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

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

POS0604 LONG TERM SAFETY AND TOLERABILITY WITH ETANERCEPT BIOSIMILAR (YLB113), RESULTS FROM A 2-YEAR OPEN LABEL EXTENSION STUDY (STUDY NO. YLB113-003)

Background:

Eligible subjects with moderate-to-severely active rheumatoid arthritis (RA) who completed a phase 3 double-blind comparative efficacy and safety study (Study No. YLB113-002; Yamanaka et al, 2019) of 50 mg etanercept biosimilar (YLB113) or etanercept reference product (RP) by subcutaneous administration with concomitant MTX treatment for 52 weeks, were enrolled in this open label extension (OLE) study (Study No. YLB113-003) to assess the long-term safety and tolerability of YLB113 through to 3 years.

Objectives:

This OLE study aimed to evaluate the long-term safety of YLB113 administration in subjects with RA who received RP or YLB113 in a phase 3 active comparator study. The main parameters assessed were safety and tolerability in terms of adverse events (AEs) and injection site reactions (ISRs), incidence of immunogenicity and efficacy as DAS28 improvement (disease activity score in 28 joints).

Methods:

Subjects received 50 mg of YLB113 subcutaneously once every 1 to 2 weeks. Safety was assessed by AEs after study drug administration, ISRs, physical examination findings, and immunogenicity. Efficacy (DAS28 score) was assessed at the time of transition to the OLE study (Week 0), and at weeks 12, 24, 48, 72, 96 and at the end of the study.

Results:

201 (Full analysis set [FAS]) subjects received the study drug and 184 subjects completed the study (91.5% completion rate). The average drug exposure in 94 subjects who continued to receive YLB113 and completed the study (94.0% completion rate) and 90 subjects who switched from RP to YLB113 and completed the study (89.1% completion rate) was 103 weeks providing the long-term drug exposure data of YLB113.

The CTCAE Grade of TEAEs and ADRs observed were Grade 2 or less in severity (with no Grade ≥3). The overall incidence of ISRs was 10.0% (20/201 subjects) 77 events. All the ISRs reported were Grade 1 except for one Grade 2.

An overview of the AEs experienced by the subjects is summarized in the Table 1.

Table 1.

Overview of Adverse events in OLE study

FASn (%)Number of eventsNumber of subjects201-Treatment emergent adverse events (TEAEs)188(93.5)975Adverse drug reactions (ADRs)82(40.8)221Serious adverse events (SAEs)21(10.4)27Serious adverse drug reactions (SADRs)7(3.5)7AEs leading to premature study discontinuation4(2.0)6ADRs leading to premature study discontinuation3(1.5)4SAEs leading to premature study discontinuation3(1.5)4SADRs leading to premature study discontinuation2(1.0)2

n - number of subjects with at least 1 AE in the category

The mean DAS28 (mean ± S.D.) of 2.22 ± 0.95 at the study transition was 2.10 ± 0.91 at Week 72 and 2.06 ± 0.89 at the end of the study. It was confirmed that DAS28 slightly decreased with time after the study transition and continued until the end of the study. The average DAS28 value remained low even with long-term administration of YLB113, suggesting that the effects of the study drug was sustained (Figure 1).

Figure 1.

DAS28 over time with YLB113 N: Number of subjects. * The administration period at the study completion differs for each subject, because the study transition time differs for each subject.

cts who tested positive for anti-drug antibodies (ADA) at least once in the OLE study were 1.0% (2/200 subjects). All ADA were transient and disappeared at study completion. Such transient ADA formation was reported in the phase 3 study as well. In the phase 3 study, ADA formation was more frequent in subjects who received RP at 24 weeks, but all subjects were negative in the OLE study after switching. Therefore, switching did not affect immunogenicity.

Conclusion:

The safety, efficacy and immunogenicity profile of YLB113 was maintained over the long-term through to 3 years. Switching from RP to YLB113 did not impact safety or immunogenicity.

References:

[1]Yamanaka H, Kamatani N, Tanaka Y, et al. A Comparative Study to Assess the Efficacy, Safety, and Immunogenicity of YLB113 and the Etanercept Reference Product for the Treatment of Patients with Rheumatoid Arthritis. Rheumatol Ther. 2020 Mar;7(1):149-163.

Disclosure of Interests:

Yamanaka Hisashi Speakers bureau: YL Biologics Ltd, Consultant of: YL Biologics Ltd, Yoshiya Tanaka Speakers bureau: Received 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, Janssen., Grant/research support from: Received research grants from Abbvie, Mitsubishi-Tanabe, Chugai, Asahi-Kasei, Eisai, Takeda, Daiichi-Sankyo., Toshihiko Hibino: None declared, Chirag Shah Shareholder of: Lupin LTD, Employee of: Lupin LTD, Dhananjay Bakhle Shareholder of: As part of Employee Stock Options Plan of Lupin LTD, Employee of: Lupin LTD, Dimitris Stefanidis Employee of: Sr. Director, Global Medical Affairs Lead, Immunology Biosimilars for Viatris GmbH

POS0336 PATTERNS OF LARGE-VESSEL LESIONS AND POOR TREATMENT OUTCOMES IN PATIENTS WITH LARGE-VESSEL GIANT CELL ARTERITIS

Background:

Giant cell arteritis (GCA) is characterized by cranial symptoms and large-vessel lesions (LVL) in the aorta or its branches. We retrospectively analyzed the Japanese patients newly diagnosed as GCA between 2007 and 2014, and subsequently treated with glucocorticoid (GC). The imaging studies revealed that LVLs were observed in approximately half of the GCA patients, and the LVLs were significantly associated with the increased probability of poor treatment outcomes (1).

Objectives:

The objective of this study is to evaluate whether the distribution of LVLs of GCA was associated with poor treatment response.

Methods:

In a retrospective, multi-centric, nationwide registry of GCA patients treated with GCs between 2007 and 2014, 68 newly-diagnosed GCA with LVLs by imaging were detected. All investigators were members of Japan Research Committee of the Ministry of Health, Labour, and Welfare for Intractable Vasculitis (JPVAS). Poor treatment outcomes (non-achievement of clinical remission by week 24 or relapse during 104 weeks) were primarily evaluated. Cumulative rates and median time to the first event were analyzed by the Kaplan-Meier method and the log-rank test. Associated factors with the outcomes were analyzed by using the Cox proportional hazard model.

Results:

The mean age was 70.5 years, and 70.6% were women. Twenty-seven (39.7%) of the 68 patients were diagnosed as having GCA by both positive temporal artery biopsy and positive imaging, and 41 (60.3%) by positive imaging. Aortic lesions were detected in 72.1% (group 2, n=49) of the 68 GCA patients with LVLs. Patients without aortic lesions were categorized into two phenotypes: large-vessel GCA with subclavian lesions (group 1, n=9) and atypical large-vessel GCA without subclavian lesions (group 3, n=10). Cranial lesions were observed in 66.7%, 55.1%, and 80.0% in the group 1, 2, and 3, respectively. The initial mean dose (SD) of prednisolone was 0.74 (0.26) mg/kg/day, and 20.6 % received methotrexate for remission induction therapy. Baseline dose of GCs and mean time to achievement of low-dose GCs (prednisolone ≤ 5 mg/day) was not significantly different among the three groups.

Overall, 35 (51.5%) of the 68 patients had the event of poor treatment outcomes. Eleven patients were not able to achieve clinical remission by week 24. Relapse after achievement of clinical remission was reported in total of 24 patients; 9 between week 0 and 24, 12 between week 24 and 52, 3 between week 52 and 104. The cumulative rate of events of poor treatment outcomes over the two years was 11.1% in patients with group 1, 55.3% in those with group 2, and 88.0% in those with group 3. Mean time to events was significantly different among the three groups. Multivariable analysis showed the risk of poor treatment outcomes was likely to decrease in the group 1 (hazard ratio 0.14 [95% CI 0.02-1.03], p=0.054), while it increased in the group 3 (hazard ratio 2.22 [95% CI 1.06-4.68], p=0.035).

Conclusion:

The distribution of LVLs were associated with poorer treatment outcomes. A half of the patients with aortic lesions had poor treatment outcomes while subclavian arteritis without aortic lesions had better clinical outcomes. Atypical large vessel-GCA without the aortic and subclavian artery involvement was the worst prognostic phenotype of LV-GCA. Extent of LVLs by imaging should be considered when determining the treatment strategy for GCA.

References:

[1]Sugihara T, et al. Arthritis Res Ther. 2020;22(1):72

Acknowledgements:

The authors would like to acknowledge Mitsuaki Isobe (Sakakibara Heart Institute), Yoshihiro Arimura (Kichijoji Asahi Hospital), and all the investigators in the Japan Research Committee of the Ministry of Health, Labour, and Welfare for Intractable Vasculitis (JPVAS). In addition to the authors, the following investigators and institutions participated in this study: Department of Internal Medicine, Juntendo University Koshigaya Hospital (Shigeto Kobayashi); Niigata Rheumatic Center (Satoshi Ito); Niigata Prefectural Shibata Hospital (Noriyuki Homma).

Disclosure of Interests:

takahiko sugihara Speakers bureau: TS has received honoraria from Abbvie Japan Co., Ltd., AsahiKASEI Co., Ltd., Astellas Pharma Inc., Ayumi Pharmaceutical, Bristol Myers Squibb K.K., Chugai Pharmaceutical Co., Ltd., Eli Lilly Japan K.K., Mitsubishi-Tanabe Pharma Co., Ono Pharmaceutical, Pfizer Japan Inc., Takeda Pharmaceutical Co. Ltd., and UCB Japan Co. Ltd., Grant/research support from: TS has received research grants from AsahiKASEI Co., Ltd., Daiichi Sankyo., and Ono Pharmaceutical., Haruhito A. Uchida Grant/research support from: HAU belongs to the Department of Chronic Kidney

Disease and Cardiovascular Disease which is endowed by Chugai Pharmaceutical, MSD, Boehringer Ingelheim, and Kawanishi Holdings., Hajime Yoshifuji Speakers bureau: HY has received lecture fees from Chugai Pharmaceutical Co., Ltd. and Nihon Medi-Physics Co., Ltd., Yasuhiro Maejima Speakers bureau: YM have received honoraria from Chugai Pharmaceutical Co., Ltd.., Taio Naniwa Speakers bureau: TN has received lecture fees from Chugai Pharmaceutical Co., Ltd.., Grant/research support from: TN has received research grants from Chugai Pharmaceutical Co., Ltd.., Yasuhiro Katsumata Speakers bureau: YK has received honoraria from Chugai Pharmaceutical Co., Ltd., Glaxo-Smithkline K.K., Sanofi K.K., Pfizer Japan Inc., and Asahi Kasei Pharma Corp., Takahiro Okazaki Grant/research support from: TO has received research grants from Chugai Pharmaceutical Co., Ltd., Eisai Pharmaceutical., and Actelion, Jun Ishizaki: None declared, Yohko Murakawa Speakers bureau: YM has received honoraria from Abbvie, Astellas, Ayumi Pharmaceutical, Bristol Myers Squibb, Chugai Pharmaceutical, Eisai Pharmaceutical, Janssen Pharmaceutical, Kissei Pharmaceutical, Nippon Kayaku, Pfizer Pharmaceutical, Takeda Pharmaceutical, UCB Pharmaceutical, Grant/research support from: YM has received research grant support from Asahi Kasei Pharma, AbbVie Japan, Chugai Pharmaceutical, Daiichi Sankyo, Eisai Pharmaceutical, Mitsubishi Tanabe Pharma, Nippon Kayaku, Gilead Sciences Inc, Janssen Pharmaceutical, and Teijin Pharma., Noriyoshi Ogawa: None declared, Hiroaki Dobashi: None declared, Tetsuya Horita: None declared, Yoshiya Tanaka Speakers bureau: YT has received consulting fees, speaking fees, and/or honoraria from Daiichi-Sankyo, Astellas, Pfizer, Mitsubishi-Tanabe, Bristol-Myers, Chugai, YL Biologics, Eli Lilly, Sanofi, Janssen, UCB, Grant/research support from: YT has received research grants from Mitsubishi-Tanabe, Takeda, Bristol-Myers, Chugai, Astellas, Abbvie, MSD, Daiichi-Sankyo, Pfizer, Kyowa- Kirin, Eisai, Ono., Shunsuke Furuta: None declared, Tsutomu Takeuchi Speakers bureau: TT has served on speakers’ fees for AbbVie, Bristol-Myers Squibb, Chugai, Mitsubishi Tanabe, Pfizer, Astellas, Daiichi Sankyo, Eisai, Sanofi, Teijin, Takeda, and Novartis., Consultant of: TT has received consulting fees from Astra Zeneca, Eli Lilly, Novartis, Mitsubishi Tanabe, AbbVie, Nippon Kayaku, Janssen, Astellas, Taiho, Chugai, Taisho Toyama, GlaxoSmithKline, and UCB., Grant/research support from: TT has received research grants from Astellas, Chugai, Daiichi Sankyo, Takeda, AbbVie, Asahi Kasei, Mitsubishi Tanabe, Pfizer, Eisai, AYUMI, Nippon Kayaku, and Novartis., Yoshinori Komagata Speakers bureau: YK has received speakers’ fees from Bristol-Myers Squibb, Eli Lilly, Janssen, Novartis, Daiichi Sankyo, AbbVie, Nippon Shinyaku, Towa., Consultant of: YK has received consulting fees from Chugai, Kyowa Hakko Kirin, Asahi Kasei, UCB, Yoshikazu Nakaoka Speakers bureau: YN has received lecture fees from Astellas, Takeda, Daiichi Sankyo, Actelion, and Japan Blood Products Organization (JB)., Consultant of: YN has received consulting fees and/or lecture fees from AbbVie and Chugai, Grant/research support from: YN has received research grants from Chugai and Bayer Yakuhin, Ltd, 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.

POS0087 LONG-TERM SAFETY AND EFFICACY OF UPADACITINIB OR ADALIMUMAB IN PATIENTS WITH RHEUMATOID ARTHRITIS: RESULTS AT 3 YEARS FROM THE SELECT-COMPARE STUDY

Background:

In the SELECT-COMPARE study, the Janus kinase inhibitor, upadacitinib (UPA), demonstrated significant improvements in the signs and symptoms of rheumatoid arthritis (RA) when administered at 15 mg once daily (QD) on background methotrexate (MTX) compared with adalimumab (ADA) plus MTX at Week 12 that were maintained through 72 weeks in patients with prior inadequate response to MTX.1

Objectives:

To assess the long-term safety and efficacy of UPA vs ADA over 3 years in the ongoing long-term extension (LTE).

Methods:

Patients receiving background MTX were randomized 2:2:1 to UPA 15 mg QD, placebo (PBO), or ADA 40 mg every other week. Between Weeks 14-26, rescue was mandated for either lack of response (<20% improvement in tender or swollen joint counts: Weeks 14, 18, 22) or failure to achieve a targeted disease outcome (CDAI low disease activity: Week 26). Patients who completed the 48-week double-blind period could enter an LTE for up to 10 years total. This analysis describes patients through 3 years of treatment. Treatment-emergent adverse events (TEAEs) per 100 patient years (PY), including events of special interest (AESI), were summarized up to 3 years based on exposure to UPA and to ADA. Efficacy was analyzed by original randomized groups. Patients who were rescued or prematurely discontinued study drug were categorized as non-responders for visits after rescue or discontinuation. Descriptive analyses were performed without formal statistical comparisons.

Results:

In total, 651, 651, and 327 patients were randomized at baseline to receive UPA, PBO, and ADA, respectively. Between Weeks 14-26, 252 (39%) patients were rescued from UPA to ADA, 159 (49%) were rescued from ADA to UPA, and all PBO patients were switched to UPA by Week 26.1 A higher proportion of patients randomized to UPA completed 3 years without rescue compared to those randomized to ADA (47% vs 36%, respectively). UPA was generally well-tolerated as assessed by the rates of TEAEs, including serious AEs, AEs leading to discontinuation of study drug, and AESIs, including serious and opportunistic infections, malignancies, adjudicated major adverse cardiac events or venous thromboembolism; Figure 1). Consistent with previous analyses, the event rates of AESIs were generally comparable between the UPA and ADA groups, while herpes zoster, lymphopenia, hepatic disorder, and CPK elevation were reported at higher rates with UPA. Consistent with earlier time points, greater proportions of patients randomized to UPA achieved low disease activity and remission at 3 years based on CDAI, as well as DAS28(CRP) ≤3.2 or <2.6, compared with patients randomized to ADA (Table 1).

Conclusion:

The safety profile of UPA was consistent with the results reported previously and with the integrated Phase 3 safety analysis.1,2 Higher levels of clinical response continued to be observed with UPA vs ADA through 3 years of treatment.

References:

[1]Fleischmann R, et al. Ann Rheum Dis 2020;79:323.

[2]Cohen SB, et al. Ann Rheum Dis 2020; doi: 10.1136/annrheumdis-2020-218510.

Table 1.

Efficacy Endpoints at 3 Years (NRI)

Endpoints, % (95% CI)UPA 15 mg QDN=651*ADA 40 mg EOWN=327*CDAI ≤1039 (36, 43)29 (24, 34)CDAI ≤2.824 (21, 28)17 (12, 21)DAS28(CRP) ≤3.237 (33, 41)26 (21, 31)DAS28(CRP) <2.632 (29, 36)22 (17, 26)

ADA, adalimumab; CI, confidence interval; DAS28(CRP), Disease Activity Score for 28-joints C-Reactive Protein; CDAI, clinical disease activity index; EOW, every other week; NRI, non-responder imputation; QD, once daily; UPA, upadacitinib.

*Patients who were rescued prior to/at Week 26 were considered non-responders. 252/651 and 159/327 patients were rescued of those randomized to UPA and ADA, respectively.

Acknowledgements:

AbbVie and the authors thank the patients, trial sites, and investigators who participated in this clinical trial. AbbVie, Inc was the trial sponsor, contributed to trial design, data collection, analysis & interpretation, and to writing, reviewing, and approval of final version. No honoraria or payments were made for authorship. The authors thank Dr. Tim Shaw of AbbVie Inc. for his support with the interpretation of the data. Medical writing support was provided by Ramona Vladea, PhD, of AbbVie, Inc.

Disclosure of Interests:

Roy Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, and UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Genentech, Janssen, Novartis, Pfizer Inc, Regeneron, Roche, Sanofi-Aventis and UCB, Eduardo Mysler Consultant of: AbbVie, AstraZeneca, Lilly, Pfizer, Roche, BMS, Sandoz, GSK, Janssen, Grant/research support from: AbbVie, AstraZeneca, Lilly, Pfizer, Roche, BMS, Sandoz, GSK, Janssen, Louis Bessette Consultant of: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Gilead, Grant/research support from: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Gilead, Charles Peterfy Shareholder of: Spire Sciences, Inc, Speakers bureau: Amgen, Bristol-Myers Squibb, Consultant of: Aclaris, Centrexion, Daiichi Sankyo, EMD, Serono, Five Prime, Flexion Therapeutics, Genentech, Gilead, GlaxoSmithKline, Istresso, Eli Lilly, Myriad Genetics, Novartis, Roche, SetPoint, Sorrento, UCB, Employee of: Spire Sciences, Inc, Patrick Durez Speakers bureau: BMS, Sanofi, Eli Lilly, Celltrion, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Astellas, Chugai, Eli Lilly, Pfizer, AbbVie, YL Biologics, Bristol-Myers, Takeda, Mitsubishi-Tanabe, Novartis, Eisai, Janssen, Teijin, Consultant of: Daiichi-Sankyo, Astellas, Chugai, Eli Lilly, Pfizer, AbbVie, YL Biologics, Bristol-Myers, Takeda, Mitsubishi-Tanabe, Novartis, Eisai, Janssen, Teijin, Grant/research support from: Asahi-kasei, Mitsubishi-Tanabe, Chugai, Takeda, Sanofi, Bristol-Myers, UCB, Daiichi-Sankyo, Eisai, Ono, Jerzy Swierkot Speakers bureau: AbbVie, Sandoz, Pfizer, Roche, BMS, UCB, MSD, Accord, Janssen, Consultant of: AbbVie, Sandoz, Pfizer, Roche, BMS, UCB, MSD, Accord, Janssen, Grant/research support from: AbbVie, Sandoz, Pfizer, Roche, BMS, UCB, MSD, Accord, Janssen, Nasser Khan Shareholder of: AbbVie, Employee of: AbbVie, Xianwei Bu Shareholder of: AbbVie, Employee of: AbbVie, Yihan Li Shareholder of: AbbVie, Employee of: AbbVie, In-Ho Song Shareholder of: AbbVie, Employee of: AbbVie.

AB0132 THE STUDY OF SUBCLINICAL SYNOVITIS DETECTED BY ULTRASONOGRAPHY AND MRI IN RA PATIENTS AFTER REACHING CLINICAL REMISSION ON PATIENT’S SUBJECTIVE SYMPTOMS

Background:

The goal of treatment in rheumatoid arthritis (RA) is to achieve remission. There is the patient with residual symptoms in the Japanese RA patient who achieved clinical remission. There are not many studies to examine the relation between everyday life, social activity and evaluation of disease activities using high-sensitivity image examinations (musculoskeletal ultrasound (MSKUS) and MRI).

Objectives:

To examine the relationship between subjective residual symptoms and imaging examinations in RA patients who have achieved clinical remission.

Methods:

30 RA patients who achieved SDAI remission during RA treatment. Age, sex, disease duration, physical findings, serological markers, disease activity, HAQ, EQ-5D-5L, FACIT-F, Patient Reported Outcomes (PROs), EGA and medications were evaluated. 44 joints were assessed by MSKUS with gray scale (GS) and power doppler (PD) and contrast-enhanced bilateral joint MRI scoring with OMERACT-RAMRIS scoring.

Results:

1. The mean SDAI of the 30 RA patients was 1.3. 2.In the analysis of the presence or absence of subjective residual symptoms that led to remission of SDAI (Table 1).

Table 1.Subjective residual symptoms/presence (N=17)Subjective residual symptoms/absence (N=13)Univariate analysisp valueMultivariate logistic analysisp valueTJC0.0±0.00.3±0.50.0173HAQ0.4±0.40.05±0.10.00950.00181EQ5D-5L0.8±0.10.9±0.00.0001FACIT-F14.5±9.84.6±4.30.0233Morning stiffness (min)256.5±564.80.0±0.00.0210Pain (VAS) (mm)9.2±9.50.9±1.50.00440.0455PGA (mm)7.7±9.00.5±1.10.0013

(1). In the univariate analysis, the number of tender joints, HAQ, EQ-5D-5L, FACIT-F, morning stiffness, and pain VAS were extracted with significant differences.

(2). In multivariate logistic analysis, HAQ and pain VAS were extracted as independent factors with significant differences. 3.In univariate analysis of the association between HAQ and pain VAS extracted in multivariate logistic analysis and imaging examinations (MSKUS/MRI), MRI-synovitis was extracted with a significant difference in HAQ.

Conclusion:

1. It was suggested that Pain VAS and HAQ due to RA could be identified in patients reaching SDAI remission. 2. In patients reaching SDAI remission, Pain VAS ≤10 or HAQ ≤0.5 suggested that subjective residual symptoms may be eliminated. 3. HAQ ≤ 0.5 suggests that synovitis is less likely to be detected on MRI. 4. In patients who have reached SDAI remission, little residual inflammation was observed on US, suggesting that induction of remission is important not only to prevent joint destruction, but also to improve and maintain long-term QoL.

Disclosure of Interests:

MASAO NAWATA Grant/research support from: I have received research funding from Eli Lilly Japan K.K., Kazuki Someya: None declared, Takafumi Aritomi: None declared, Masashi funada: None declared, Katsumi Nakamura: None declared, SAITO KAZUYOSHI Grant/research support from: I have received research funding from Eli Lilly Japan K.K., Yoshiya Tanaka Speakers bureau: I have received speaking fees from Abbvie, Daiichi-Sankyo, Chugai, Takeda, Mitsubishi-Tanabe, Bristol-Myers, Astellas, Eisai, Janssen, Pfizer, Asahi-kasei, Eli Lilly, GlaxoSmithKline, UCB, Teijin, MSD, and Santen, Consultant of: I have received consulting fees from Abbvie, Daiichi-Sankyo, Chugai, Takeda, Mitsubishi-Tanabe, Bristol-Myers, Astellas, Eisai, Janssen, Pfizer, Asahi-kasei, Eli Lilly, GlaxoSmithKline, UCB, Teijin, MSD, and Santen, Grant/research support from: I have received research grants from Mitsubishi-Tanabe, Takeda, Chugai, Astellas, Eisai, Taisho-Toyama, Kyowa-Kirin, Abbvie, and Bristol-Myers

POS0028 DEFINING THE PREVALENCE OF UNMET NEED IN SLE: DATA FROM A LARGE MULTINATIONAL LONGITUDINAL SLE COHORT

Background:

The recent prospectively validated definition of the lupus low disease activity state (LLDAS) allows characterisation of patients not achieving a treatment goal, providing impetus for an analysis of unmet needs in SLE using formal definitions. Other recently described definitions of high disease burden include disease activity over time, high disease activity status (HDAS) episodes, and the combination of high disease activity, serological activity and glucocorticoid (GC) use (HDAS+SA+GC).

Objectives:

To determine the prevalence of formal categories of unmet need, and the association of these with adverse outcomes, in SLE.

Methods:

Data from a 13-country longitudinal SLE cohort (ACR/SLICC criteria) were collected between 2013 and 19 using standard templates. Unmet need was defined as (i) patients never attaining LLDAS defined as in Golder et al., 2019 [1], (ii) having persistently active disease (time adjusted mean SLEDAI-2K (AMS) > 4), (iii) ever exhibiting high disease activity status (HDAS; SLEDAI-2K ≥10[2]), or (iv) ever exhibiting all of SLEDAI≥10, serological activity, and glucocorticoid use (HDAS+SA+GC)[3]. Health-related quality of life (HRQoL) was assessed using SF36 (v2) surveys and damage accrual using SLE Damage Index (SDI).

Results:

3,384 SLE patients were followed for 30,313 visits over median [IQR] 2.4 [0.4, 4.3] years. 53% of all visits were not in LLDAS; 813 patients (24%) never achieved LLDAS during observation. Median AMS was 3.0 [1.4, 4.9] and 34% of patients had AMS > 4 throughout the study. 25% of patients had at least one episode of HDAS, representing 8% of visits. 702 patients (21%) had at least one episode of HDAS+SA+GC, representing 8% of visits. Each of never-LLDAS, AMS>4, ever-HDAS, and ever-HDAS+SA+GC were associated with significantly greater number of physician visits, higher mean glucocorticoid dose, lower HRQoL and higher mortality. 31%, 58% and 83% of never-LLDAS, AMS>4, and ever-HDAS patients respectively were also HDAS+SA+GC on at least one occasion.

Conclusion:

Data from a multinational longitudinal SLE cohort indicate that unmet need, defined by LLDAS-never, AMS>4, HDAS, or HDAS+SA+GC, is prevalent in SLE, and that these definitions are associated with poor outcomes.

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.

[2]Koelmeyer, R., et al., High disease activity status suggests more severe disease and damage accrual in systemic lupus erythematosus. Lupus Sci Med, 2020. 7(1).

[3]van Vollenhoven, R.F., et al., Belimumab in the treatment of systemic lupus erythematosus: high disease activity predictors of response. Annals of the Rheumatic Diseases, 2012. 71(8): p. 1343-1349.

Acknowledgements:

The APLC acknowledges all the Data Collectors and Patients for their valuable contributions to research.

Disclosure of Interests:

Rangi Kandane-Rathnayake: None declared, Worawit Louthrenoo: None declared, Alberta Hoi Consultant of: Abbvie and GSK, Grant/research support from: AstraZeneca, GSK, BMS, Janssen, and Merck Serono, Vera Golder: None declared, Yi-Hsing Chen Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, AstraZeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, AstraZeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead, Grant/research support from: Pfizer, Norvatis, BMS, Abbevie, Johnson & Johnson, Roche, Sanofi, Guigai, Roche, Boehringer Ingelheim, UCB, MSD, Astra-Zeneca, Astellas, Gilead, Shue Fen Luo: None declared, Yeong-Jian Jan Wu Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, Aisha Lateef: None declared, Jiacai Cho: None declared, Laniyati Hamijoyo Speakers bureau: Pfizer, Novartis, Abbot, Chak Sing Lau Shareholder of: Pfizer, Sanofi, and Janssen, 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: 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: 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: AbbVie, Boehringer-ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co.,Ltd. and Teijin Pharma., Grant/research support 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, 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., BMDB Basnayake: None declared, Fiona Goldblatt: None declared, Madelynn Chan Speakers bureau: AbbVie, Novartis, Consultant of: Pfizer, Eli-Lilly, Kristine Ng Speakers bureau: Abbvie, Novartis, Janssen, Sang-Cheol Bae: None declared, Shereen Oon: None declared, Sean O’Neill Consultant of: GSK, Kathryn Gibson Speakers bureau: UCB, Consultant of: Novartis, Janssen, Grant/research support from: Novartis, Sunil Kumar: None declared, Nicola Tugnet: 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: Abbvie, Mitsubishi-Tanabe, Chugai, Asahi-Kasei, Eisai, Takeda, Daiichi-Sankyo, 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, 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.

POS0653 IMPACT OF UPADACITINIB OR ADALIMUMAB AS INITIAL THERAPY ON THE ACHIEVEMENT OF 48-WEEK TREATMENT GOALS IN PATIENTS WITH RHEUMATOID ARTHRITIS AND INADEQUATE RESPONSE TO METHOTREXATE: POST HOC ANALYSIS OF A PHASE 3 STUDY

Background:

In the randomized, double-blinded, Phase 3 SELECT-COMPARE study, upadacitinib (UPA) + MTX demonstrated greater clinical and functional responses vs adalimumab (ADA) + MTX in patients (pts) with RA and inadequate response to MTX.1,2 Pts with insufficient response to initial therapy were switched from UPA to ADA (and vice versa) according to treat-to-target (T2T) principles.

Objectives:

We analyzed 1-year treatment outcomes in SELECT-COMPARE according to initial randomization group, regardless of whether pts subsequently switched therapy.

Methods:

Pts initially randomized to UPA 15 mg once daily (QD) or ADA 40 mg every other week (EOW; both + MTX) for up to 48 weeks in SELECT-COMPARE were included in the analysis. As per the protocol-directed rescue strategy, pts experiencing <20% improvement in tender or swollen joint counts at Week 14, 18, or 22, or Clinical Disease Activity Index (CDAI) >10 at Week 26, were switched from UPA to ADA or ADA to UPA in a blinded fashion. Efficacy outcomes included CDAI remission (≤2.8) and low disease activity (LDA; ≤10), DAS of 28 joints using CRP (DAS28[CRP]) <2.6 and ≤3.2, and a composite of “deep response” (CDAI remission, HAQ-Disability Index <0.5, and pain score <20). Data are presented and attributed to initial randomized group (UPA or ADA) regardless of any subsequent switch in therapy. Time-averaged response rates were calculated as area under the curve of response rate standardized by 48 weeks. The proportions of pts who maintained Week 26 responses through 6 months of follow-up are also reported.

Results:

This analysis included 651 pts initially randomized to UPA (of whom 245 switched to ADA) and 327 pts initially randomized to ADA (of whom 157 switched to UPA). Baseline characteristics including age, sex, and BMI were generally well balanced between randomized groups. At Week 48, similar proportions of pts initially randomized to UPA or ADA therapy achieved CDAI remission/LDA (27.6%/61.9% vs 24.8%/59.0%) and DAS28(CRP) <2.6/≤3.2 (45.0%/60.2% vs 43.7%/59.0%) (Figure 1). However, a small but significantly greater proportion of pts achieved a deep response with initial UPA vs initial ADA therapy (17.8% vs 12.8%; p<0.05). In addition, time-averaged response rates over 48 weeks were higher for initial UPA vs initial ADA therapy across efficacy outcomes. Similar trends were observed for other outcomes. Additionally, similar proportions of pts maintained Week 26 responses with initial UPA vs initial ADA therapy based on CDAI remission/LDA and DAS28(CRP) <2.6/≤3.2 during 6-month follow-up (Table 1).

Conclusion:

Using a stringent T2T approach to RA management, rates of LDA or remission at 1 year were similar, regardless of whether pts were initially randomized to UPA or ADA. However, initial UPA therapy led to more frequent deep responses and higher time-averaged response rates vs initial ADA therapy.

References:

[1]Fleischmann R, et al. Arthritis Rheumatol 2019;71:1788–800.

[2]Fleischmann R, et al. Ann Rheum Dis 2019;78:1454–62.

Table 1.

Proportion of patients maintaining Week 26 CDAI and DAS28(CRP) responses during 6-month follow-up by initial therapy with UPA or ADA in SELECT-COMPAREa-c

UPA 15 mg QDADA 40 mg EOWCDAI LDA (≤10)43.936.3CDAI Remission (≤2.8)35.022.7DAS28(CRP) ≤3.239.135.3DAS28(CRP) <2.630.530.1

aAs observed.

bBlinded rescue from UPA to ADA or ADA to UPA was permitted at Week 14, 18, and 22 for patients with <20% improvement in TJC or SJC and at Week 26 for patients with a CDAI <10. Data are presented and attributed to original randomized group (UPA or ADA) regardless of any subsequent switch in therapy.

cMaintaining response defined as never losing response at any visit during ~6 months (22–26 weeks) follow up after first achieving response before or at Week 26.

ADA, adalimumab; CDAI, Clinical Disease Activity Index; DAS28(CRP), DAS of 28 joints using CRP; EOW, every other week; QD, once daily; SJC, swollen joint count; TJC, tender joint count; UPA, upadacitinib.

Acknowledgements:

AbbVie funded this study and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship. Medical writing assistance was provided by Frances Smith, PhD, of 2 the Nth, which was funded by AbbVie.

Disclosure of Interests:

Eduardo Mysler Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Janssen, Pfizer, Roche, and Sandoz., Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Janssen, Pfizer, Roche, and Sandoz., Yoshiya Tanaka Speakers bureau: AbbVie, Asahi Kasei, Astellas, Bristol-Myers Squibb, Eli Lilly, Chugai, Daiichi-Sankyo, Eisai, Gilead, GlaxoSmithKline, Janssen, Mitsubishi-Tanabe, Novartis, Pfizer, Sanofi, and YL Biologics, Consultant of: AbbVie, Asahi Kasei, Astellas, Bristol-Myers Squibb, Eli Lilly, Chugai, Daiichi-Sankyo, Eisai, Gilead, GlaxoSmithKline, Janssen, Mitsubishi-Tanabe, Novartis, Pfizer, Sanofi, and YL Biologics, Grant/research support from: AbbVie, Chugai, Daiichi-Sankyo, Eisai, Mitsubishi-Tanabe, Takeda, and UCB., Arthur Kavanaugh Consultant of: AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, Celgene, Janssen, Pfizer, Roche, and UCB., Grant/research support from: AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, Celgene, Janssen, Pfizer, Roche, and UCB., Daniel Aletaha Consultant of: AbbVie, Amgen, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Roche, Sanofi, and UCB., Grant/research support from: AbbVie, Amgen, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Roche, Sanofi, and UCB., Peter C. Taylor Speakers bureau: AbbVie, Biogen, Bristol-Myers Squibb, Celgene, Celltrion, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Fresenius, Nordic Pharma, Pfizer, Roche, Sanofi, and UCB., Consultant of: AbbVie, Biogen, Bristol-Myers Squibb, Celgene, Celltrion, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Fresenius, Nordic Pharma, Pfizer, Roche, Sanofi, and UCB., Grant/research support from: AbbVie, Biogen, Bristol-Myers Squibb, Celgene, Celltrion, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Fresenius, Nordic Pharma, Pfizer, Roche, Sanofi, and UCB., In-Ho Song Shareholder of: AbbVie, Employee of: AbbVie, Tim Shaw Shareholder of: AbbVie, Employee of: AbbVie, Yanna Song Shareholder of: AbbVie, Employee of: AbbVie, Ryan DeMasi Shareholder of: AbbVie, Employee of: AbbVie, Mira Ali Shareholder of: AbbVie, Employee of: AbbVie, Roy Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sanofi-Aventis, and UCB., Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sanofi-Aventis, and UCB.