMPAREc(MTX-IR)UPA 15 mg QD55218.5 (5.5)−10.2 (7.1)ADA 40 mg EOW26418.7 (5.4)−8.8 (6.7)SELECT-BEYOND(bDMARD-IR)UPA 15 mg QD13319.2 (5.1)−8.6 (6.8)UPA 30 mg QD11818.5 (5.3)−9.3 (7.3)

b, biologic; BL, baseline; EOW, every other week; IR, inadequate response; MTX, methotrexate; QD, once daily; SD, standard deviation

aNumber of patients with RAPID3 values at both BL and Week 60. bNegative values indicate improvement from BL. cObserved data include patients rescued to UPA and/or ADA; treatment effect may include both the randomized and switch treatments in these patients

Acknowledgements:

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. No honoraria or payments were made for authorship. Medical writing support was provided by Grant Kirkpatrick, MSc, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests:

Martin Bergman Shareholder of: Johnson & Johnson, Speakers bureau: AbbVie, Celgene, GSK, MSD, Novartis, Pfizer, and Sanofi/Regeneron, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Genentech/Roche, Gilead, Horizon, Janssen, MSD, Novartis, Pfizer, Sandoz, Sanofi/Regeneron, and Scipher, Maya H Buch Consultant of: AbbVie, Eli Lilly, Merck-Serono, Pfizer, Sandoz, and Sanofi, Grant/research support from: Pfizer, Roche, and UCB, Yoshiya Tanaka Speakers bureau: AbbVie, Asahi Kasei, Astellas, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Eli Lilly, GSK, Janssen, Mitsubishi Tanabe, Novartis, Pfizer, Sanofi, Takeda, UCB, and YL Biologics, Grant/research support from: AbbVie, Astellas, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Mitsubishi Tanabe, MSD, Ono, Taisho Toyama, and Takeda, Gustavo Citera Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genzyme, Pfizer, and Roche, Sami Bahlas: None declared, Ernest Wong Consultant of: AbbVie, Chugai, Eli Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Chugai, Novartis, and UCB, Yanna Song Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Namita Tundia Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Jessica Suboticki Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Vibeke Strand Consultant of: AbbVie, Amgen, Arena, AstraZeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, Celltrion, Eli Lilly, Gilead, Ichnos, Inmedix, Janssen, Kiniksa, MSD, Myriad Genetics, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Scipher, Setpoint, and UCB.

POS0691 EFFECTS OF ANIFROLUMAB ON RENAL DISEASE IN PATIENTS WITH SLE

Background:

The type I interferon (IFN) receptor antibody anifrolumab has shown efficacy in patients with systemic lupus erythematosus (SLE) in the phase 3 TULIP-1 and TULIP-2 trials.1,2 Type I IFN dysregulation is associated with lupus nephritis (LN) pathogenesis.3

Objectives:

Pooled TULIP data were analyzed post hoc to assess baseline characteristics of patients with and without renal involvement and to evaluate the effects of anifrolumab on renal disease.

Methods:

TULIP-1 (NCT02446912) and TULIP-2 (NCT02446899) were randomized, placebo-controlled, 52-week trials of intravenous anifrolumab every 4 weeks in patients with moderate to severe SLE despite standard therapy, which excluded patients with severe active LN.1,2 Renal involvement at baseline was defined as any of the following: BILAG-2004 renal score A–C; SLEDAI-2K renal score >0; urine protein–creatinine ratio (UPCR) >0.5 mg/mg. Baseline characteristics were evaluated in patients with and without renal involvement, and the following endpoints were compared for the anifrolumab 300 mg and placebo groups: cumulative UPCR (area under the curve, AUC) through Week (W)52; percentage of patients with UPCR >0.5 mg/mg at baseline who improved to UPCR ≤0.5 mg/mg at W52; percentage of patients with renal flares (new BILAG-2004 A/B renal score vs prior visit); cumulative glucocorticoid (GC) use (AUC) through W52; and percentage changes in complement C3/C4 from baseline to W52.

Results:

Of the 726 patients in TULIP-1/-2 (anifrolumab, n=360; placebo, n=366), 99 had renal involvement at baseline (anifrolumab, n=45; placebo, n=54), 57 of whom had UPCR >0.5 mg/mg (anifrolumab, n=24; placebo, n=33). Patients with renal involvement vs without renal involvement had a lower mean age (37.8 vs 42.4 years) and were more likely to be male (14.1% vs 6.1%), Asian (16.2% vs 9.6%), IFN gene signature test–high (89.9% vs 81.5%), and anti-dsDNA positive (69.7% vs 40.4%); have a SLEDAI-2K score ≥10 (91.9% vs 68.4%); and be receiving GC ≥10 mg/day (67.7% vs 49.1%) or mycophenolate (26.3% vs 11.5%) at baseline. Among patients with baseline renal involvement, anifrolumab treatment was associated with a numerically greater improvement vs placebo in cumulative UPCR (AUC) through W52 (LS mean difference [SE]: –54.1 [54.26]) (Table 1). Numerically more patients improved from UPCR >0.5 mg/mg at baseline to ≤0.5 mg/mg at W52 with anifrolumab vs placebo (difference [SE], 4.9% [13.3]). Among all TULIP patients, fewer had ≥1 BILAG-2004 renal flare with anifrolumab vs placebo (5.0% vs 7.4%).4 Among patients with renal involvement, cumulative GC use (AUC) through W52 was lower with anifrolumab vs placebo (LS mean difference [SE]: –210.3 mg [332.6]) and there were numerically greater improvements in C3 and C4 from baseline to W52 (Table 1).

Conclusion:

TULIP data suggest renal benefit with anifrolumab in patients with SLE with mild/stable renal disease, supporting further investigation into anifrolumab’s efficacy in patients with active LN.

References:

[1]Furie R. Lancet Rheumatol. 2019;1:e208–19.

[2]Morand E. N Engl J Med. 2020;382:211–21.

[3]Feng X. Arthritis Rheum. 2006;54:2951–62.

[4]Furie R [abstract]. Arthritis Rheumatol. 2020;72(supp 10).

Table 1.

Renal Endpoints in TULIP-1 and TULIP-2

Endpoint (baseline to Week 52)PlaceboAnifrolumab 300 mgUPCR AUCan5445LS mean (SE)271.8 (54.8)217.7 (60.0)LS mean difference (SE), 95% CI−54.1 (54.3), −161.9, 53.6Improvement from >0.5 to ≤0.5 mg/mg UPCRbn3324Patients with improvement (%)36.341.2Difference, % (SE), 95% CI4.9 (13.3), −21.1, 30.9Glucocorticoid AUCan5445LS mean (SE)3524.5 (339.0)3314.2 (365.2)LS mean difference (SE), 95% CI−210.3 (332.6), −870.7, 450.1Change in C3/C4 (%)cC3N3121Mean (SE)20.3 (6.2)26.6 (5.0)C4N1914Mean (SE)29.1 (12.0)38.7 (13.8)

AUC, area under the curve; CI, confidence interval; LS, least squares; UPCR, urine protein–creatinine ratio; SE, standard error.

n, number satisfying baseline inclusion criteria for subgroup.

aPatients with baseline renal involvement; analysis of covariance.

bStratified Cochran–Mantel–Haenszel.

cPatients with renal involvement and abnormal C3/C4 at baseline.

Acknowledgements:

Writing assistance by Rosie Butler, PhD, of JK Associates Inc. part of Fishawack Health. This study was sponsored by AstraZeneca.

Disclosure of Interests:

Eric F. Morand Speakers bureau: AstraZeneca, Consultant of: AstraZeneca, Grant/research support from: AstraZeneca, Richard Furie Consultant of: AstraZeneca, Grant/research support from: AstraZeneca, Yoshiya Tanaka Speakers bureau: AbbVie, Asahi Kasei, Astellas, Bristol Myers Squibb, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, GSK, Janssen, Mitsubishi-Tanabe, Novartis, Pfizer, Sanofi, and YL Biologics, Grant/research support from: AbbVie, Chugai, Daiichi-Sankyo, Eisai, Mitsubishi-Tanabe, Takeda, and UCB, Tsutomu Takeuchi Speakers bureau: AbbVie GK., Bristol–Myers K.K., Chugai Pharmaceutical Co,. Ltd., Mitsubishi Tanabe Pharma Co., Pfizer Japan Inc., Astellas Pharma Inc, Daiichi Sankyo Co., Ltd., Eisai Co., Ltd., Sanofi K.K., Teijin Pharma Ltd., Takeda Pharmaceutical Co., Ltd., Novartis Pharma K.K., Consultant of: AstraZeneca K.K., Eli Lilly Japan K.K., Novartis Pharma K.K., Mitsubishi Tanabe Pharma Co., Abbvie GK, Nipponkayaku Co.Ltd, Janssen Pharmaceutical K.K., Astellas Pharma Inc,. Taiho Pharmaceutical Co., Ltd., Chugai Pharmaceutical Co, Ltd., Grant/research support from: Astellas Pharma Inc, Chugai Pharmaceutical Co, Ltd., Daiichi Sankyo Co., Ltd., Takeda Pharmaceutical Co., Ltd., AbbVie GK, Asahikasei Pharma Corp., Mitsubishi Tanabe Pharma Co., Pfizer Japan Inc., Eisai Co., Ltd., AYUMI Pharmaceutical Corporation, Nipponkayaku Co.Ltd., Novartis Pharma K.K., Gabriel Abreu Employee of: AstraZeneca, Raj Tummala Employee of: AstraZeneca, Catharina Lindholm Employee of: AstraZeneca

POS0877 THE EFFECT OF PLATELET INHIBITORS ON DIGITAL ULCERS IN SYSTEMIC SCLEROSIS - A DERIVATION AND VALIDATION EUSTAR STUDY

Background:

Digital ulcers (DUs) affect half of the patients with systemic sclerosis (SSc) and can be complicated by gangrene and amputation. The direct involvement of platelets in the development of DUs has been suggested by in vitro studies, which encouraged physicians to consider platelet inhibitors as a therapeutic option in the management of DUs. However, until now, there is no clinical study to assess the efficacy of platelet inhibitors for DUs in SSc patients.

Objectives:

To demonstrate a possible relationship between treatment with platelet inhibitors and the occurrence of DUs at the next follow-up visit in patients with SSc.

Methods:

This study used prospectively collected data from the European Scleroderma Trials and Research group (EUSTAR) registry. Patients fulfilling the 2013 ACR/EULAR SSc classification criteria with complete longitudinal data on the presence of DUs and platelet inhibitors were included in the analysis. Multiple imputation using a random forest algorithm was implemented to handle missing values.

The dataset was split into a derivation and validation cohort. To investigate the response for the binary dependent variable of DUs, a generalized linear mixed model (GLMM) was developed in the derivation cohort and validated using ROC analysis and Brier scores to address discrimination and calibration, respectively.

Results:

Of 3,463 patients (2,961 in the derivation cohort, 722 in the validation cohort), 453 had current DUs at the baseline and 245 were exposed to platelet inhibitors (table 1).

Our GLMM revealed that the exposure to platelet inhibitors is associated with a reduced risk of DUs at the next follow up visit (OR = 0.33, 95% CI = [0.13 to 0.82]). Further factors associated with absence or presence of DUs at the next follow-up visit are shown in figure 1. This confirmed the previously identified risk factors for the presence of DUs, supporting the overall robustness and the validity of our model.

The performance was evaluated by ROC curve analysis and showed an AUC = 97.97% (95% CI = [96.93% to 97.67%]) for the derivation cohort and AUC = 77.3% (95% CI = [74.01% to 81.39%]) for the validation cohort, respectively, showing an acceptable discrimination. The Brier score was 0.05 in the derivation cohort and 0.07 in the validation cohort, suggesting a good calibration of the model.

Conclusion:

Our model, with acceptable discrimination and good calibration, suggests a positive treatment effect of platelet inhibitors on DUs in clinical practice.

Table 1.

Baseline characteristics of patients before imputation

CharacteristicsOverallDerivation setValidation setn3,4632,691772Age (median [IQR])56.00 [47.00, 66.00]56.00 [47.00, 65.00] 57.00 [48.00, 67.00]Disease duration (median [IQR]) 9.00 [4.00, 16.00] 9.00 [4.00, 16.00] 8.00 [4.00, 15.00]Disease subset = Limited cutaneous SSc (%) 1562 (65.2) 1164 (64.6) 398 (66.9)DUs (%): Current 453 (13.1) 378 (14.0) 75 (9.7)DUs (%): Never 1783 (51.5) 1326 (49.3) 457 (59.2)DUs (%): Previously 1227 (35.4) 987 (36.7) 240 (31.1)mRSS (median [IQR]) 5.00 [2.00, 11.00] 6.00 [2.00, 12.00] 4.00 [1.00, 11.00]Joint Contractures = Yes (%) 881 (26.8) 770 (29.4) 111 (16.5)LVEF (median [IQR])62.00 [60.00, 65.00]60.00 [60.00, 65.00] 65.00 [60.00, 67.00]Dyspnea NYHA III and IV (%)300 (9.5)214 (8.6)86 (12.7)Pulmonary hypertension = Yes (%) 244 (10.7) 200 (11.3) 44 (8.4)Lung fibrosis on HRCT = Yes (%) 685 (46.6) 600 (47.7) 85 (39.7)FVC % predicted (median [IQR])97.00 [82.00, 111.00]95.00 [81.00, 110.00]101.00 [85.00, 115.00]Serum creatinine mg/dl (median [IQR]) 0.70 [0.60, 0.90] 0.70 [0.60, 0.90] 0.70 [0.70, 0.90]Anti-Scl-70 positive = Yes (%) 1147 (33.1) 958 (35.6) 189 (24.5)CRP elevation = Yes (%) 639 (21.1) 490 (20.8) 149 (22.1)Platelet inhibitors therapy = Yes (%) 245 (7.1) 206 (7.7) 39 (5.1)Oral anti-coagulants therapy = Yes (%) 53 (1.5) 50 (1.9) 3 (0.4)

Disclosure of Interests:

None declared