OP0017 RECAPTURE RATES WITH IXEKIZUMAB AFTER WITHDRAWAL OF THERAPY IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS: RESULTS AT WEEK 104 FROM A RANDOMIZED PLACEBO-CONTROLLED WITHDRAWAL STUDY

Background

COAST-Y is the first study to evaluate the effect of continuing vs withdrawing an IL-17A antagonist, Ixekizumab (IXE) on the maintenance of disease control in patients (pts) with ankylosing spondylitis and non-radiographic axial spondyloarthritis through 104 Weeks (wks).

Objectives

Here, we describe the final results of pts re-randomized to either placebo (PBO; IXE Withdrawal) or IXE, who experienced flare, and recaptured response before or after open label retreatment during COAST-Y.

Methods

COAST-Y (NCT03129100) is a Phase 3, long-term extension study that included a double-blind, PBO-controlled, randomized withdrawal-retreatment period (RWP). Eligible pts who completed an originating study (COAST-V, -W, or -X) entered a 24-Week (Wk) lead-in period and received 80 mg IXE every 2 (Q2W) or 4 wks (Q4W) (the treatment regimen at the end of the originating study); pts receiving PBO at the end of COAST-X were assigned to IXE Q4W in COAST-Y. Pts who achieved remission (Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3 (inactive disease; ID) at least once at Wk 16 or 20, and <2.1 (low disease activity; LDA) at both visits) were randomized 2:1 at Wk 24 to continue IXE (as per lead-in period) or withdrawn to PBO. Pts who subsequently experienced flare (ASDAS ≥2.1 at 2 consecutive visits or ASDAS >3.5 at any visit) were switched to open label IXE Q2W or Q4W at the next visit (same as lead-in period). Time to first flare was analyzed using the Kaplan-Meier method with treatment comparison performed using log-rank test. The observed proportion of pts who recaptured ASDAS LDA and ID were summarized for pts who experienced flare and were retreated with open label IXE.

Results

A total of 155 pts met the criteria for remission and entered the RWP (PBO [IXE withdrawal], N=53; IXE Q4W, N=48; IXE Q2W, N=54) and 138 completed Wk 104. At Wk 104, significantly more pts in the combined IXE group (75.5%, p<0.001, IXE Q4W: 75.0%, p<0.001; IXE Q2W: 75.9%, p<0.001) remained flare free through Wk 104 vs PBO (Figure 1). Notably, 35.8% of pts on PBO (IXE Withdrawal) never experienced flare. Of the PBO pts who experienced flare and were retreated during Wk 24-104 (N=28), 4 recaptured LDA before switching to open label IXE retreatment, while 23 recaptured LDA and 19 met ID after switching (Table 1). Of the continuously treated IXE pts (N=13), 7 recaptured LDA before switching to open label IXE retreatment, while 5 recaptured LDA and 4 met ID after.

Figure 1.

The proportion (%) of patients who remained flare free through 104 weeks. ‡p<0.001, †p<0.01, *p<0.05 vs PBO (IXE Withdrawal).

Table 1.

Recapture of first treatment response before or after switching to open label IXE through 104 weeks among placebo (ixekizumab withdrawal)-treated patients who experienced a flare and retreated

Total patients who flared and were switched to open-label ixekizumab retreatmentPlacebo (ixekizumab withdrawal)(N=28)ASDAS disease activity statusLDAIDRecaptured response before open label ixekizumab retreatment41Recaptured response with open label ixekizumab retreatment (≤16 weeks)2314Recaptured response with open label ixekizumab retreatment (>16 weeks)05Total patients who recaptured response at week 10427/28 (96%)20/28 (71%)

Data are presented as n, (%) for the total row and n only for all other rows. In each column, the denominator is 28. ASDAS, Ankylosing Spondylitis Disease Activity Score; ID, inactive disease; LDA, low disease activity including ID; N, number of patients in the analysis population.

Conclusion

Pts continuously treated with IXE were less likely to experience flare vs pts on PBO (IXE withdrawal). The vast majority of pts withdrawn from IXE to PBO recaptured at least LDA and over half met ID with IXE retreatment. This may provide support for pts who require interruption in therapy.

Acknowledgements

This study was sponsored by Eli Lilly and Company. Medical writing services were provided by Edel Hughes, PhD and Sumeet Sood, PhD of Eli Lilly and Company, and was funded by Eli Lilly and Company.

Disclosure of Interests

Robert B.M. Landewé Consultant of: Rheumatology Consultancy BV, AbbVie, UCB, Pfizer, Eli Lilly and Company, Novartis, and Celgene, Denis Poddubnyy Speakers bureau: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, and UCB Pharma, Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, and UCB Pharma, Grant/research support from: AbbVie, Eli Lilly and Company, Merck Sharp & Dohme, Novartis, and Pfizer, Proton Rahman Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, and UCB, Rebecca Bolce Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Soyi Liu Leage Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Jeffrey Lisse Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Ann Leung: None declared, So Young Park Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Lianne S. Gensler Consultant of: AbbVie, Eli Lilly and Company, Grant/research support from: Novartis, Pfizer, and UCB.

Psoriatic arthritis from a mechanistic perspective

Psoriatic arthritis (PsA) is part of a group of closely related clinical phenotypes ('psoriatic disease') that is defined by shared molecular pathogenesis resulting in excessive, prolonged inflammation in the various tissues affected, such as the skin, the entheses or the joints. Psoriatic disease comprises a set of specific drivers that promote an aberrant immune response and the consequent development of chronic disease that necessitates therapeutic intervention. These drivers include genetic, biomechanical, metabolic and microbial factors that facilitate a robust and continuous mobilization, trafficking and homing of immune cells into the target tissues. The role of genetic variants involved in the immune response, the contribution of mechanical factors triggering an exaggerated inflammatory response (mechanoinflammation), the impact of adipose tissue and altered lipid metabolism and the influence of intestinal dysbiosis in the disease process are discussed. Furthermore, the role of key cytokines, such as IL-23, IL-17 and TNF, in orchestrating the various phases of the inflammatory disease process and as therapeutic targets in PsA is reviewed. Finally, the nature and the mechanisms of inflammatory tissue responses inherent to PsA are summarized.

P277 Ixekizumab shows a distinct pattern of pain improvement beyond measurable inflammation as assessed by MRI, CRP or BASDAI questions 5 and 6 in patients with ankylosing spondylitis

Background/Aims

Efficacy of ixekizumab (IXE) in patients (pts) with ankylosing spondylitis (AS) at week (W) 16 in the absence of elevated inflammation as measured by CRP and MRI Spondyloarthritis Research Consortium of Canada (SPARCC) has been previously reported. In this analysis, we evaluated the improvement in pain with IXE based on longitudinal status of objective measures of inflammation by MRI, CRP value, and BASDAI 5/6 over 16W.

Methods

The Phase III COAST-V (NCT02696785) 52W, multi-center, randomized, double-blind, placebo (PBO)-controlled study examined the efficacy of IXE in pts with active AS. Adalimumab (ADA) was used as an active reference arm for the first 16W. Pts assigned to ADA went through a wash-out period of 6W prior to getting their first dose of IXE. Change in spinal pain at night (SP-N) and Short Form 36 Health Survey Questionnaire (SF-36) Bodily Pain were measured during study visits and analyzed while controlling for inflammation status using MRI, CRP levels and mean of BASDAI 5/6 (Q5: Duration, Q6: Intensity of morning stiffness). Observed data analyses are presented for each group stratified by treatment arm. Initial analysis: ‘controlled inflammation’ is defined as MRI SPARCC SI joint &lt;4 and MRI SPARCC Spine &lt;3 at W16, CRP &lt;5mg/L at every visit W4-16, or BASDAI 5/6 improvement of ≥ 2 points W12 and W16. Second analysis: control is defined as CRP &lt;5 mg/L at every week between W4-16 and MRI SPARCC SI joint &lt;4 at W16 and MRI SPARCC Spine &lt;3 at W16.

Results

When inflammation is controlled per MRI, pts treated (tx) with IXEQ4W (-3.9 p&lt;0.001) and ADA (-2.8 p=0.02) experienced significant reduction in SP-N vs PBO (-1.6) at W16; further improvements were experienced in pts rerandomized to IXE by W52. When inflammation was not controlled per MRI, IXEQ4W (-3.5 p&lt;0.01) and ADA (-3.1 p=0.02) experienced significant reduction in SP-N at W16; all IXE tx pts had further reductions at W52. When inflammation was controlled per MRI+CRP, IXEQ4W (-3.8 p=0.2) and ADA (-3.1 p=0.4) had reduction in SP-N at W16 vs PBO (-2.4); all IXE groups had further improvements at W52. When inflammation was not controlled as measured by MRI+CRP, IXEQ4W (-3.7 p&lt;0.001) had significant reduction in SP-N vs PBO (-1.7), whereas improvement with ADA (-2.6 p=0.06) was not significant; all IXE tx pts had further reduction by W52. For SF-36 bodily pain, improvements were observed with IXE and ADA at W16 and W52, whether inflammation was controlled or not controlled per MRI, CRP, MRI+CRP, or BASDAI 5/6.

Conclusion

This analysis adds support to the hypothesis that IXE improves pain in pts with and without measurable inflammation.

Disclosure

N. Maney: None. K. de Vlam: Consultancies; Celgene, Eli Lilly and Company, Galapagos NV, Novartis, Pfizer, and UCB Pharma. Grants/research support; Celgene. P.G. Conaghan: Consultancies; Amgen, Bristol Myers Squibb, Eli Lilly and Company, Galapagos NV, Gilead Sciences, Novartis, Pfizer, and UCB Pharma. P.J. Mease: Member of speakers’ bureau; AbbVie, Amgen, Bristol Myers Squibb, Celgene, Genentech, Janssen, Pfizer, and UCB Pharma. Grants/research support; AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Galapagos NV, Gilead Sciences, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and UCB Pharma. P. Rahman: Grants/research support; AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and UCB Pharma. V. Krishnan: Shareholder/stock ownership; Eli Lilly and Company. R. Bolce: Shareholder/stock ownership; Eli Lilly and Company. D. Marcelino Sandoval Calderon: Shareholder/stock ownership; Eli Lilly and Company. S. Park: Shareholder/stock ownership; Eli Lilly and Company. G. Gallo: Shareholder/stock ownership; Eli Lilly and Company. W. Maksymowych: Grants/research support; AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Galapagos NV, Janssen, Novartis, Pfizer, and UCB Pharma; and is the Chief Medical Officer of CARE Arthritis Ltd.

Restricting Branched-Chain Amino Acids within a High-Fat Diet Prevents Obesity

Obesity is a global pandemic, but there is yet no effective measure to control it. Recent metabolomics studies have identified a signature of altered amino acid profiles to be associated with obesity, but it is unclear whether these findings have actionable clinical potential. The aims of this study were to reveal the metabolic alterations of obesity and to explore potential strategies to mitigate obesity. We performed targeted metabolomic profiling of the plasma/serum samples collected from six independent cohorts and conducted an individual data meta-analysis of metabolomics for body mass index (BMI) and obesity. Based on the findings, we hypothesized that restriction of branched-chain amino acids (BCAAs), phenylalanine, or tryptophan may prevent obesity and tested our hypothesis in a dietary restriction trial with eight groups of 4-week-old male C57BL/6J mice (n = 5/group) on eight different types of diets, respectively, for 16 weeks. A total of 3397 individuals were included in the meta-analysis. The mean BMI was 30.7 ± 6.1 kg/m2, and 49% of participants were obese. Fifty-eight metabolites were associated with BMI and obesity (all p ≤ 2.58 × 10-4), linked to alterations of the BCAA, phenylalanine, tryptophan, and phospholipid metabolic pathways. The restriction of BCAAs within a high-fat diet (HFD) maintained the mice's weight, fat and lean volume, subcutaneous and visceral adipose tissue weight, and serum glucose and insulin at levels similar to those in the standard chow group, and prevented obesity, adipocyte hypertrophy, adipose inflammation, and insulin resistance induced by HFD. Our data suggest that four metabolic pathways, BCAA, phenylalanine, tryptophan, and phospholipid metabolic pathways, are altered in obesity and restriction of BCAAs within a HFD can prevent the development of obesity and insulin resistance in mice, providing a promising strategy to potentially mitigate diet-induced obesity.

Comparison between adalimumab introduction and methotrexate dose escalation in patients with inadequately controlled psoriatic arthritis (CONTROL): a randomised, open-label, two-part, phase 4 study

BACKGROUND

Many patients with psoriatic arthritis do not reach minimal disease activity (MDA) on methotrexate alone. This phase 4 open-label study aimed to compare attainment of MDA following introduction of adalimumab with methotrexate escalation in patients with psoriatic arthritis who do not reach MDA after an initial methotrexate course (≤15 mg every week).

METHODS

CONTROL was a phase 4, randomised, two-part, open-label study conducted in 14 countries and 46 sites. We recruited patients with confirmed active psoriatic arthritis, naive to biologic disease-modifying antirheumatic drugs, with an inadequate response to 15 mg or less of methotrexate. In part 1, patients were randomly assigned (1:1) to receive either methotrexate 15 mg (oral or subcutaneous) every week with the addition of adalimumab 40 mg (subcutaneously) every other week (adalimumab plus methotrexate group) or methotrexate (oral or subcutaneous) escalation up to 25 mg every week (escalated methotrexate group). Randomisation was done using Interactive Response Technology and stratified by the duration of methotrexate treatment (≤3 months and >3 months). In this open-label study there was no masking; participants, people giving the interventions, those assessing outcomes, and those analysing the data were aware of group assignment. The primary endpoint was the proportion of patients who reached MDA at 16 weeks. After 16 weeks (part 2), patients who reached MDA (responders) had their current therapy maintained or modified, wheras patients who did not reach MDA (non-responders) had their therapy escalated until 32 weeks. The primary endpoint in part 2 was the proportion of patients who reached MDA at 32 weeks, analysed in all patients who received one or more doses of study drug. The study is registered with ClinicalTrials.gov, NCT02814175.

FINDINGS

Between Aug 5, 2016, and March 19, 2020, 245 of 287 patients initially assessed were enrolled in the study (50% men and 50% women; 92% of patients were White). 123 patients were randomly assigned to receive adalimumab plus methotrexate and 122 patients to receive escalated methotrexate. All 245 patients were included in the primary analysis, and 227 completed part 1 and entered part 2. A significantly higher proportion of patients reached MDA at 16 weeks in the adalimumab plus methotrexate group (51 [41%] patients) compared with the escalated methotrexate group (16 [13%] patients; p<0·0001). Efficacy was generally maintained through 32 weeks for patients who reached MDA at 16 weeks, with 41 (80%) of 51 adalimumab responders and ten (67%) of 15 methotrexate responders maintaining MDA at 32 weeks. Of adalimumab non-responders, 17 (30%) of 57 patients reached MDA at 32 weeks after adalimumab escalation to every week dosing. Among methotrexate non-responders, 50 (55%) of 91 reached MDA after adalimumab introduction. In part 1, two patients in the adalimumab plus methotrexate group reported serious adverse events; and in part 2, one adalimumab responder, three adalimumab non-responders, and three methotrexate non-responders reported serious adverse events. No new safety signals were identified.

INTERPRETATION

Results from this novel treatment-strategy trial support the addition of adalimumab over escalating methotrexate in patients with psoriatic arthritis not reaching MDA after an initial methotrexate course. Safety results were consistent with the therapies' known safety profiles.

FUNDING

AbbVie.

Defining imaging sub-phenotypes of psoriatic arthritis: integrative analysis of imaging data and gene expression in a PsA patient cohort

OBJECTIVES

To define imaging sub-phenotypes in patients with PsA; determine their association with whole blood gene expression and identify biological pathways characterizing the sub-phenotypes.

METHODS

Fifty-five patients with PsA ready to initiate treatment for active disease were prospectively recruited. We performed musculoskeletal ultrasound assessment of the extent of inflammation in the following domains: synovitis, peritenonitis, tenosynovitis and enthesitis. Peripheral whole blood was profiled with RNAseq, and gene expression data were obtained. First, unsupervised cluster analysis was performed to define imaging sub-phenotypes that reflected the predominant tissue involved. Subsequently, principal component analysis was used to determine the association between imaging-defined sub-phenotypes and peripheral blood gene expression profile. Pathway enrichment analysis was performed to identify underlying mechanisms that characterize individual sub-phenotypes.

RESULTS

Cluster analysis revealed three imaging sub-phenotypes: (i) synovitis predominant [n = 31 (56%)]; (ii) enthesitis predominant [n = 13 (24%)]; (iii) peritenonitis predominant [n = 11 (20%)]. The peritenonitis-predominant sub-phenotype had the most severe clinical joint involvement, whereas the enthesitis-predominant sub-phenotype had the highest tender entheseal count. Unsupervised clustering of gene expression data identified three sub-phenotypes that partially overlapped with the imaging sub-phenotypes suggesting biological and clinical relevance of these sub-phenotypes. We therefore characterized enriched differential pathways, which included: immune system (innate system, B cells and neutrophil degranulation), complement system, platelet activation and coagulation function.

CONCLUSIONS

We identified three sub-phenotypes based on the predominant tissue involved in patients with active PsA. Distinct biological pathways may underlie these imaging sub-phenotypes seen in PsA, suggesting their biological and clinical importance.

Metabolomic signatures for the longitudinal reduction of muscle strength over 10 years

Background

Skeletal muscles are essential components of the neuromuscular skeletal system that have an integral role in the structure and function of the synovial joints which are often affected by osteoarthritis (OA). The aim of this study was to identify the baseline metabolomic signatures for the longitudinal reduction of muscle strength over 10 years in the well-established community-based Tasmanian Older Adult Cohort (TASOAC).

Methods

Study participants were 50–79 year old individuals from the TASOAC. Hand grip, knee extension, and leg strength were measured at baseline, 2.6-, 5-, and 10-year follow-up points. Fasting serum samples were collected at 2.6-year follow-up point, and metabolomic profiling was performed using the TMIC Prime Metabolomics Profiling Assay. Generalized linear mixed effects model was used to identify metabolites that were associated with the reduction in muscle strength over 10 years after controlling for age, sex, and BMI. Significance level was defined at α=0.0004 after correction of multiple testing of 129 metabolites with Bonferroni method. Further, a genome-wide association study (GWAS) analysis was performed to explore if genetic factors account for the association between the identified metabolomic markers and the longitudinal reduction of muscle strength over 10 years.

Results

A total of 409 older adults (50% of them females) were included. The mean age was 60.93±6.50 years, and mean BMI was 27.12±4.18 kg/m² at baseline. Muscle strength declined by 0.09 psi, 0.02 kg, and 2.57 kg per year for hand grip, knee extension, and leg strength, respectively. Among the 143 metabolites measured, 129 passed the quality checks and were included in the analysis. We found that the elevated blood level of asymmetric dimethylarginine (ADMA) was associated with the reduction in hand grip (p=0.0003) and knee extension strength (p=0.008) over 10 years. GWAS analysis found that a SNP rs1125718 adjacent to WISP1gene was associated with ADMA levels (p=4.39*10^-8). Further, we found that the increased serum concentration of uric acid was significantly associated with the decline in leg strength over 10 years (p=0.0001).

Conclusion

Our results demonstrated that elevated serum ADMA and uric acid at baseline were associated with age-dependent muscle strength reduction. They might be novel targets to prevent muscle strength loss over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13395-022-00286-9.

Mutational Landscape of Autism Spectrum Disorder Brain Tissue

Rare post-zygotic mutations in the brain are now known to contribute to several neurodevelopmental disorders, including autism spectrum disorder (ASD). However, due to the limited availability of brain tissue, most studies rely on estimates of mosaicism from peripheral samples. In this study, we undertook whole exome sequencing on brain tissue from 26 ASD brain donors from the Harvard Brain Tissue Resource Center (HBTRC) and ascertained the presence of post-zygotic and germline mutations categorized as pathological, including those impacting known ASD-implicated genes. Although quantification did not reveal enrichment for post-zygotic mutations compared with the controls (n = 15), a small number of pathogenic, potentially ASD-implicated mutations were identified, notably in TRAK1 and CLSTN3. Furthermore, germline mutations were identified in the same tissue samples in several key ASD genes, including PTEN, SC1A, CDH13, and CACNA1C. The establishment of tissue resources that are available to the scientific community will facilitate the discovery of new mutations for ASD and other neurodevelopmental disorders.

Long-term Efficacy and Safety of Guselkumab, a Monoclonal Antibody Specific to the p19 Subunit of Interleukin-23, Through 2 Years: Results from a Phase 3, Randomized, Double-blind, Placebo-controlled Study Conducted in Biologic-naïve Patients with Active Psoriatic Arthritis

OBJECTIVE

Assess long-term efficacy and safety of guselkumab, an IL-23p19-subunit inhibitor, in patients with active psoriatic arthritis (PsA) from the Phase-3 DISCOVER-2 trial.

METHODS

In DISCOVER-2, patients with active PsA (≥5 swollen and ≥5 tender joints; CRP ≥0.6 mg/dL) despite prior nonbiologic therapy were randomized to: guselkumab 100mg every-4-weeks (Q4W); at Week0, Week4, and Q8W; or placebo➔guselkumab Q4W at Week24. Efficacy assessments included ≥20%/50%/70% improvement in ACR components (ACR20/50/70), Investigator's Global Assessment of psoriasis score=0 (IGA=0; indicating complete skin clearance), enthesitis (Leeds Enthesitis Index) and dactylitis (Dactylitis Severity Score) resolution, and changes in PsA-modified van der Heijde-Sharp (vdH-S) radiographic scores. Clinical data (imputed as no response/no change from baseline if missing) and observed radiographic data were summarized through Week100; safety assessments continued through Week112.

RESULTS

Of 739 randomized and treated patients, 652 (88%) completed treatment through Week100. Across groups of guselkumab-treated patients (including placebo➔Q4W) ACR20 (68%-76%), ACR50 (48%-56%), ACR70 (30%-36%), and IGA=0 (55%-67%) responses and enthesitis (62%-70%) and dactylitis (72%-83%) resolution rates at Week100 indicated amelioration of arthritis signs/symptoms and extra-articular manifestations was durable through 2years. Mean changes in PsA-modified vdH-S scores from Week52-100 (0.13-0.75) indicated the low rates of radiographic progression observed among guselkumab-treated patients at earlier timepoints extended through Week100. Through Week112, 8% (5.8/100 patient-years) and 3% (1.9/100 patient-years) of 731 guselkumab-treated patients had a serious adverse event or serious infection, respectively; one death occurred (road traffic accident).

CONCLUSION

In biologic-naïve PsA patients, guselkumab provided durable improvements in multiple disease domains with no unexpected safety findings through 2years.

Single-cell transcriptome identifies FCGR3B upregulated subtype of alveolar macrophages in patients with critical COVID-19

Understanding host cell heterogeneity is critical for unraveling disease mechanism. Utilizing large-scale single-cell transcriptomics, we analyzed multiple tissue specimens from patients with life-threatening COVID-19 pneumonia, compared with healthy controls. We identified a subtype of monocyte-derived alveolar macrophages (MoAMs) where genes associated with severe COVID-19 comorbidities are significantly upregulated in bronchoalveolar lavage fluid of critical cases. FCGR3B consistently demarcated MoAM subset in different samples from severe COVID-19 cohorts and in CCL3L1-upregulated cells from nasopharyngeal swabs. In silico findings were validated by upregulation of FCGR3B in nasopharyngeal swabs of severe ICU COVID-19 cases, particularly in older patients and those with comorbidities. Additional lines of evidence from transcriptomic data and in vivo of severe COVID-19 cases suggest that FCGR3B may identify a specific subtype of MoAM in patients with severe COVID-19 that may present a novel biomarker for screening and prognosis, as well as a potential therapeutic target.

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Association of MoAM subtype with severe COVID-19 cases presented with comorbidities

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Upregulated FCGR3B in CCL3L1 positive MoAM cells in severe COVID-19 cases

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Upregulated FCGR3B within MoAM subtype as a potential marker for COVID-19 severity

Ixekizumab improves spinal pain, function, fatigue, stiffness, and sleep in radiographic axial Spondyloarthritis: COAST-V/W 52-week results

Background

This analysis assessed improvements in patients with radiographic axial spondyloarthritis (r-axSpA) treated with ixekizumab in the Assessment of Spondyloarthritis International Society (ASAS) treatment response domains and additional patient-reported outcomes at 1 year of treatment.

Methods

COAST-V and COAST-W were 52-week, phase 3, randomized controlled trials evaluating the efficacy and safety of ixekizumab in biologic disease-modifying antirheumatic drug (bDMARD)-naïve and tumor necrosis factor inhibitor (TNFi)-experienced patients with radiographic spondyloarthritis, respectively. Patients were treated with 80-mg ixekizumab either every 2 weeks or every 4 weeks. Patient-reported outcomes included Patient Global Disease Activity, Spinal Pain, stiffness as measured by Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) Questions 5 and 6, function as measured by the Bath Ankylosing Spondylitis Functional Index, fatigue as measured by the Fatigue Numeric Rating Scale and BASDAI question 1, Spinal Pain at Night, and sleep quality as measured by the Jenkins Sleep Evaluation Questionnaire. Mixed-effects models for repeated measures were used to analyze changes from baseline in patient-reported outcomes from weeks 1 to 16, and descriptive statistics were reported from weeks 20 to 52. Analysis of covariance with Scheffé’s method was used for the ASAS response association analyses.

Results

This study assessed 341 bDMARD-naïve and 316 TNFi-experienced patients in the placebo-controlled blinded treatment dosing period (weeks 1–16) as well as 329 bDMARD-naïve and 281 TNFi-experienced patients in the dose double-blind extended treatment period (weeks 20–52). bDMARD-naïve or TNFi-experienced patients treated with ixekizumab every 2 weeks and every 4 weeks reported improvements in patient global disease activity, spinal pain, function, stiffness, fatigue, spinal pain at night, and sleep quality through week 52. Greater correlations with improvements in all response domains were seen when comparing ASAS40 responders to ASAS20 non-responders (p < 0.001), with up to 10.5-fold greater improvements observed in ASAS40 responses compared with ASAS20 non-responders. Function and fatigue demonstrated the highest values.

Conclusions

Ixekizumab-treated bDMARD-naïve and TNFi-experienced patients with radiographic axial spondyloarthritis achieving ASAS40 reported sustained and consistent improvement in all ASAS response domains and other patient-reported outcomes though week 52, with spinal pain, function, and stiffness as major drivers of the response.

Trial registration

NCT02696785 and NCT02696798, March 2, 2016.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41927-021-00205-3.

Guselkumab demonstrated an independent treatment effect in reducing fatigue after adjustment for clinical response-results from two phase 3 clinical trials of 1120 patients with active psoriatic arthritis

Background

The interleukin-23p19-subunit inhibitor guselkumab effectively treats signs and symptoms of psoriatic arthritis (PsA). We evaluated the effect of guselkumab on fatigue.

Methods

Across two phase 3 trials of guselkumab (DISCOVER-1, DISCOVER-2), patients with active PsA despite standard therapy were randomized to subcutaneous injections of guselkumab 100 mg every 4 weeks (Q4W, N = 373); guselkumab 100 mg at week 0, week 4, and then Q8W (N = 375); or placebo (N = 372) through week 24, after which patients in the placebo group crossed over to guselkumab Q4W. Fatigue was measured as a secondary endpoint using the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue instrument (range 0–52, higher scores indicate less fatigue). Least-squares mean changes in FACIT-Fatigue scores were compared between treatments using a mixed-effect model for repeated measures. Mediation analysis was used to adjust for indirect effects on fatigue deriving from improvement in other outcomes, including ≥20% improvement in American College of Rheumatology criteria (ACR20; prespecified), minimal disease activity (MDA; post hoc), or C-reactive protein (CRP; post hoc).

Results

Baseline mean (SD) FACIT-Fatigue scores in DISCOVER-1 (N = 381) and DISCOVER-2 (N = 739), ranging from 29.1 (9.5) to 31.4 (10.1), indicated substantial levels of fatigue relative to the United States general population (43.6 [9.4]). Across studies, mean improvements, and proportions of patients with ≥4-point improvements, in FACIT-Fatigue scores at week 24 with guselkumab Q4W and Q8W (5.6–7.6 and 54–63%, respectively) were larger vs placebo (2.2–3.6 and 35–46%). Improvement in FACIT-Fatigue scores with guselkumab was sustained from week 24 to week 52, with moderate-to-large effect sizes (Cohen’s d = 0.52–0.81 at week 24; 0.66–0.91 at week 52). Mediation analyses demonstrated that substantial proportions of the effects of guselkumab vs placebo on fatigue were direct effect, after adjusting for achievement of ACR20 (Q4W 69–70%, Q8W 12–36% direct effect) or MDA (72–92% across dosing regimens) response or for change in serum CRP concentrations (82–88% across dosing regimens).

Conclusions

In patients with active PsA, guselkumab 100 mg Q4W or Q8W led to clinically meaningful and sustained improvements in fatigue through 1 year. A substantial portion of the improvement in FACIT-Fatigue scores induced by guselkumab was independent of effects on the achievement of other select outcomes.

Trial registration

Name of the registry: ClinicalTrials.gov

Trial registrations: DISCOVER-1, NCT03162796; DISCOVER-2, NCT03158285

Date of registration: DISCOVER-1, May 22, 2017; DISCOVER-2, May 18, 2017

URLs of the trial registry record:

DISCOVER-1, https://clinicaltrials.gov/ct2/show/NCT03162796?term=NCT03162796&draw=1&rank=1

DISCOVER-2, https://clinicaltrials.gov/ct2/show/NCT03158285?term=NCT03158285&draw=2&rank=1

Secukinumab provides sustained improvement in signs and symptoms and low radiographic progression in patients with psoriatic arthritis: 2-year (end-of-study) results from the FUTURE 5 study

OBJECTIVE

Secukinumab provided sustained efficacy, low radiographic progression and consistent safety over 52 weeks in patients with psoriatic arthritis (PsA) in the FUTURE 5 study. Here, we report 2-year (end-of-study) results from this study.

METHODS

Adults with active PsA were randomised 2:2:2:3 to receive subcutaneous secukinumab 300 mg load (300 mg), 150 mg load (150 mg), 150 mg no load or placebo at baseline; weeks 1, 2, 3 and 4; and every 4 weeks thereafter. Secukinumab could be escalated from 150 mg to 300 mg starting at week 52, if active signs of disease were observed based on physician's assessment. Assessments at week 104 (2 years) included clinical end points and radiographic damage (mean change in van der Heijde-modified total Sharp score (vdH-mTSS)). Safety analysis included all patients who received ≥1 dose of study medication.

RESULTS

Of the 996 patients randomised, 783 patients (78.6%) completed 2 years of treatment. Improvement in clinical end points was sustained through 2 years. The vdH-mTSS (mean change (SD)) was 0.10 (1.74; 300 mg), 0.52 (2.66; 150 mg) and 0.41 (2.20; 150 mg no load) at 2 years. The proportion of patients with no radiographic progression (change from baseline in vdH-mTSS ≤0.5) at 2 years was 89.5% (300 mg), 82.3% (150 mg) and 81.1% (150 mg no load).

CONCLUSION

Secukinumab with and without loading regimen provided sustained clinical efficacy and low radiographic progression through 2 years in patients with PsA. No new safety findings were reported.

TRIAL REGISTRATION NUMBER

NCT02404350.

Endotypes of primary osteoarthritis identified by plasma metabolomics analysis

OBJECTIVE

To identify endotypes of osteoarthritis (OA) by a metabolomics analysis.

METHODS

Study participants included hip/knee OA patients and controls. Fasting plasma samples were metabolomically profiled. Common factor analysis and K-means clustering were applied to the metabolomics data to identify the endotypes of OA patients. Logistic regression was utilized to identify the most significant metabolites contributing to the endotypes. Clinical and epidemiological factors were examined in relation to the identified OA endotypes.

RESULTS

Six hundred and fifteen primary OA patients and 237 controls were included. Among the 186 metabolites measured, 162 passed the quality control analysis. The 615 OA patients were classified in three clusters (A, 66; B, 200; and C, 349). Patients in cluster A had a significantly higher concentration of butyrylcarnitine (C4) than other clusters and controls (all P < 0.0002). Elevated C4 is thought to be related to muscle weakness and wasting. Patients in cluster B had a significantly lower arginine concentration than other clusters and controls (all P < 7.98 × 10-11). Cluster C patients had a significantly lower concentration of lysophosphatidylcholine (with palmitic acid), which is a pro-inflammatory bioactive compound, than other clusters and controls (P < 3.79 × 10-6). Further, cluster A had a higher BMI and prevalence of diabetes than other clusters (all P ≤ 0.0009), and also a higher prevalence of coronary heart disease than cluster C (P = 0.04). Cluster B had a higher prevalence of coronary heart disease than cluster C (P = 0.003) whereas cluster C had a higher prevalence of osteoporosis (P = 0.009).

CONCLUSION

Our data suggest three possible clinically actionable endotypes in primary OA: muscle weakness, arginine deficit and low inflammatory OA.

Modelling the impact of travel restrictions on COVID-19 cases in Newfoundland and Labrador

In many jurisdictions, public health authorities have implemented travel restrictions to reduce coronavirus disease 2019 (COVID-19) spread. Policies that restrict travel within countries have been implemented, but the impact of these restrictions is not well known. On 4 May 2020, Newfoundland and Labrador (NL) implemented travel restrictions such that non-residents required exemptions to enter the province. We fit a stochastic epidemic model to data describing the number of active COVID-19 cases in NL from 14 March to 26 June. We predicted possible outbreaks over nine weeks, with and without the travel restrictions, and for contact rates 40-70% of pre-pandemic levels. Our results suggest that the travel restrictions reduced the mean number of clinical COVID-19 cases in NL by 92%. Furthermore, without the travel restrictions there is a substantial risk of very large outbreaks. Using epidemic modelling, we show how the NL COVID-19 outbreak could have unfolded had the travel restrictions not been implemented. Both physical distancing and travel restrictions affect the local dynamics of the epidemic. Our modelling shows that the travel restrictions are a plausible reason for the few reported COVID-19 cases in NL after 4 May.

AB0527 CORRELATIONS BETWEEN REDUCTIONS IN FATIGUE SEVERITY AND IMPROVEMENTS IN PHYSICAL FUNCTION AND CLINICAL RESPONSE IN PATIENTS WITH PSORIATIC ARTHRITIS: RESULTS FROM THE PHASE 3 DISCOVER PROGRAM

Background:

In patients (pts) with psoriatic arthritis (PsA), fatigue is a major driver of perceived impact of disease and has been identified as an important domain to be assessed in clinical trials.1,2 The association between fatigue and other PsA domains (eg, physical function) or clinical response is not well understood.

Objectives:

Fatigue was measured with the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue questionnaire in the pivotal DISCOVER-1 and DISCOVER-2 Phase 3 studies of guselkumab (GUS) vs placebo (PBO). This post hoc analysis explores the correlation between FACIT-Fatigue and physical function and clinical response in the DISCOVER program.

Methods:

This analysis used pooled data from pts (N=1120) treated with GUS or PBO. In DISCOVER-1 and DISCOVER-2, 381 pts with active PsA (swollen joint count [SJC] ≥3, tender joint count [TJC] ≥3, C-reactive protein [CRP] ≥0.3 mg/dL) and 739 pts with active PsA (SJC ≥5, TJC ≥5, CRP ≥0.6 mg/dL) and inadequate response to standard therapies, respectively, were randomized 1:1:1 to GUS 100 mg Q4W; GUS 100 mg at W0, W4, then Q8W; or PBO. PBO pts switched to GUS 100 mg Q4W at W24. The FACIT-Fatigue questionnaire has 13 items that assess self-reported fatigue/tiredness over the last 7 days. Items are scored from 0 (very much fatigued) to 4 (not at all fatigued). FACIT-Fatigue response was defined as an increase of ≥4 points from baseline. Physical function was evaluated with the Health Assessment Questionnaire-Disability Index (HAQ-DI). HAQ-DI response was defined as a decrease of ≥0.35 points from baseline. Clinical response was defined as achievement of ≥20% improvement in the American College of Rheumatology (ACR 20) criteria. Relationships between FACIT-Fatigue and HAQ-DI at W8/16/24 were assessed by Pearson correlation coefficients. Mean changes in HAQ-DI scores at W8/16/24 were summarized in FACIT-Fatigue responders and nonresponders. A logistic regression model was applied to estimate odds ratios (ORs) for achievement of HAQ-DI and ACR 20 response by FACIT-Fatigue response status at each visit. A multiple linear regression model was used to evaluate the association between FACIT-Fatigue and HAQ-DI at W24 after adjusting for SJC, TJC, CRP, and pt assessment of pain.

Results:

FACIT-Fatigue and HAQ-DI scores and changes from baseline were negatively correlated at W8, W16, and W24 (Table 1). Mean changes in HAQ-DI were −0.31, −0.43, and −0.48 at W8, W16, and W24, respectively, in FACIT-Fatigue responders and −0.06, −0.07, and −0.09, respectively, in FACIT-Fatigue nonresponders. FACIT-Fatigue responders were significantly more likely than nonresponders to achieve HAQ-DI and ACR 20 response (OR [95% CI] at W8, 2.8 [2.2-3.7] and 2.4 [1.9-3.1]; at W16, 3.6 [2.8-4.7] and 2.9 [2.3-3.7]; and at W24, 4.4 [3.4-5.7] and 3.2 [2.5-4.2], respectively; Figure 1). Correlations between FACIT-Fatigue and HAQ-DI remained significant after adjusting for SJC, TJC, CRP, and pt assessment of pain.

Conclusion:

In pts with PsA, fatigue response is a clinically meaningful predictor of improvements in physical function and achievement of ACR 20 response, reinforcing the importance of assessing fatigue in PsA disease management.

References:

[1]Leung YY et al. J Rheumatol. 2020;96:46-9.

[2]Gudu T et al. Joint Bone Spine. 2016;83:439-43.

Table 1.

Correlation* of FACIT-Fatigue and HAQ-DI

VisitHAQ-DI and FACIT Fatigue ScoresChanges From Baseline in HAQ-DI and FACIT-Fatigue ScoresW8−0.61 (p<0.0001)−0.42 (p<0.0001)W16−0.60 (p<0.0001)−0.47 (p<0.0001)W24−0.62 (p<0.0001)−0.50 (p<0.0001)

*Determined by Pearson correlation coefficient; p-values derived from hypothesis tests of correlation ρ=0 (ie, no correlation).

Figure 1

Disclosure of Interests:

Arthur Kavanaugh Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Genentech, Janssen, Eli Lilly, Merck, Novartis, Pfizer and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Genentech, Janssen, Eli Lilly, Merck, Novartis, Pfizer and UCB, Yan Liu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Atul Deodhar Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Galapagos, GSK, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Eli Lilly, GSK, Novartis, Pfizer, UCB, Philip J Mease Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, SUN, and UCB; and personal fees from Boehringer Ingelheim and GlaxoSmithKline, Philip Helliwell Consultant of: Galapagos, Janssen, Novartis, Grant/research support from: Abbvie, Janssen, Pfizer, Laure Gossec Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Biogen, Celgene, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, UCB, Grant/research support from: Amgen, Galapagos, Janssen, Eli Lilly, Pfizer, Sandoz, Sanofi, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Chenglong Han Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Proton Rahman Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Janssen and Novartis.

POS1048 IN PHASE-3 TRIALS DISCOVER 1 & 2, GUSELKUMAB REDUCED FATIGUE OVER 52 WEEKS IN PATIENTS WITH PSORIATIC ARTHRITIS AND DEMONSTRATED INDEPENDENT TREATMENT EFFECTS ON FATIGUE AFTER ADJUSTMENT FOR CLINICAL RESPONSE (ACR20)

Background:

DISCOVER 1 & 2 are phase-3 trials of guselkumab (GUS, an IL-23 inhibitor) in patients with psoriatic arthritis (PsA). In both trials, treatment with GUS led to significantly more improvement than placebo (PBO) in the primary endpoint (American College of Rheumatology 20% improvement criteria [ACR20]) and in other measures of arthritis and psoriasis at week (w) 24,1,2 and these improvements were maintained through 1 year of active treatment.3,4

Objectives:

To evaluate the effect of GUS on fatigue in DISCOVER 1 & 2 using the patient reported outcome (PRO) FACIT-Fatigue, which has demonstrated content validity and strong psychometric properties in clinical trials.5

Methods:

DISCOVER 1 & 2 enrolled patients with active PsA, despite non-biologic DMARDS or NSAIDS, who were biologic naïve except ~30% of patients in DISCOVER 1 who had received 1-2 TNFi. Patients were randomized (1:1:1) in a blinded fashion to subcutaneous GUS 100 mg at w0, w4, then every (q) 8w; GUS 100 mg q4w; or matching PBO. At w24, PBO patients were switched to GUS q4w. Concomitant treatment with select non-biologic DMARDS, oral corticosteroids, and NSAIDs was allowed. The FACIT-Fatigue is a 13-item PRO assessing fatigue and its impact on daily activities and function over the past 7 days, total score ranging from 0 to 52, higher score denoting less fatigue. A change of ≥4 points is considered clinically meaningful.5 The change from baseline in FACIT-Fatigue presented below is based on observed data. Mediation analysis6 was applied to the treatment effect of GUS on FACIT-Fatigue to estimate the natural direct and indirect effects, after adjusting for ACR20 response (Table 1).

Results:

At baseline in DISCOVER 1 & 2, the mean FACIT-fatigue scores (SD) were 30.4 (10.4) and 29.7 (9.7), respectively, indicating that patients with PsA experienced fatigue worse than the general population. At w24 in the DISCOVER trials, treatment with GUS led to significant improvements in FACIT-Fatigue scores compared with PBO, as early as w16 in DISCOVER 1 and w8 in DISCOVER 2. Improvements in fatigue were similar between GUS q4w and q8w doses, and the improvements at w24 were maintained through w52 (Figure 1). After a switch to GUS q4w at w24, PBO patients achieved FACIT-Fatigue scores that were comparable to those of GUS patients (Figure 1). 54%-63% of GUS patients compared with 35%-46% of PBO patients achieved clinically meaningful improvement (≥4 points) in FACIT-Fatigue at w24 (P≤0.003). At w52, 61%-70% of both GUS and PBO to GUS groups reached this improvement. As evaluated by mediation analysis at w24, GUS had independent positive treatment effects on fatigue (12%-36% in the q8w GUS dosing group and 69%-70% in the q4w GUS group) after adjustment for ACR20 response (Table 1).

Conclusion:

In 2 phase-3 trials, GUS treatment improved fatigue when compared to PBO during PBO-controlled periods and maintained improvements through 1 year of active treatment. Substantial proportions of those effects were independent of the effects on ACR20, especially for the q4W dosing group.

References:

[1]Deodhar et al. Lancet 2020;395:1115

[2]Mease et al. Lancet 2020;395:1126

[3]Ritchlin et al. EULAR20. SAT0397

[4]McInnes et al. EULAR20. SAT0402

[5]Cella et al. J Patient-Reported Outcomes 2019;3:30

[6]Valeri et al. Psychologic Meth 2013;18:137

Table 1.

Mediation Analysis: Guselkumab Has Direct Effects and Indirect Effects (Mediated through ACR20) on Fatigue in PsA

EffectGUS 100 mg q8w vs. PBO (95% CI)GUS 100 mg q4w vs. PBO (95% CI)DISCOVER-1Total Effect3.1 (1.0, 5.2)(p<0.02)3.8 (1.9, 5.4)(p<0.02)% Direct Effect11.7%68.5%% Indirect effect mediated by ACR2088.3%31.5%DISCOVER-2Total Effect4.0 (2.4, 5.5)(p<0.02)3.6 (2.1, 5.0)(p<0.02)% Direct Effect36.3%69.7%% Indirect effect mediated by ACR2063.7%30.3%

ACR, American College of Rheumatology; CI, confidence interval; GUS, guselkumab; PBO, placebo; PsA, psoriatic arthritis; q4W, every 4 weeks; q8W, every 8 weeks

Disclosure of Interests:

Proton Rahman Speakers bureau: Received speakers fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Grant/research support from: Received grant/research support from Janssen and Novartis, consultation fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer, Philip Helliwell Consultant of: Consultation fees paid to charity (AbbVie, Amgen, Pfizer, UCB) or himself (Celgene, Galapagos), Grant/research support from: Received grants/research support paid to charity (AbbVie, Janssen, Novartis), Atul Deodhar Speakers bureau: Received speakers fees from AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Consultant of: Received consultation fees from AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Grant/research support from: Received grant/research support from AbbVie, Eli Lilly, GSK, Novartis, Pfizer, UCB, Alexa Kollmeier Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Bei Zhou Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Xiwu Lin Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Chenglong Han Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Philip J Mease Speakers bureau: Received speakers fees from Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB, Consultant of: Received consultation fees from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB, Grant/research support from: Received grant/research support from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB.

POS1027 EFFICACY AND SAFETY OF GUSELKUMAB, A MONOCLONAL ANTIBODY SPECIFIC TO THE p19-SUBUNIT OF INTERLEUKIN-23, THROUGH 2 YEARS: RESULTS FROM A PHASE 3, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED STUDY CONDUCTED IN BIOLOGIC-NAÏVE PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS

Background:

Guselkumab (GUS), a selective IL-23 inhibitor dosed every 4 or 8 weeks (Q4W or Q8W), demonstrated efficacy for joint and skin symptoms, inhibition of structural damage progression (Q4W), and safety vs. placebo (PBO) through Week 24 (W24) of the Ph3, double-blind, PBO-controlled trial in biologic-naïve pts with PsA (DISCOVER-2).1 Favorable benefit-risk was also seen through 1 year.2

Objectives:

To assess GUS efficacy and safety through 2 years.

Methods:

Biologic-naïve adults with active PsA (≥5 swollen joint count [SJC] + ≥5 tender joint count [TJC]; CRP ≥0.6 mg/dL) were randomized (1:1:1) to GUS 100 mg Q4W; GUS 100 mg at W0, W4, Q8W; or PBO with crossover to GUS 100 mg Q4W (PBO→Q4W) at W24. Clinical efficacy (ACR/PASI/IGA/HAQ-DI) was assessed in the modified intention to treat (mITT) population through W100 with missing data imputation (nonresponse for categorical endpoints; no change/multiple imputation for continuous endpoints). Observed PsA-modified van der Heijde Sharp (vdH-S) scores derived from blinded radiographic images collected at W0, W24, W52, W100 (or at discontinuation [d/c]) and adverse events (AEs) through W112 were collected.

Results:

712/739 (96%) randomized pts continued study agent at W24; 687/739 (93%) continued at W52; 652/739 (88%) completed W100. ACR20 response rates in the mITT population continued to increase after W24, and at W100 were 76% for Q4W and 74% for Q8W (Figure 1). Similar response patterns were seen for ACR50/70, HAQ-DI and PASI90/100 (Table 1), and IGA0/1 and PASI75 response rates were consistent through W100 in pts randomized to Q4W and Q8W; W100 data for PBO→Q4W pts were consistent with pts treated with Q4W and Q8W (Table 1). GUS improvements in SF-36 PCS/MCS at W52 also persisted through W100 (data not shown). Low rates of radiographic progression (as measured by PsA-modified vdH-S scores) were observed during W52-100 for Q4W (n=227; 0.75) and Q8W (n=232; 0.46). In the PBO→Q4W group (n=228), radiographic progression was 1.12 during W0-24 (while on PBO), 0.51 during W24-100 (while on Q4W), and 0.13 during W52-100. Through W112, the incidences of AEs, serious AEs (SAEs), AEs leading to d/c, infections, serious infections, and injection site reactions were generally consistent with the PBO-controlled period and through 1 year. Of the pts in the Q4W (n=245), Q8W (n=248), and PBO→Q4W (n=238) groups, 9%, 9% and 7% had ≥1 SAE; 2%, 3% and 3% had ≥1 serious infection; 2 Q8W pts (fungal esophagitis, disseminated herpes zoster) and 1 PBO→Q4W pt (listeria meningitis) had opportunistic infections; 1 PBO→Q4W pt died (road traffic accident); 1 PBO-randomized pt had IBD; no pt had anaphylactic or serum sickness reaction, or active TB.

Conclusion:

In biologic-naïve PsA pts, GUS improvements in joint and skin symptoms, physical function, and low rates of radiographic progression persisted through 2 years. GUS safety in PsA through 2 years was comparable with safety at 6 months and 1 year, similar between Q4W and Q8W, and consistent with GUS safety in psoriasis.

References:

[1]Mease PJ. Lancet. 2020 Apr 4;395(10230):1126-1136. [2] McInnes IB. Arthritis Rheumatol. 2020 Oct 11. doi: 10.1002/art.41553.

Table 1.

Efficacy Through W100 (NRI)

Data are %GUS Q4WGUS Q8WPBO→GUS Q4WW24W52W100W24W52W100W24W52W100Analysis set, n245248246 ACR 50334656324855144148 ACR 7013263519283641830BL HAQ-DI ≥0.35, n228228236Improvement ≥0.35a565963505864314856BL ≥3% BSA psoriasis + IGA ≥2, n184176183 IGA0/1696362715855196367 PASI75788783798682238380PASI90617774697470107277PASI10045585945535335261

BL, Baseline; BSA, Body surface area; HAQ-DI, Health assessment questionnaire disability index; IGA, Investigator global assessment; NRI, nonresponder imputation; PASI, Psoriasis area and severity index. a≥0.35 improvement among pts with HAQ-DI ≥0.35 at BL.

Disclosure of Interests:

Iain McInnes Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Proton Rahman Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Janssen and Novartis, Alice B Gottlieb Consultant of: Avotres Therapeutics, Beiersdorf, Boehringer Ingelheim, Bristol-Myers Squibb Co, Incyte, Janssen, LEO Pharma, Eli Lilly, Novartis, Sun Pharmaceutical Industries Inc, UCB, and Xbiotech, Grant/research support from: Boehringer Ingelheim, Incyte, Janssen, Novartis, Sun Pharmaceuticals Industries Inc, UCB, and Xbiotech, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research and Development, LLC, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Xie L Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Shihong Sheng Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Yusang Jiang Employee of: Cytel, Inc. providing statistical support (funded by Janssen), May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Désirée van der Heijde Paid instructor for: Director of Imaging and Rheumatology BV, Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, Bayer, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, and UCB, Philip J Mease Speakers bureau: Boehringer Ingelheim and GlaxoSmithKline, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, SUN, and UCB.

AB0528 COMPARABLE SAFETY PROFILE OF GUSELKUMAB IN PSORIATIC ARTHRITIS AND PSORIASIS: RESULTS FROM PHASE 3 TRIALS THROUGH 1 YEAR

Background:

DISCOVER 1&2 (PsA) and VOYAGE 1&2 (PsO) are Phase 3 trials of guselkumab (GUS).

Objectives:

Compare safety results through up to 1yr of GUS in PsA and PsO pts.

Methods:

In DISCOVER, 1120 pts with active PsA despite standard therapy were treated. Most pts were biologic-naïve; ~30% in DISCOVER 1 had previous exposure to 1-2 TNFi. Concomitant MTX (57%), oral corticosteroids (17%), and NSAIDs (64%) were permitted. Pts were randomized to SC GUS 100mg at W0, W4, then Q8W; GUS 100mg Q4W; or PBO. At W24, PBO patients were switched to GUS 100mg Q4W. In VOYAGE, in which concomitant MTX use was prohibited, 1245 pts with moderate to severe PsO were treated and randomized to SC GUS 100 mg at W0, W4, W12, then Q8W; or PBO at W0, W4, W12, with crossover to GUS at W16, W20, then Q8W. AEs and laboratory parameters, analyzed by National Cancer Institute-Common Terminology Criteria for AEs [NCI-CTCAE] toxicity grades, were summarized through the PBO-controlled periods and 1yr.

Results:

Safety profiles were generally consistent across the GUS PsO and PsA clinical programs (Table 1). Time-adjusted incidence rates for numbers of AEs, serious AEs, serious infections, malignancy, MACE and AEs leading to d/c were generally similar between PsO and PsA. No cases of anaphylaxis or opportunistic infections were reported. Proportions of pts with decreased neutrophil counts and elevations in hepatic transaminases were slightly higher in PsA vs PsO. These abnormalities were mostly of NCI-CTCAE Grade 1 or 2 (<LLN-1000/mm3 for neutrophils; <5.0 x ULN for AST/ ALT), generally transient, required no medical interventions, resolved spontaneously, and did not lead to interruption or d/c of treatment. Through 1yr, proportions of pts with ALT/AST elevations in PsA trials were slightly higher for GUS Q4W than Q8W and in pts with vs without baseline MTX use.

Conclusion:

The GUS safety profile was generally consistent in PsA and PsO GUS-treated pts through 1yr of the DISCOVER and VOYAGE trials.

Table 1.

Treatment-Emergent AEs During PBO-controlled Period and Through 1Yr: VOYAGE & DISCOVER Trials

Pooled VOYAGE 1&2Pooled DISCOVER 1&2Time PeriodW0-16Through 1YrW0-24bThrough 1Yr(N=)PBO(422)GUS Q8W(823)Combined GUSa(1221)PBOc(372)GUS Q8W(375)GUS Q4W (373)GUS Q8W(375)GUS Q4W (373)Combined GUS† (1100)Total pt-yrs of follow-up128255974173173172384385973Incidence/100 pt-yrs (95% CI)dAEs317 (287,349)330 (308,353)259 (249, 270)219 (198,243)256 (232,281)221 (200, 245)218 (203,233)177 (164,191)191 (182, 199)SAEs5 (2, 10)6 (4, 10)6 (5, 8)9 (5, 15)4 (2, 8)5 (2, 10)6 (4, 9)4 (2, 7)6 (4, 7)AEs leading to study agent d/c3 (0.9, 8)4 (2, 8)2 (2, 4)4 (2, 8)3 (1, 7)7 (4, 12)2 (1, 4)4 (2, 6)3 (2, 5)Infections86 (71, 104)98 (86, 111)98 (92, 104)58 (48, 71)58 (47, 71)63 (51, 76)58 (50, 66)53 (46, 61)55 (50, 60)Serious Infections0. 8 (0, 4)0.4 (0, 2)1 (0.5, 2)4 (2, 8)0.6 (0, 3)2 (0.4, 5)2 (0.6, 3)1 (0, 2)2 (0.9, 3)All Malignancy0 (0, 2)0.4 (0, 2)1 (0.4, 2)0.6 (0, 3)1 (0, 4)0 (0, 2)0.5 (0, 2)0 (0, 0. 8)0 (0, 1)MACE0 (0, 2)0.4 (0, 2)0.4 (0, 1)0.6 (0, 3)0 (0, 2)0.6 (0, 3)0 (0, 0.8)0.3 (0, 1.4)0.1 (0, 0.6)% pts with ≥1 injection site rxn3.14.55.00.31.31.11.62.41.7

aPlacebo crossover pts were included in the combined GUS column after crossover to GUS

bFor all pts who d/c study treatment early with the last dose of PBO/GUS prior to W24 and who did not receive any PBO/GUS at or after Wk24, all data including the final safety follow-up visit collected through 1yr were included

cFor pts in PBO group who switched to GUS due to cross-over or inadvertently, only data prior to first administration of GUS were included.

dCI based on an exact method assuming observed number of events follows a Poisson distribution

Disclosure of Interests:

Alice B Gottlieb Consultant of: Anaptyps Bio, Avotres Therapeutics, Beiersdorf, Boehringer Ingelheim, Bristol-Myers-Squibb, Eli Lilly, Janssen, LEO Pharma, Novartis, Sun Pharmaceuticals, UCB, and Xbiotech, Grant/research support from: Boehringer Ingelheim, Janssen, Novartis, Sun Pharmaceuticals, UCB, and Xbiotech, Joseph F. Merola Consultant of: AbbVie, Arena, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Novartis, Pfizer, Sun Pharma, UCB, April Armstrong Consultant of: AbbVie, Janssen, Lilly, Leo, Novartis, UCB, Ortho Dermatologics, Dermira, KHK, Sanofi, Regeneron, Sun Pharma, BMS, Dermavant, and Modernizing Medicine, Richard Langley Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, LEO Pharma, Merck, Novartis, Pizer, Sun Pharmaceutical, and UCB Pharma, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, LEO Pharma, Merck, Novartis, Pizer, Sun Pharmaceutical, and UCB Pharma, Mark Lebwohl Consultant of: Aditum Bio, Allergan, Almirall, Arcutis, Inc., Avotres Therapeutics, BirchBioMed Inc., BMD skincare, Boehringer-Ingelheim, Bristol-Myers Squibb, Cara Therapeutics, Castle Biosciences, Corrona, Dermavant Sciences, Evelo, Evommune, Facilitate International Dermatologic Education, Foundation for Research and Education in Dermatology, Inozyme Pharma, Kyowa Kirin, LEO Pharma, Meiji Seika Pharma, Menlo, Mitsubishi, Neuroderm, Pfizer, Promius/Dr. Reddy’s Laboratories, Serono, Theravance, and Verrica., Grant/research support from: Abbvie, Amgen, Arcutis, Boehringer Ingelheim, Dermavant, Eli Lilly, Evommune, Incyte, Janssen, Leo Pharmaceutucals, Ortho Dermatologics, Pfizer, and UCB, Christopher E.M. Griffiths Speakers bureau: AbbVie, Amgen, Almirall, BMS, Boehringer Ingelheim Celgene, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Sun Pharma, UCB Pharma., Consultant of: AbbVie, Amgen, Almirall, BMS, Boehringer Ingelheim Celgene, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Sun Pharma, UCB Pharma., Grant/research support from: AbbVie, Amgen, Almirall, BMS, Boehringer Ingelheim Celgene, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Sun Pharma, UCB Pharma., May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Ya-Wen Yang Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Xie L Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Miwa Izutsu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Paraneedharan Ramachandran Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Shihong Sheng Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Yin You Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Megan Miller Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Christopher T. Ritchlin Consultant of: AbbVie, Amgen, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, and UCB Pharma, Iain McInnes Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, and Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Proton Rahman Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Janssen and Novartis.

POS0406 miRNAs DEREGULATED IN RESPONSE TO IL17A INHIBITORS IN PSORIATIC ARTHRITIS REGULATE GENE PRODUCTS IN Rho-GTPase PATHWAYS

Background:

Using transcriptomic data at initiation of therapy, we recently identified differentially expressed genes (DEGs) that separated IL-17Ai response from non-response1. Integration of cell-type-specific DEGs with protein-protein interactions (PPIs) and further comprehensive pathway enrichment analysis revealed Rho GTPase signaling pathway exhibited a strong signal specific to IL-17Ai response and particularly the genes, RAC1 and ROCKs.

Objectives:

To characterize microRNA (miR) profiles among IL-17Ai responders and non-responders, as it relates to RHO GTPase pathway.

Methods:

We interrogated 20 psoriatic arthritis (PsA) patients initiating IL-17Ai. Patients achieving at least low disease activity according to the Disease Activity Index for PsA (DAPSA) at three months were classified as responders. There were seven responders (35%) and thirteen non-responders (65%) in the IL-17Ai group, with biologic treatment naïve (bio-naïve) and previously-exposed (bio-exposed) patients exhibiting a 50% (4/8) and a 25% (3/12) response rate, respectively. For the miR analysis, CD4 positive T cells were isolated from peripheral blood mononuclear cells using DynabeadsTM CD4 beads (ThermoFisher). Total RNA was extracted from the CD4+ T cells using Lexogen’s Split RNA Extraction Kit (D-Mark Biosciences). Libraries were prepared from 200ng total RNA with the NEXTFLEX Small RNA-Seq Kit v3 with UDIs (Bioo Scientific) and sequenced on the Illumina NovaSeq 6000. Raw sequencing fastq data assessed the quality using FastQC. The miRDeep2 was used to trim the adapter, align and quantify human mature miRs from miRbase (Release 22). The abundance of miRs was converted to read counts per million, normalized and limma R package was used to identify pre- and post-differentially expressed miRs.

Results:

We obtained 2,889 miRs. After removing miRs with low reads in >90% of samples, 1902 high quality miRs remained for further analysis. Using mirDIP v4.1 we identified gene targets for differential miRs, and focused on recently identified DEGs related to RHO GTPase pathway. The miRs on the left of the figure 1 are those deregulated in pre-treatment, and the miRs on the right of the figure 1 show the post-treatment deregulated miRs. hsa-miR-3691-5p and hsa-miR-3161 represent the miRs that were deregulated in both conditions. The red highlighted nodes represent the most connected miRs and genes; thus, representing miRs that are the most RHO-pathway centric regulators (hsa-miR-495-3p, 16-5p, 129-5p, 520h, 520g-3p), and genes representing the most strongly regulated RHO-pathway gene products (ROCK1, RHOQ, PFN2, TAOK1, DYNC1L12, MAPRE1, PAFAH1B1, ARHGAP5, MAPK1, CALM1, DIAPH2, PKN2, ITSN1).

Conclusion:

Pre- and post-treatment differential miRs related to IL-17Ai response regulate multiple genes from RHO GTPase pathway.

References:

[1]Rahmati S, O’Rielly DD, Li Q, Codner D, Dohey A, Jenkins K, Jurisica I, Gladman DD, Chandran V, Rahman P. Rho-GTPase pathways may differentiate treatment response to TNF-alpha and IL-17A inhibitors in psoriatic arthritis. Sci Rep. 2020 Dec 10;10(1):21703.

Figure 1.

Disclosure of Interests:

Proton Rahman Speakers bureau: AbbVie, Amgen, BMS, Celgene, Eli Lily, Janssen, Merck, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Celgene, Eli Lily, Janssen, Merck, Novartis, Pfizer, UCB, Grant/research support from: Janssen, Novartis, Quan Li: None declared, Dianne Codner: None declared, Darren O’Rielly: None declared, Amanda Dohey: None declared, Kari Jenkins: None declared, Dafna D Gladman Speakers bureau: AbbVie, Amgen, BMS, Eli Lily, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Eli Lily, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Eli Lily, Janssen, Novartis, Pfizer, UCB, Vinod Chandran Speakers bureau: AbbVie, Amgen, BMS, Eli Lily, Janssen, Novartis, Pfizer, UCB, Paid instructor for: AbbVie, Amgen, BMS, Eli Lily, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Eli Lily, Employee of: Spousal Employment Eli Lilly, Igor Jurisica: None declared

POS1028 PATIENT CHARACTERISTICS & CLINICAL FEATURES ASSOCIATE WITH HEALTH-RELATED QUALITY OF LIFE IN BIO-NAÏVE PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS THROUGH WEEK 24 OF THE DISCOVER-2 STUDY

Background:

Psoriatic arthritis (PsA) is a chronic inflammatory disease characterized by peripheral arthritis, axial inflammation, dactylitis, enthesitis, & skin/nail psoriasis. Patients (pts) with PsA often experience reduced health-related quality of life (HRQoL) due to these features.

Objectives:

Using EuroQoL-5 dimension-5 level (EQ-5D-5L) questionnaire index & visual analog scale (EQ-VAS) scores, we assessed HRQoL in pts with PsA & its association with pt characteristics & clinical features of PsA, including fatigue.

Methods:

The Phase 3 DISCOVER-2 trial evaluated guselkumab (GUS), a human monoclonal antibody targeting the IL-23p19-subunit, in bio-naïve adults with active PsA (swollen joint count [SJC] ≥5, tender joint count [TJC] ≥5, C-reactive protein [CRP] ≥0.6 mg/dL) despite standard therapies.1 Pts were randomized 1:1:1 to GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at Week 0 (W0), W4, then Q8W; or placebo (PBO). EQ-5D-5L index assesses mobility, self-care, usual activities, pain/discomfort, & anxiety/depression. EQ-VAS assesses pt health state. Spearman correlation testing was used to evaluate relationships between baseline (BL) pt characteristics & PsA clinical features & BL EQ-5D-5L index & EQ-VAS scores (Figure 1). Employing absolute observed scores at both W0 & W24, univariate linear regression was used to assess the association between EQ-5D-5L index & EQ-VAS scores & pt characteristics/PsA clinical features. Variables with p<0.20 in the univariate analysis were included in a multivariate analysis employing mixed-effect model for repeated measures (MMRM), controlling for all other variables; resulting p values <0.05 were considered statistically significant. Least-squares (LS) mean changes in EQ-5D-5L index & EQ-VAS were assessed at W24 using MMRM.

Results:

Among 738 pts, BL EQ-5D-5L index & EQ-VAS scores were moderately to strongly correlated (ie, ≥0.4) with BL pt-reported pain (0-10 VAS), physical function (Health Assessment Questionnaire-Disability Index [HAQ-DI]), fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-F] scale), & 36-item Short Form Health Survey (SF-36) physical & mental component summary (PCS & MCS) scores & weakly correlated with other variables (Figure 1). Based on univariate analyses (p<0.20) & evaluation of collinearity between variables, attributes at W0 & W24 included in the multivariate models were age, sex, CRP, FACIT-F, pain, psoriasis area & severity index (PASI) score, TJC, SJC, enthesitis, & dactylitis. In the final model, CRP, FACIT-F, pain, PASI score, & the presence of dactylitis were significantly associated with EQ-5D-5L index & EQ-VAS scores. A higher TJC was significantly associated with a worse EQ-5D-5L index score. A higher SJC was significantly associated with a worse EQ-VAS score (Table 1). For reference, in the GUS Q4W (N=244), GUS Q8W (N=246), & PBO (N=244) groups, the LS mean changes from baseline at W24 were 0.12, 0.12, & 0.05, respectively, for EQ-5D-5L index & 18.1, 18.4, & 6.8, respectively, for EQ-VAS.

Conclusion:

Joint & skin symptoms, dactylitis, fatigue, pain, & elevated levels of CRP were significantly associated with reduced HRQoL (measured by EQ-5D-5L index & EQ-VAS) in bio-naïve pts with active PsA. Treatment of multiple PsA domains may help optimize HRQoL. Improvement across clinical domains1 & in HRQoL has been observed in GUS-treated pts with PsA.

References:

[1]Mease P, et al. Lancet 2020;395:1126-36.

Table 1.

Multivariate analysis of pt characteristics/clinical features & EQ-5D-5L index & EQ-VAS scores at W0 & W24

ParameterEQ-5D-5L IndexEQ-VASEstimatep valueEstimatep valueAge (y)-0.00010.690.060.12Female-0.0030.531.110.20CRP (mg/dL)-0.005<0.001-0.510.007FACIT-F (0-52)0.007<0.0010.57<0.001Pain (0-10)-0.02<0.001-3.47<0.001PASI (0-72)-0.0010.03-0.17<0.001SJC (0-66)-0.0010.21-0.170.02TJC (0-68)-0.0010.04-0.040.41Dactylitis (Y/N)0.010.021.740.49Enthesitis (Y/N)-0.0040.33-0.980.22

Disclosure of Interests:

Jeffrey Curtis Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Eli Lilly, Janssen, Myriad, Pfizer, Regeneron, Roche, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Eli Lilly, Janssen, Myriad, Pfizer, Regeneron, Roche, and UCB, Iain McInnes Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, and UCB, Dafna D Gladman Consultant of: Abbvie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer and UCB, Grant/research support from: Abbvie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer and UCB, Feifei Yang Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Steve Peterson Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Prasheen Agarwal Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Chenglong Han Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, William Tillett Speakers bureau: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, MSD, Pfizer, and UCB, Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, Novartis, Philip J Mease Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Novartis, Pfizer, SUN, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, SUN, and UCB, Proton Rahman Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Janssen and Novartis.

POS0200 CLINICAL CHARACTERISTICS & OUTCOMES ASSOCIATE WITH WORK PRODUCTIVITY IN BIO-NAÏVE PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS THROUGH WEEK 24 OF THE DISCOVER-2 STUDY

Background:

Psoriatic arthritis (PsA), a chronic inflammatory disease characterized by peripheral arthritis, axial inflammation, dactylitis, enthesitis & skin/nail psoriasis, causes impaired physical function, disability & loss of work productivity.

Objectives:

Evaluate associations between PsA clinical characteristics & outcomes including fatigue & work productivity using Work Productivity & Activity Impairment Questionnaire: PsA (WPAI-PsA).

Methods:

The Phase 3 DISCOVER-2 trial assessed guselkumab (GUS), an anti-IL-23p19 subunit monoclonal antibody, in bio-naïve adults with active PsA (swollen joint count [SJC] ≥5 & tender joint count [TJC] ≥5, C-reactive protein [CRP] ≥0.6 mg/dL) despite standard therapies.1 Patients (Pts) were randomized 1:1:1 to GUS 100 mg Q4W; GUS 100 mg at W0, W4, then Q8W; or placebo (PBO). WPAI-PsA assesses PsA-related work time missed (absenteeism), impairment while working (presenteeism), productivity loss (absenteeism+presenteeism), & daily activity during the previous week. Spearman correlation testing evaluated relationships between pt demographics & disease characteristics of PsA & WPAI domain scores based on observed values at baseline. Univariate linear regression assessed associations between WPAI & these variables based on observed data at W0 & at W24. Variables with p<0.10 were included in a multivariate analysis employing a mixed-effects model for repeated measures, controlling for all other variables; resulting p-values <0.05 were considered statistically significant.

Results:

As reported elsewhere,2 least-squares mean % changes from baseline at W24 were -3.8/-19.5/-20.0/-20.5 for GUS Q4W, -3.1/-19.4/-19.7/-21.5 for GUS Q8W, & -3.5/-10.2/-10.9/-10.3 for PBO for absenteeism, presenteeism, absenteeism+presenteeism, & daily activity impairment, respectively. Among 738 pts, WPAI domain scores were moderately to strongly correlated (ie, ≥0.4) with pt-reported pain (0-10 visual analog scale), physical function (Health Assessment Questionnaire Disability Index [HAQ-DI]), fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-F] scale) & 36-Item Short Form Health Survey (SF-36) Physical Component Summary (PCS) score, but weakly correlated with other variables (Figure 1). Based on univariate analyses & evaluation of collinearity between variables, attributes included in multivariate models were age, body mass index (BMI), gender, CRP, FACIT-F, pain, Psoriasis Area Severity Index (PASI), TJC, SJC, enthesitis & dactylitis. In final model, CRP, FACIT-F, & pain were statistically significantly associated with all WPAI domains (Table 1). Presence of enthesitis & higher PASI score were significantly associated with higher loss of work productivity & activity outside work.

Conclusion:

In PsA pts, extra-articular symptoms, fatigue, pain & elevated CRP were significantly associated with WPAI-assessed work & activity impairment. Treating all major clinical manifestations of PsA is needed to help pts improve work & activity impairment. GUS effectively treats all major clinical manifestations1 & improves work & activity impairment in PsA.2

References:

[1]Mease P. Lancet 2020;395:1126-36.

[2]Curtis J. ACR 2020; Poster 0332.

Table 1.

Multivariate analysis of clinical characteristics/outcomes & WPAI domains at W0 & W24

ParameterAbsenteeismaPresenteeismaProductivity LossaActivity ImpairmentbEstimatep-valueEstimatep-valueEstimatep-valueEstimatep-valueAge-0.050.42-0.27<0.001-0.28<0.001-0.060.17Female0.910.46-1.540.22-1.740.202.380.02CRP0.730.040.970.011.010.010.89<0.001FACIT-F-0.31<0.001-0.67<0.001-0.73<0.001-0.75<0.001Pain1.03<0.0014.15<0.0014.25<0.0014.02<0.001PASI0.060.360.160.020.140.050.150.003SJC0.080.48-0.050.61-0.050.660.030.75TJC-0.100.130.110.090.090.190.100.04Dactylitis (Y/N)-1.100.392.470.052.580.050.540.57Enthesitis (Y/N)1.520.202.380.042.990.012.400.01

aPts working at baseline

bAll pts in study

Disclosure of Interests:

Jeffrey Curtis Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Eli Lilly, Myriad, Pfizer, Regeneron, Roche, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Eli Lilly, Myriad, Pfizer, Regeneron, Roche, and UCB, Iain McInnes Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, and UCB, Dafna D Gladman Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer and UCB, Feifei Yang Shareholder of: Janssen, Employee of: Janssen, Steve Peterson Shareholder of: Janssen, Employee of: Janssen, Prasheen Agarwal Shareholder of: Janssen, Employee of: Janssen, Alexa Kollmeier Shareholder of: Janssen, Employee of: Janssen, Elizabeth C Hsia Shareholder of: Janssen, Employee of: Janssen, Chenglong Han Shareholder of: Janssen, Employee of: Janssen, May Shawi Shareholder of: Janssen, Employee of: Janssen, William Tillett Speakers bureau: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, MSD, Pfizer, and UCB, Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, and Novartis, Philip J Mease Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Novartis, Pfizer, SUN, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, SUN, and UCB, Proton Rahman Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Janssen and Novartis