Use of Quantitative CT Imaging to Identify Bronchial Thermoplasty Responders

BACKGROUND

Bronchial thermoplasty (BT) is a treatment for patients with poorly controlled, severe asthma. However, predictors of treatment response to BT are defined poorly.

RESEARCH QUESTION

Do baseline radiographic and clinical characteristics exist that predict response to BT?

STUDY DESIGN AND METHODS

We conducted a longitudinal prospective cohort study of participants with severe asthma receiving BT across eight academic medical centers. Participants received three separate BT treatments and were monitored at 3-month intervals for 1 year after BT. Similar to prior studies, a positive response to BT was defined as either improvement in Asthma Control Test results of ≥ 3 or Asthma Quality of Life Questionnaire of ≥ 0.5. Regression analyses were used to evaluate the association between pretreatment clinical and quantitative CT scan measures with subsequent BT response.

RESULTS

From 2006 through 2017, 88 participants received BT, with 70 participants (79.5%) identified as responders by Asthma Control Test or Asthma Quality of Life Questionnaire criteria. Responders were less likely to undergo an asthma-related ICU admission in the prior year (3% vs 25%; P = .01). On baseline quantitative CT imaging, BT responders showed less air trapping percentage (OR, 0.90; 95% CI, 0.82-0.99; P = .03), a greater Jacobian determinant (OR, 1.49; 95% CI, 1.05-2.11), greater SD of the Jacobian determinant (OR, 1.84; 95% CI, 1.04-3.26), and greater anisotropic deformation index (OR, 3.06; 95% CI, 1.06-8.86).

INTERPRETATION

To our knowledge, this is the largest study to evaluate baseline quantitative CT imaging and clinical characteristics associated with BT response. Our results show that preservation of normal lung expansion, indicated by less air trapping, a greater magnitude of isotropic expansion, and greater within-lung spatial variation on quantitative CT imaging, were predictors of future BT response.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT01185275; URL: www.

CLINICALTRIALS

gov.

A naturally occurring variant of MBD4 causes maternal germline hypermutation in primates

As part of an ongoing genome sequencing project at the Oregon National Primate Research Center, we identified a rhesus macaque with a rare homozygous frameshift mutation in the gene methyl-CpG binding domain 4, DNA glycosylase (MBD4). MBD4 is responsible for the repair of C > T deamination mutations at CpG dinucleotides and has been linked to somatic hypermutation and cancer predisposition in humans. We show here that MBD4-associated hypermutation also affects the germline: The six offspring of the MBD4-null dam have a fourfold to sixfold increase in de novo mutation burden. This excess burden was predominantly C > T mutations at CpG dinucleotides consistent with MBD4 loss of function in the dam. There was also a significant excess of C > T at CpA sites, indicating an important, unappreciated role for MBD4 to repair deamination in CpA contexts. The MBD4-null dam developed sustained eosinophilia later in life, but we saw no other signs of neoplastic processes associated with MBD4 loss of function in humans nor any obvious disease in the hypermutated offspring. This work provides the first evidence for a genetic factor causing hypermutation in the maternal germline of a mammal and adds to the very small list of naturally occurring variants known to modulate germline mutation rates in mammals.

Parallel neurodegenerative phenotypes in sporadic Parkinson's disease fibroblasts and midbrain dopamine neurons

Understanding the mechanisms causing Parkinson's disease (PD) is vital to the development of much needed early diagnostics and therapeutics for this debilitating condition. Here, we report cellular and molecular alterations in skin fibroblasts of late-onset sporadic PD subjects, that were recapitulated in matched induced pluripotent stem cell (iPSC)-derived midbrain dopamine (DA) neurons, reprogrammed from the same fibroblasts. Specific changes in growth, morphology, reactive oxygen species levels, mitochondrial function, and autophagy, were seen in both the PD fibroblasts and DA neurons, as compared to their respective controls. Additionally, significant alterations in alpha synuclein expression and electrical activity were also noted in the PD DA neurons. Interestingly, although the fibroblast and neuronal phenotypes were similar to each other, they differed in their nature and scale. Furthermore, statistical analysis revealed potential novel associations between various clinical measures of the PD subjects and the different fibroblast and neuronal data. In essence, these findings encapsulate spontaneous, in-tandem, disease-related phenotypes in both sporadic PD fibroblasts and iPSC-based DA neurons, from the same patient, and generates an innovative model to investigate PD mechanisms with a view towards rational disease stratification and precision treatments.

Tezepelumab and Mucus Plugs in Patients with Moderate-to-Severe Asthma

Tezepelumab and Mucus Plugs in Patients with AsthmaMucus plugs in airways of asthma patients are associated with airway obstruction and the activity of inflammatory cytokines. This article reports prespecified and post hoc analyses of the effect of tezepelumab treatment on mucus plugs identified by computed tomography imaging in patients with moderate-to-severe asthma. At baseline, mucus plug scores correlated positively with levels of inflammatory biomarkers and negatively with lung function measures. Patients treated with tezepelumab had resolution of more mucus plugs than patients taking placebo.

Parallel Neurodegenerative Phenotypes in Sporadic Parkinson's Disease Fibroblasts and Midbrain Dopamine Neurons

Understanding the mechanisms causing Parkinson's disease (PD) is vital to the development of much needed early diagnostics and therapeutics for this debilitating condition. Here, we report cellular and molecular alterations in skin fibroblasts of late-onset sporadic PD subjects, that were recapitulated in matched induced pluripotent stem cell (iPSC)-derived midbrain dopamine (DA) neurons, reprogrammed from the same fibroblasts. Specific changes in growth, morphology, reactive oxygen species levels, mitochondrial function, and autophagy, were seen in both the PD fibroblasts and DA neurons, as compared to their respective controls. Additionally, significant alterations in alpha synuclein expression and electrical activity were also noted in the PD DA neurons. Interestingly, although the fibroblast and neuronal phenotypes were similar to each other, they also differed in their nature and scale. Furthermore, statistical analysis revealed novel associations between various clinical measures of the PD subjects and the different fibroblast and neuronal data. In essence, these findings encapsulate spontaneous, in-tandem, disease-related phenotypes in both sporadic PD fibroblasts and iPSC-based DA neurons, from the same patient, and generates an innovative model to investigate PD mechanisms with a view towards rational disease stratification and precision treatments.

Temperature-controlled Laminar Airflow (TLA) in symptomatic severe asthma – a post hoc analysis of severe exacerbations, quality of life and health economics

Purpose

Uncontrolled severe asthma constitutes a major economic burden to society. Add-ons to standard inhaled treatments include inexpensive oral corticosteroids and expensive biologics. Nocturnal treatment with Temperature-controlled Laminar Airflow (TLA; Airsonett®) could be an effective, safe and cheaper alternative. The potential of TLA in reducing severe asthma exacerbations was addressed in a recent randomised placebo-controlled trial (RCT) in patients with severe asthma (Global Initiative for Asthma (GINA) step 4/5), but the results were inconclusive. We re-analysed the RCT with severe exacerbations stratified by the level of baseline asthma symptoms and Quality of Life.

Methods

More uncontrolled patients, defined by Asthma Control Questionnaire 7 (ACQ7) > 3, EuroQoL 5-Dimension Questionnaire Visual Analogue Scale (EQ5D-VAS) ≤ 65 and Asthma Quality of Life Questionnaire (AQLQ) ≤ 4 were selected for re-analysis. The rates of severe asthma exacerbations, changes in QoL and health-economics were analysed and compared between TLA and placebo.

Results

The study population included 226 patients (113 TLA / 113 placebo.) The rates of severe asthma exacerbations were reduced by 33, 31 and 25% (p = 0.083, 0.073, 0.180) for TLA compared to placebo, dependent on selected control measures (ACQ7, EQ5D-VAS, AQLQ, respectively). For patients with less control defined by AQLQ≤4, the difference in mean AQLQ0-12M between TLA and placebo was 0.31, 0.33, 0.26 (p = 0.085, 0.034, 0.150), dependent on selected covariate (AQLQ, EQ5D-VAS, ACQ7, respectively). For patients with poor control defined by ACQ7 > 3, the difference in EQ5D-5 L utility scores between TLA and placebo was significant at 9 and 12 months with a cost-effective ICER. The results from the original study did not demonstrate these differences.

Conclusion

This post hoc analysis demonstrated an effect of TLA over placebo on severe exacerbations, asthma control and health economics in a subgroup of patients with more symptomatic severe allergic asthma. The results are consistent with the present recommendations for TLA. However, these differences were not demonstrated in the full study. Several explanations for the different outcomes have been outlined, which should be addressed in future studies.

Funding

NIHR Health Technology Assessment Programme and Portsmouth Hospitals NHS Trust.

Inpatient Hospitalizations for Firearm Injury: Estimating State-Level Rates from 2000 to 2016

One particular challenge for gun policy researchers is the lack of a single resource that provides reliable estimates of state-level firearm injuries over time. The data that do exist are sparse across state-years and cost-prohies affect deaths and injuries in the same manner. As part of the Gun Policy in America initiative, RAND researchers developed a publicly available longitudinal database of state-level estimates of inpatient hospitalizations that occur as a result of firearm injury. This article describes the methods that the researchers used to construct the estimates and provides technical documentation and other information that will facilitate use of the database.

Esophageal Dysmotility Is Associated With Disease Severity in Eosinophilic Esophagitis

BACKGROUND & AIMS

An association of eosinophilic esophagitis (EoE) with esophageal dysmotility has been described, however, the related mechanism remains unclear. We aimed to evaluate clinical and physiologic characteristics, including esophageal distensibility, associated with secondary peristalsis in patients with EoE.

METHODS

A total of 199 consecutive adult patients with EoE (age, 18-78 y; 32% female) who completed a 16-cm functional luminal imaging probe (FLIP) during endoscopy were evaluated in a cross-sectional study. FLIP panometry contractile response (CR) patterns were classified as normal CR or borderline CR if antegrade contractions were present, and abnormal CRs included impaired/disordered CR, absent CR, or spastic-reactive CR. The distensibility plateau of the esophageal body and esophagogastric junction distensibility was measured with FLIP.

RESULTS

FLIP CR patterns included 68 (34%) normal CR, 65 (33%) borderline CR, 44 (22%) impaired/disordered CR, 16 (8%) absent CR, and 6 (3%) spastic-reactive CR. Compared with normal CRs, abnormal CRs more frequently had reduced esophageal distensibility (distensibility plateau <17 mm in 56% vs 32%), greater total EoE reference scores (median, 5; interquartile range [IQR], 3-6 vs median, 4; IQR, 3-5) with more severe ring scores, and a greater duration of symptoms (median, 10 y; IQR, 4-23 y vs median, 7 y; IQR, 3-15 y). Mucosal eosinophil density, however, was similar between abnormal CRs and normal CRs (median, 34 eosinophils/high-power field [hpf]; IQR, 14-60 eosinophils/hpf vs median, 25 eosinophils/hpf; IQR, 5-50 eosinophils/hpf).

CONCLUSIONS

Although normal secondary peristalsis was observed frequently in this EoE cohort, abnormal esophageal CRs were related to EoE disease severity, especially features of fibrostenosis. This study evaluating secondary peristalsis in EoE suggests that esophageal wall remodeling, rather than eosinophilic inflammatory intensity, was associated with esophageal dysmotility in EoE.

Do changes in primary care service use over time differ by neighbourhood income? Population-based longitudinal study in British Columbia, Canada

Background

Strong primary care systems have been associated with improved health equity. Primary care system reforms in Canada may have had equity implications, but these have not been evaluated. We sought to determine if changes in primary care service use between 1999/2000 and 2017/2018 differ by neighbourhood income in British Columbia.

Methods

We used linked administrative databases to track annual primary care visits, continuity of care, emergency department (ED) visits, specialist referrals, and prescriptions dispensed over time. We use generalized estimating equations to examine differences in the magnitude of change by neighbourhood income quintile, adjusting for age, sex/gender, and comorbidity, and stratified by urban/rural location of residence. We also compared the characteristics of physicians providing care to people living in low- and high-income neighbourhoods at two points in time.

Results

Between 1999/2000 and 2017/8 the average number of primary care visits per person, specialist referrals, and continuity of care fell in both urban and rural settings, while ED visits and prescriptions dispensed increased. Over this period in urban settings, primary care visits, continuity, and specialist referrals fell more rapidly in low vs. high income neighbourhoods (relative change in primary care visits: Incidence Rate Ratio (IRR) 0.881, 95% CI: 0.872, 0.890; continuity: partial regression coefficient -0.92, 95% CI: -1.18, -0.66; specialist referrals: IRR 0.711, 95%CI: 0.696, 0.726), while ED visits increased more rapidly (IRR 1.06, 95% CI: 1.03, 1.09). The percentage of physicians who provide the majority of visits to patients in neighbourhoods in the lower two income quintiles declined from 30.6% to 26.3%.

Conclusion

Results raise concerns that equity in access to primary care has deteriorated in BC. Reforms to primary care that fail to attend to the multidimensional needs of low-income communities may entrench existing inequities. Policies that tailor patterns of funding and allocation of resources in accordance with population needs, and that align accountability measures with equity objectives are needed as part of further reform efforts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-022-01679-4.

AB0888 Guselkumab Provides Sustained Improvements in Work Productivity and Daily Activity in Patients With Active Psoriatic Arthritis Through 2 Years of DISCOVER-2

Background

Psoriatic arthritis (PsA) impacts patients’ (pts) work productivity (WP) and daily activity.1 DISCOVER-2 (D2), a Phase 3 trial of the selective interleukin-23 p19-subunit inhibitor guselkumab (GUS) in biologic-naïve pts with PsA,2 demonstrated significant improvements in pt-reported WP and daily activity following 1 year (Y) of GUS treatment.3

Objectives

Assess WP and daily activity impairment in D2 pts through 2Y. Estimate indirect savings associated with GUS treatment and assess changes in employment status.

Methods

Pts with active PsA received GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4, then Q8W; or placebo (PBO). At W24, PBO pts crossed over to GUS 100 mg Q4W. WPAI-PsA assesses PsA-related work time missed (absenteeism), impairment while working (presenteeism), and impaired overall WP (absenteeism + presenteeism) for pts employed at baseline (EBL) and daily activity for all pts, including those unemployed at baseline (UBL) during the previous week. Mean changes in WPAI-PsA domains were calculated for each multiple imputation (MI) dataset using an analysis of covariance (ANCOVA); the reported LS mean is the average of all MI datasets. Significance was defined as p<0.05. Among pts EBL, potential indirect savings from improved overall WP were estimated using 2020 European Union mean yearly wage estimate (all occupations) combined with LS mean change from BL in WPAI-PsA overall work impairment.4 A shift analysis evaluated proportions of pts employed vs unemployed by treatment group using observed data over time.

Results

Pts EBL comprised 64% of the analysis cohort. Significant improvements in WP in pts EBL and in daily activity among all pts were observed with GUS Q4W/Q8W vs PBO at W24;3 mean improvements in WP and daily activity increased with continued GUS through 2Y (Table 1). Potential annual indirect savings from improved overall WP in pts EBL were €10,826 GUS Q4W, €12,712 GUS Q8W, and €10,948 PBO→ GUS Q4W at 2Y. Shift analysis showed relatively stable employment in pts EBL with GUS up to 2Y (>83% continued to work). Among pts UBL (36% of cohort), the proportion of pts employed increased by >20% through 2Y of GUS (Figure 1).

Table 1.

Model-Based Estimates of Change From BL in WPAI-PsA Domains1

GUS 100mg Q4WGUS 100mg Q8WPBO (W0-24) → GUS 100 mg Q4W (W24-100)VisitW24W100W24W100W24W100Absenteeism, N145147147149162166  LS Mean (95% CI)-3.4 (-6.5, -0.3)-1.8 (-4.5, 0.9)-3.0 (-6.0, 0.1)-4.2 (-6.8,-1.5)-3.0 (-6.0, 0.04)-4.2 (-6.8,-1.6)  Diff vs. PBO-0.4 (-4.6, 3.8)--0.01 (-4.2, 4.2)---Presenteeism, N145147147149162166  LS Mean (95% CI)-20.1 (-23.7, -16.6)-26.3 (-30.1,-22.5)-19.6 (-23.2, -16.1)-28.0 (-31.8, -24.2)-10.5 (-13.9, -7.0)-24.2 (-27.9, -20.5)  Diff vs PBO-9.7* (-14.4, -5.0)--9.2* (-13.9, -4.5)---Work productivity, N145147147149162166  LS Mean (95% CI)-20.1 (-24.1, -16.1)-23.8 (-28.0, -19.6)-19.2 (-23.1, -15.2)-28.0 (-32.1, -23.8)-10.6 (-14.4, -6.8)-24.1 (-28.1, -20.1)  Diff vs PBO-9.5* (-14.8, -4.2)--8.6* (-13.9, -3.3)---Daily Activity, N242242246246245245  LS Mean (95% CI)-20.5 (-23.3, -17.7)-29.2 (-32.2, -26.1)-21.2 (-23.9, -18.4)-28.0 (-31.0, -24.9)-9.9 (-12.6, -7.1)-26.6 (-29.6, -23.6)  Diff vs PBO-10.6* (-14.4, -6.8)--11.3* (-15.1, -7.5)-

1Mean changes in WPAI-PsA domains were calculated for each MI dataset using an ANCOVA; reported LS mean (95% confidence interval [CI]) = average of all MI datasets.

*p<0.002

Conclusion

In GUS-treated bio-naïve PsA pts, robust improvements in WP and daily activity seen at W24 were maintained and increased through 2Y of GUS. Long-term improvements in WP achieved may result in substantial indirect cost savings for GUS-treated pts. Rates of employment remained stable in pts employed and increased in those unemployed at BL.

References

[1]Tillett W et al. Rheumatol (Oxford). 2012;51:275–83.

[2]Mease PJ, et al. Lancet. 2020;395:1126–36.

[3]Curtis JR et al. EULAR, June 2–5, 2021. POS1026.

[4]OECD (2020). Average wages (indicator). https://data.oecd.org/earnwage/average-wages.htm

Disclosure of Interests

Jeffrey Curtis Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, CorEvitas, Eli Lilly and Company, Janssen, Myriad, Novartis, Pfizer, Sanofi, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, CorEvitas, Eli Lilly and Company, Janssen, Myriad, Novartis, Pfizer, Sanofi, and UCB, Iain McInnes Shareholder of: Causeway Therapeutics, and Evelo Compugen, Consultant of: Astra Zeneca, AbbVie, Bristol-Myers Squibb, Amgen, Eli Lilly and Company, Cabaletta, Compugen, GSK, Gilead, Janssen, Novartis, Pfizer, Sanofi, Roche, and UCB, Grant/research support from: Astra Zeneca, Bristol-Myers Squibb, Amgen, Eli Lilly and Company, GSK, Janssen, Novartis, Roche, and UCB, Proton Rahman Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: Janssen and Novartis, Dafna D Gladman Consultant of: Abbvie, Amgen, BMS, Eli Lilly, Galapagos, Gilead, janssen, Novartis, Pfizer and UCB., Grant/research support from: Abbvie, Amgen, Eli Lilly, Janssen, Pfizer, 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, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Natalie Shiff Shareholder of: Johnson & Johnson, Abbvie, Gilead, Employee of: Janssen Scientific Affairs, LLC, Chenglong Han Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Immunology Global Medical Affairs, Janssen Pharmaceutical Companies, William Tillett Speakers bureau: Abbvie, Amgen, Eli-Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Consultant of: Abbvie, Amgen, Eli-Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Grant/research support from: Abbvie, Amgen, Eli-Lilly, Janssen, and UCB, Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Consultant of: AbbVie, Aclaris, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, Sun Pharma, and UCB

AB0896 Comparative Effectiveness of Guselkumab in Psoriatic Arthritis: Updates to a Systematic Literature Review and Network Meta-Analysis

Background

The efficacy of guselkumab (GUS), an interleukin (IL)-23 p19-subunit inhibitor, has been demonstrated for psoriatic arthritis (PsA) in two pivotal phase 3 trials (DISCOVER‑1&2). A third phase 3b trial (COSMOS) evaluated GUS in patients with PsA who had an inadequate response (IR) to tumor necrosis factor inhibitors (TNFi). GUS has previously been compared to targeted PsA therapies through network meta-analysis (NMA).

Objectives

This NMA update was to include data for GUS in TNFi-IR patients from COSMOS, as well as two additional key comparators, risankizumab (RIS), an IL-23 inhibitor, and upadacitinib (UPA), a Janus kinase inhibitor (JAKi).

Methods

A systematic literature review identified PsA randomized controlled trials up to February 2021. A subsequent hand-search identified data for newer agents, including congresses up to July 2021. Bayesian NMAs were performed to compare treatments on American College of Rheumatology (ACR) response, Psoriasis Area and Severity Index (PASI) response, modified van der Heijde-Sharp (vdH-S) score, and serious adverse events (SAEs). Analyses used fixed or random effects models and adjusted for placebo response via meta-regression on baseline risk when feasible. Multinomial models were used for ACR and PASI. Results were summarized by ranking treatments in league tables according to results derived from NMAs. Conclusions (ie, comparable or better/worse) for GUS 100 mg every 8/4 weeks (Q8W/Q4W) versus comparators were based on overlap of pairwise 95% credible intervals (CrIs) (ie, treatments are comparable if CrIs overlap 1 [dichotomous outcomes] or 0 [continuous outcomes]).

Results

Thirty-three phase 3 studies were included in the NMAs. Studies were placebo-controlled up to 24 weeks except for 2 head-to-head studies, and evaluated 15 targeted PsA therapies in TNFi naïve, IR, or mixed populations. For ACR 20 response, GUS Q8W and Q4W ranked 14th and 12th among 23 treatments and were comparable to most other active agents, including RIS and UPA, subcutaneous (SC) TNFi, and most IL-17A inhibitors (IL-17Ai), as demonstrated by overlap in pairwise 95% CrIs with unity. Results were similar for ACR 50 and 70 responses. For PASI 90, GUS Q8W and Q4W ranked 2nd and 1st among 23 treatments and were better than multiple agents, including all SC TNFi, JAKi, including UPA, and other small molecules, as demonstrated by nonoverlap in pairwise 95% Crls with unity. GUS Q8W and Q4W were similar to RIS and most IL-17Ai for PASI 90, but point estimates consistently favored GUS. For vdH-S score, GUS Q8W and Q4W ranked 8th and 3rd among 18 treatments; GUS Q4W was better than RIS, and both GUS Q8W and Q4W were comparable to most other agents, including UPA. SAEs were comparable across most agents.

Conclusion

GUS demonstrated better skin efficacy than most other targeted PsA therapies, including UPA. For vdH-S, both GUS dose regimens were comparable to most treatments, with both GUS dose regimens ranking higher than most, including UPA and RIS. Both GUS dose regimens demonstrated ACR responses that were comparable to most other agents, including UPA and RIS, and ranked favorably in the network for SAEs.

References

None

Disclosure of Interests

Philip J Mease Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Sun Pharma, and UCB Pharma, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Sun Pharma, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Sun Pharma, and UCB Pharma, Iain McInnes Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, and UCB Pharma, Lai-Shan Tam Grant/research support from: Novartis and Pfizer, Raji Rajalingam Employee of: EVERSANA, Steve Peterson Shareholder of: may own stock or stock options in Johnson & Johnson, Employee of: Janssen Global Services, LLC, Fareen Hassan Shareholder of: may own stock or stock options in Johnson & Johnson, Employee of: Janssen EMEA, Soumya D Chakravarty Shareholder of: may own stock or stock options in Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Christine CONTRE Shareholder of: may own stock or stock options in Johnson & Johnson, Employee of: Janssen Pharmaceutical Companies of Johnson & Johnson, France, Alison Armstrong Employee of: EVERSANA, Wolf-Henning Boehncke Speakers bureau: AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Leo, Novartis, and UCB Pharma, Consultant of: AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Leo, Novartis, and UCB Pharma, Grant/research support from: Pfizer, Christopher T. Ritchlin Consultant of: AbbVie, Amgen, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen and UCB Pharma

AB0881 Guselkumab Provides Sustained Improvements in Health-Related Quality of Life in Patients With Active Psoriatic Arthritis Through 2 Years of DISCOVER-2

Background

Psoriatic arthritis (PsA), a chronic inflammatory disease characterized by peripheral arthritis, axial inflammation, dactylitis, enthesitis, and skin/nail psoriasis, is associated with reduced health-related quality of life (HRQoL).

Objectives

To assess long-term effect of guselkumab (GUS), a human monoclonal antibody that selectively targets the interleukin (IL)-23p19 subunit, on HRQoL of bio-naïve PsA patients (pts) who participated in the Phase 3 2-year DISCOVER-2 trial.1

Methods

Pts with active PsA despite nonbiologic disease-modifying antirheumatic drugs (DMARDs) and/or nonsteroidal anti-inflammatory drugs (NSAIDs) received GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4, then Q8W; or placebo (PBO). At W24, PBO pts crossed over to GUS 100 mg Q4W. HRQoL was assessed using the pt-reported EuroQoL-5 Dimension-5 Level (EQ-5D-5L) questionnaire index and EuroQol Visual Analog Scale (EQ-VAS), widely used and complimentary tools that allow pts to provide a global assessment of their HRQoL. The EQ-5D-5L index assesses mobility, self-care, usual activities, pain/discomfort, and anxiety/depression; an index score is derived ranging from 0 (death) to 1 (perfect health).2 EQ-VAS assesses pt health state on a scale of 0-100, with higher scores indicating better health. Using mixed effects models for repeated measures (MMRM), least squares (LS) mean changes from baseline in the EQ-5D-5L index and EQ-VAS through W100 were assessed. Observed changes from baseline were evaluated; in pts who met treatment failure rules before W24 and in pts who discontinued with missing data after W24, changes from baseline were imputed as 0.

Results

GUS-treated pts achieved greater improvements in pt-reported health status than PBO at both W16 and W24 when evaluated using both the EQ-5D-5L index score and the EQ-VAS. The improvements by GUS in EQ-5D-5L index scores through W24 (0.12 for GUS Q4W/Q8W vs 0.05 for PBO; each nominal p<0.0001) were maintained with continued GUS through 2 years (0.15 for GUS Q4W/Q8W) (Table 1). PBO-treated pts who started GUS at W24 reported comparable improvements in their HRQoL by W52 (0.12), with maintenance though W100 (0.14). Similar results were observed with EQ-VAS (Figure 1). W24 improvements in EQ-VAS scores were greater following GUS treatment (18.2/18.4 GUS Q4W/Q8W) vs PBO (6.8; nominal p<0.0001). EQ-VAS scores continued to improve with GUS through 2 years (25.0/24.6 GUS Q4W/Q8W). Likewise, PBO-treated pts who crossed over to GUS at W24 experienced improvements in HRQoL by W52 (18.8), with maintenance through W100 (21.2).

Table 1.

LS mean change from baseline through W100 in EQ-5D-5L index

GUS 100mg Q4W(W0-100)GUS 100mg Q8W(W0-100)PBO → GUS 100 mg Q4WPBO(W0-24)GUS(W24-100)Week162410016241001624100N243244243247246248244244244LS mean change (95% CI)0.10 (0.09,0.12)0.12 (0.1,0.13)0.15 (0.13,0.16)0.11 (0.1,0.13)0.12 (0.1,0.13)0.15 (0.13,0.17)0.06 (0.04,0.07)0.05 (0.04,0.07)0.14 (0.12,0.16)  Diff vs. PBO0.04 (0.02,0.06)0.06 (0.04,0.09)--0.05 (0.03,0.07)0.06 (0.04,0.08)--------  Nominal p-value<0.0001<0.0001--<0.0001<0.0001--------

CI=Confidence interval; Diff=Difference

Conclusion

In bio-naïve pts with active PsA receiving GUS, earlier improvements (at the first timepoint assessed) in self-reported HRQoL measures were sustained through 2 years.

References

[1]Mease PJ, et al. Lancet. 2020;395:1126–36.

[2]EuroQol Group. 1990;16:199-208.

Disclosure of Interests

Jeffrey Curtis Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, CorEvitas, Eli Lilly, Janssen, Myriad, Novartis, Pfizer, Sanofi, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, CorEvitas, Eli Lilly, Janssen, Myriad, Novartis, Pfizer, Sanofi, and UCB, Iain McInnes Shareholder of: Causeway Therapeutics, and Evelo Compugen, Consultant of: Astra Zeneca, AbbVie, Amgen, Bristol-Myers Squibb, Cabaletta, Compugen, Eli Lilly, Gilead, GSK, Janssen, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: Astra Zeneca, Amgen, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen, Novartis, Roche, and UCB, Proton Rahman Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: Janssen and Novartis, 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, Eli Lilly, Janssen, Pfizer, and UCB, Feifei Yang Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC (a wholly owned subsidiary of Johnson & Johnson), Steve Peterson Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC (a wholly owned subsidiary of Johnson & Johnson), Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC (a wholly owned subsidiary of Johnson & Johnson), Natalie Shiff Shareholder of: AbbVie, Gilead, and Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC (a wholly owned subsidiary of Johnson & Johnson), Chenglong Han Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC (a wholly owned subsidiary of Johnson & Johnson), May Shawi Shareholder of: Johnson & Johnson, Employee of: Immunology Global Medical Affairs, Janssen Pharmaceutical Companies (a wholly owned subsidiary of Johnson & Johnson), William Tillett Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Eli Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Eli Lilly, Janssen, and UCB, Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Consultant of: AbbVie, Aclaris, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, Galapagos, Gilead, GSK, Inmagene, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, SUN Pharma, and UCB

POS1099 QUALITY OF LIFE, WORK IMPAIRMENT, AND DAILY ACTIVITY IMPAIRMENT OF PATIENTS WITH PSORIASIS VERSUS PSORIATIC ARTHRITIS: A REAL-WORLD SURVEY IN US AND EUROPE

Background

Psoriasis (PsO) and psoriatic arthritis (PsA) and are chronic immune-mediated diseases characterised by joint inflammation and skin lesions which negatively impact patients’ health-related quality of life (HRQoL). Several previous comparative studies have focused on PsA patients with or without skin involvement. Better understanding of the impact of both PsO and PsA on HRQoL and work / activity impairment will improve understanding of the incremental burden of PsA compared to PsO, and may lead to more personalised treatment options.

Objectives

To compare HRQoL, work impairment, and daily activity impairment of patients with a PsO diagnosis (dx) only, PsO dx with musculoskeletal (MSK) symptoms (sx), PsA dx with active skin sx, and PsA dx without active skin sx.

Methods

Data were drawn from the Adelphi PsO & PsA Disease Specific Programmes™ (DSP), real-world point-in-time surveys of rheumatologists, dermatologists and their consulting patients in the United States and Europe (France, Germany, Italy, Spain and UK); conducted in 2018/19. Patients were grouped according to their symptoms and confirmed diagnoses, comprising four groups:

1. Patients with PsO dx only,

2. Patients with PsO dx and with MSK sx,

3. Patients with PsA dx and with active skin sx,

4. Patients with PsA dx with no active skin sx,

Multivariate linear regression analyses with marginal mean predictions examined differences in patient-reported outcome measures (PROMs) between the four groups. Measures included HRQoL (EuroQol 5-Dimension 5-Level [EQ-5D Utility] and EuroQoL Visual Analogue Scale [EQ-VAS]), work impairment, and daily activity impairment (Work Productivity and Activity Impairment Questionnaire [WPAI]). Analyses controlled for demographics (age, sex, BMI), comorbidities present in >10% of patients and current treatment class (biologics, csDMARDs, steroids & other).

Results

4491 patients were included: Group 1 (n=1833), Group 2 (n=91), Group 3 (n=2451), and Group 4 (n=116). 54% of patients were male, 89% of patients were white, with a mean age of 46.6 years. Demographics were consistent across all patient groups.

The model-predicted EQ-5D-Utility was lower in Groups 2, 3 and 4, compared with Group 1 (p=0.003, p<0.001 and p=0.004 respectively). Similarly, predicted EQ-VAS was lower in Group 3 compared with Group 1 (p=0.006), Table 1.

Table 1.

Predictions of PROMs for PsO-PsA patient groups

PRO toolGroup [n]*Predicted PRO valuePopulation norm (MCID)Regression model p-value (vs. reference group)EQ-5D Utility score (n=1839)1 (ref) [743]0.9220.88 (0.07)2 [32]0.8160.0033 [1023]0.810<0.0014 [41]0.8500.004EQ-VAS (n=1882)1 (ref) [763]78.7878.2 (n/a)2 [36]70.560.0573 [1040]73.890.0064 [43]75.230.248WPAI % overall work impairment (n=1015)1 (ref) [422]15.36n/a (15.0)2 [14]17.860.5603 [558]22.16<0.0014 [21]26.090.014WPAI % work time missed (n=1028)1 (ref) [424]0.91n/a (n/a)2 [14]3.570.4863 [569]4.460.0024 [21]10.430.003WPAI % impairment while working (n=1153)1 (ref) [486]14.90n/a (20.0)2 [18]13.890.8463 [626]19.63<0.0014 [23]17.390.435WPAI % activity impairment (n=1818)1 (ref) [732]18.02n/a (20.0)2 [32]26.250.1223 [1012]26.14<0.0014 [42]25.240.044

*n values provided for reference, but margins are predictions as a result of the model and not for the specific number of patients in each subgroup.

(1) patients with PsO dx only

(2) Patients with PsO dx and MSK sx

(3) Patients with PsA dx and with active skin sx

(4) Patients with PsA dx with no active skin sx

Overall work impairment increased in Groups 3 and 4, compared with Group 1 (p<0.001 and p=0.014 respectively). Furthermore, Groups 3 and 4 missed more work compared with Group 1 (p=0.002 and p=0.003 respectively). Group 3 patients exhibited an increase in presenteeism and activity impairment compared with Group 1 (p<0.001), Table 1.

Conclusion

Patients experiencing PsA dx or MSK sx experienced an additional disease burden compared to patients with PsO sx alone, as measured by worse HRQoL and work impairment.

Disclosure of Interests

Joseph F. Merola Consultant of: Merck Research Laboratories, Abbvie, Dermavant, Eli Lilly and Company, Novartis, Janssen, UCB, Samumed, Celgene, Sanofi Regeneron, GSK, Almirall, Sun Pharma, Biogen, Pfizer, Incyte, Aclaris, and Leo Pharma, Lars Erik Kristensen Speakers bureau: Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly, and Janssen Pharmaceuticals, Consultant of: Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly, and Janssen Pharmaceuticals, Grant/research support from: Novo, UCB, Eli Lilly; Novartis and Abbvie, Feifei Yang Employee of: Employee of Janssen Pharmaceuticals, Steve Peterson Employee of: Employee of Janssen Pharmaceuticals, Rachel Teneralli Employee of: Employee of Janssen Pharmaceuticals, Nicola Massey Employee of: Adelphi Real World, Soumya D. Chakravarty Employee of: Employee of Janssen Pharmaceuticals, Megan Hughes Employee of: Adelphi Real World, May Shawi Employee of: Employee of Janssen Pharmaceuticals, Sarah Weatherby Employee of: Adelphi Real World, Christine Contre Employee of: Employee of Janssen Pharmaceuticals, Iris Lin Employee of: Employee of Janssen Pharmaceuticals, Fareen Hassan Employee of: Employee of Janssen Pharmaceuticals, M Elaine Husni Consultant of: Abbvie, Amgen, Eli Lilly, Novartis, Janssen, UCB, Pfizer, Regeneron, and BMS

Aldh2 is a lineage-specific metabolic gatekeeper in melanocyte stem cells

Melanocyte stem cells (McSCs) in zebrafish serve as an on-demand source of melanocytes during growth and regeneration, but metabolic programs associated with their activation and regenerative processes are not well known. Here, using live imaging coupled with scRNA-sequencing, we discovered that, during regeneration, quiescent McSCs activate a dormant embryonic neural crest transcriptional program followed by an aldehyde dehydrogenase (Aldh) 2 metabolic switch to generate progeny. Unexpectedly, although ALDH2 is well known for its aldehyde-clearing mechanisms, we find that, in regenerating McSCs, Aldh2 activity is required to generate formate – the one-carbon (1C) building block for nucleotide biosynthesis – through formaldehyde metabolism. Consequently, we find that disrupting the 1C cycle with low doses of methotrexate causes melanocyte regeneration defects. In the absence of Aldh2, we find that purines are the metabolic end product sufficient for activated McSCs to generate progeny. Together, our work reveals McSCs undergo a two-step cell state transition during regeneration, and that the reaction products of Aldh2 enzymes have tissue-specific stem cell functions that meet metabolic demands in regeneration.

Summary: In zebrafish melanocyte regeneration, quiescent McSCs respond by re-expressing a neural crest identity, followed by an Aldh2-dependent metabolic switch to generate progeny.

Quantitative CT metrics are associated with longitudinal lung function decline and future asthma exacerbations: Results from SARP-3

BACKGROUND

Currently, there is limited knowledge regarding which imaging assessments of asthma are associated with accelerated longitudinal decline in lung function.

OBJECTIVES

We aimed to assess whether quantitative computed tomography (qCT) metrics are associated with longitudinal decline in lung function and morbidity in asthma.

METHODS

We analyzed 205 qCT scans of adult patients with asthma and calculated baseline markers of airway remodeling, lung density, and pointwise regional change in lung volume (Jacobian measures) for each participant. Using multivariable regression models, we then assessed the association of qCT measurements with the outcomes of future change in lung function, future exacerbation rate, and changes in validated measurements of morbidity.

RESULTS

Greater baseline wall area percent (β = -0.15 [95% CI = -0.26 to -0.05]; P < .01), hyperinflation percent (β = -0.25 [95% CI = -0.41 to -0.09]; P < .01), and Jacobian gradient measurements (cranial-caudal β = 10.64 [95% CI = 3.79-17.49]; P < .01; posterior-anterior β = -9.14, [95% CI = -15.49 to -2.78]; P < .01) were associated with more severe future lung function decline. Additionally, greater wall area percent (rate ratio = 1.06 [95% CI = 1.01-1.10]; P = .02) and air trapping percent (rate ratio =1.01 [95% CI = 1.00-1.02]; P = .03), as well as lower decline in the Jacobian determinant mean (rate ratio = 0.58 [95% CI = 0.41-0.82]; P < .01) and Jacobian determinant standard deviation (rate ratio = 0.52 [95% CI = 0.32-0.85]; P = .01), were associated with a greater rate of future exacerbations. However, imaging metrics were not associated with clinically meaningful changes in scores on validated asthma morbidity questionnaires.

CONCLUSIONS

Baseline qCT measures of more severe airway remodeling, more small airway disease and hyperinflation, and less pointwise regional change in lung volumes were associated with future lung function decline and asthma exacerbations.

Small Airway Reduction and Fibrosis is an Early Pathologic Feature of Idiopathic Pulmonary Fibrosis

RATIONALE

To improve disease outcomes in idiopathic pulmonary fibrosis (IPF) it is essential to understand its early pathophysiology so that it can be targeted therapeutically.

OBJECTIVES

Perform three-dimensional (3D) assessment of the IPF lung micro-structure using stereology and multi-resolution computed tomography (CT) imaging.

METHODS

Explanted lungs from IPF patients (n=8) and donor controls (n=8) were inflated with air and frozen. CT scans were used to assess large airways. Unbiased, systematic uniform random (SUR) samples (n=8/lung) were scanned with microCT for stereological assessment of small airways (number, airway wall and lumen area) and parenchymal fibrosis (volume fraction of tissue, alveolar surface area, and septal wall thickness).

RESULTS

The total number of airways on clinical CT was greater in IPF lungs than control lungs (p<0.01), due to an increase in the wall (p<0.05) and lumen area (p<0.05) resulting in more visible airways with a lumen larger than 2 mm. In IPF tissue samples without microscopic fibrosis, assessed by the volume fraction of tissue using microCT, there was a reduction in the number of the terminal (p<0.01) and transitional (p<0.001) bronchioles, and an increase in terminal bronchiole wall area (p<0.001) compared to control lungs. In IPF tissue samples with microscopic parenchymal fibrosis, terminal bronchioles had increased airway wall thickness (p<0.05), and dilated airway lumens (p<0.001) leading to honeycomb cyst formations.

CONCLUSION

This study has important implications for the current thinking on how the lung tissue is remodeled in IPF, and highlights small airways as a potential target to modify IPF outcomes.

AB0556 COMPARING EFFICACY OF GUSELKUMAB VERSUS USTEKINUMAB IN PATIENTS WITH PSORIASIS ARTHRITIS: AN ADJUSTED COMPARISON USING INDIVIDUAL PATIENT DATA FROM DISCOVER 1&2 AND PSUMMIT TRIALS

Background:

Guselkumab is an anti-interleukin (IL)-23 monoclonal antibody recently approved for a treatment of Psoriasis arthritis (PsA). In two large Phase III trials of patients with PsA (DISCOVER -1 & -2) guselkumab has shown to be superior versus placebo. In this indication no direct comparison is available between guselkumab and ustekinumab, a monoclonal antibody targeting IL-12 and IL-23. Indirect comparisons based on relative treatment effects versus a common comparator (placebo) only allow for analyses up to week 24 due to cross-over to active arms in available PsA trials.

Objectives:

To compare indirectly joint and skin efficacy of guselkumab versus ustekinumab up to week 52, using pooled patient-level trial data from DISCOVER 1&2 and PSUMMIT 1&2, adjusting for cross-trial population differences.

Methods:

Patient level data, including baseline characteristics and outcome data on American College of Rheumatology (ACR) response, Psoriasis Area Severity Index (PASI) response from the guselkumab arms of DISCOVER -1 & -2 were pooled with the data from the ustekinumab trials PSUMMIT -1&-2. Analyses were performed for bio-naïve and bio-experienced populations separately. Differences in patient characteristics across trial populations were adjusted for using multivariate logistic regression, including: gender, age, body mass index, previous TNF use, disease duration, PASI level, number of swollen and tender joints. This method of indirect comparisons allows for analysis of comparative efficacy beyond controlled induction period and odds ratios’ resulting from this model were translated into predicted response rates for ustekinumab, assuming same patient population, as enrolled in the guselkumab trial arms.

Results:

Majority of baseline characteristics for patients on guselkumab (100mg q8w; 100mg q4w) were comparable to patients on ustekinumab 45/90mg, in both in bio-naïve and bio-experienced group of patients. The probability of reaching a ACR 20 in both the bio-naïve & bio-experienced population was significantly higher for guselkumab vs ustekinumab at weeks 52 for both dosing regimens of guselkumab (bio-naïve ACR 20: q8w OR= 1.88 [1.28;2.76]), q4w (OR= 1.92 [1.29;2.86]; bio experienced ACR20 q8w OR= 2.72[1.17;6.31], q4w OR=4.77 [1.95;11.63]). Similarly guselkumab was superior over ustekinumab on PASI 90 outcome at week 52 in both bio-naïve & bio-experienced patients with BSA ≥3 % at baseline (bio-naïve: q8w OR= 2.59 [1.68;3.99]), q4w OR= 3.19 [2.03;5.00], and bio-experienced q8w OR= 3.96[1.39,11.27], q4w OR=13.10[4.18,41.04]). Figure 1 represents unadjusted pooled DISCOVER 1&2 trial results and estimated proportions of ustekinumab treated patient group achieving ACR 20 in bio-naïve patient group up to week 52 using the method described above.

Conclusion:

An adjusted comparison using patient level data from pivotal Phase III studies demonstrates both dosages of guselkumab to be significantly more effective versus ustekinumab in both skin and joint outcomes in both bio-naïve & bio experienced patients up to week 52.

Disclosure of Interests:

Joris Diels Shareholder of: Janssen, Employee of: Janssen, Pushpike Thilakarathne Employee of: Janssen, Agata Schubert Shareholder of: Janssen, Employee of: Janssen, Fareen Hassan Shareholder of: Janssen, Employee of: Janssen, Steve Peterson Shareholder of: Janssen, Employee of: Janssen, Wim Noel Shareholder of: Janssen, Employee of: Janssen.

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

POS1026 GUSELKUMAB PROVIDES SUSTAINED IMPROVEMENTS IN WORK PRODUCTIVITY AND NON-WORK ACTIVITY IN PATIENTS WITH PSORIATIC ARTHRITIS: RESULTS THROUGH 1 YEAR OF A PHASE 3 TRIAL

Background:

DISCOVER-2 was a Phase 3 trial of the first-in-class anti-IL-23-specific mAb guselkumab (GUS) in patients (pts) with psoriatic arthritis (PsA). PsA impacts patients’ productivity at work and in daily activity.1

Objectives:

To evaluate the effect of GUS on work productivity and daily activity in DISCOVER-2 through 1 year using the Work Productivity and Activity Impairment Questionnaire: PsA (WPAI- PsA).

Methods:

Bio-naïve adults with active PsA despite nonbiologic DMARDs &/or NSAIDs received subcutaneous GUS 100 mg every 4 weeks (Q4W); GUS 100 mg W0, W4, then Q8W; or placebo (PBO). At W24, PBO pts crossed over to GUS 100 mg Q4W. WPAI-PsA assesses PsA-related work time missed (absenteeism), impairment while working (presenteeism), impaired overall work productivity (absenteeism + presenteeism), and daily activity during the previous week. A shift analysis evaluated proportions of pts employed vs unemployed (regardless of desire to work) over time. Among pts working at baseline, least-squares (LS) mean changes from baseline in WPAI-PsA domains were determined using a mixed-effects model for repeated measures analysis, whereby mean changes in WPAI-PsA domains were calculated for each multiple imputation (MI) dataset using an analysis of covariance (ANCOVA); the reported LSmean is the average of all MI datasets. Also, among pts employed at baseline, indirect savings from improved overall work productivity were estimated using 2020 EU mean yearly wage estimate (all occupations).2

Results:

In pts working at baseline, significant improvement in work productivity and non-work activity vs PBO was observed at W24. Productivity gains seen with GUS at W24 continued to improve through 1 year (Table 1). Shift analysis showed relatively stable employment in pts employed at baseline (62% of shift analysis cohort) through 1 year of GUS (>91% continued to work when assessed at W16, W24, and W52 [data not shown]). For those unemployed at baseline (38% of cohort), the proportion of pts working increased by ~10% following 1 year of GUS (Figure 1). Potential yearly indirect savings from improved overall work productivity were: €7409 GUS Q4W and €7039 GUS Q8W vs €4075 PBO at W24 and were €8520 GUS Q4W, €9632 GUS Q8W, and €6668 PBO→GUS Q4W at W52.

Conclusion:

Improvement in work productivity and non-work activity was greater with GUS vs PBO among pts with active PsA through W52. Improvements demonstrated may result in reduction in PsA costs associated with work productivity.

References:

[1]Tillett W et al. Rheumatol (Oxford). 2012;51:275–83.

[2]OECD (2020). Average wages (indicator). https://data.oecd.org/earnwage/average-wages.htm

Table 1.

Model-based estimates of LSmean changea (95% CI) from baseline in WPAI-PsA domains among pts working at baseline and with an observed change through W24 (N=474) and W52 (N=475)

Change from baselineGUS 100mg Q4WGUS 100mg Q8WPBO(W0-24)PBO → GUS 100 mg Q4W (W24-52)VisitW24W52W24W52W24W52Absenteeism, N145145147147162163LSmean-3.4 (-6.5,-0.3)-4.1 (-6.8,-1.5)-3.0 (-6.0,0.1)-4.0 (-6.6,-1.3)-3.0 (-6.0, 0.04)-3.0 (-5.5,-0.4)Diff vs. PBO-0.4 (-4.6,3.8)-0.01 (-4.2, 4.2)Presenteeism, N145145147147162163LSmean-20.1 (-23.7,-16.6)-22.4 (-26.3,-18.6)-19.6 (-23.2,-16.1)-25.7 (-29.5,-21.8)-10.5 (-13.9,-7.0)-18.5 (-22.2,-14.7)Diff vs PBO-9.7* (-14.4,-5.0)-9.2* (-13.9,-4.5)Work productivity, N145145147147162163LSmean-20.1 (-24.1,-16.1)-22.6 (-26.8,-18.3)-19.2 (-23.1,-15.2)-25.9 (-30.0,-21.7)-10.6 (-14.4,-6.8)-17.6 (-21.7,-13.6)Diff vs PBO-9.5* (-14.8,-4.2)-8.6* (-13.9,-3.3)Non-work Activity, N242242246246245245LSmean-20.5 (-23.3,-17.7)-25.7 (-28.6,-22.7)-21.2 (-23.9,-18.4)-25.4 (-28.4,-22.5)-9.9 (-12.6,-7.1)-22.3 (-25.3,-19.4)Diff vs PBO-10.6* (-14.4,-6.8)-11.3* (-15.1,-7.5)

CI=Confidence interval

a. LSmean for each MI dataset is calculated based on an ANCOVA model for the change from baseline at W24/W52. The combined LSmean, which is the average of the LSmean, taken over all the MI datasets, is presented.

*p<0.05

Disclosure of Interests:

Jeffrey Curtis Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, and UCB, 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, Steve Peterson Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Prasheen Agarwal Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Feifei Yang Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, 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, William Tillett Speakers bureau: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, Pfizer Inc, and UCB, Consultant of: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, MSD, Pfizer Inc, and UCB, Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer Inc, 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, 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.

Quantitative CT imaging and advanced visualization methods: potential application in novel coronavirus disease 2019 (COVID-19) pneumonia

Increasingly, quantitative lung computed tomography (qCT)-derived metrics are providing novel insights into chronic inflammatory lung diseases, including chronic obstructive pulmonary disease, asthma, interstitial lung disease, and more. Metrics related to parenchymal, airway, and vascular anatomy together with various measures associated with lung function including regional parenchymal mechanics, air trapping associated with functional small airways disease, and dual-energy derived measures of perfused blood volume are offering the ability to characterize disease phenotypes associated with the chronic inflammatory pulmonary diseases. With the emergence of COVID-19, together with its widely varying degrees of severity, its rapid progression in some cases, and the potential for lengthy post-COVID-19 morbidity, there is a new role in applying well-established qCT-based metrics. Based on the utility of qCT tools in other lung diseases, previously validated supervised classical machine learning methods, and emerging unsupervised machine learning and deep-learning approaches, we are now able to provide desperately needed insight into the acute and the chronic phases of this inflammatory lung disease. The potential areas in which qCT imaging can be beneficial include improved accuracy of diagnosis, identification of clinically distinct phenotypes, improvement of disease prognosis, stratification of care, and early objective evaluation of intervention response. There is also a potential role for qCT in evaluating an increasing population of post-COVID-19 lung parenchymal changes such as fibrosis. In this work, we discuss the basis of various lung qCT methods, using case-examples to highlight their potential application as a tool for the exploration and characterization of COVID-19, and offer scanning protocols to serve as templates for imaging the lung such that these established qCT analyses have the best chance at yielding the much needed new insights.

Can Linked Electronic Medical Record and Administrative Data Help Us Identify Those Living with Frailty?

Introduction

Frailty is a complex condition that affects many aspects of patients’ wellbeing and health outcomes.

Objectives

We used available Electronic Medical Record (EMR) and administrative data to determine definitions of frailty. We also examined whether there were differences in demographics or health conditions among those identified as frail in either the EMR or administrative data.

Methods

EMR and administrative data were linked in British Columbia (BC) and Manitoba (MB) to identify those aged 65 years and older who were frail. The EMR data were obtained from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) and the administrative data (e.g. billing, hospitalizations) was obtained from Population Data BC and the Manitoba Population Research Data Repository. Sociodemographic characteristics, risk factors, prescribed medications, use and costs of healthcare are described for those identified as frail.

Results

Sociodemographic and utilization differences were found among those identified as frail from the EMR compared to those in the administrative data. Among those who were >65 years, who had a record in both EMR and administrative data, 5%-8% (n=191 of 3,553, BC; n=2,396 of 29,382, MB) were identified as frail. There was a higher likelihood of being frail with increasing age and being a woman. In BC and MB, those identified as frail in both data sources have approximately twice the number of contacts with primary care (n=20 vs. n=10) and more days in hospital (n=7.2 vs. n=1.9 in BC; n=9.8 vs. n=2.8 in MB) compared to those who are not frail; 27% (BC) and 14% (MB) of those identified as frail in 2014 died in 2015.

Conclusions

Identifying frailty using EMR data is particularly challenging because many functional deficits are not routinely recorded in structured data fields. Our results suggest frailty can be captured along a continuum using both EMR and administrative data.

Development of comparable algorithms to measure primary care indicators using administrative health data across three Canadian provinces

INTRODUCTION

Performance measurement has been recognized as key to transforming primary care (PC). Yet, performance reporting in PC lags behind even though high-performing PC is foundational to an effective and efficient health care system.

OBJECTIVES

We used administrative data from three Canadian provinces, British Columbia, Ontario and Nova Scotia, to: 1) identify and develop a core set of PC performance indicators using administrative data and 2) examine their ability to capture PC performance.

METHODS

Administrative data used included Physician Billings, Discharge Abstract Database, the National Ambulatory Care and Reporting System database, Census and Vital Statistics. Indicators were compiled based on a literature review of PC indicators previously developed with administrative data available in Canada (n=158). We engaged in iterative discussions to assess data conformity, completeness, and plausibility of results in all jurisdictions. Challenges to creating comparable algorithms were examined through content analysis and research team discussions, which included clinicians, analysts, and health services researchers familiar with PC.

RESULTS

Our final list included 21 PC performance indicators pertaining to 1) technical care (n=4), 2) continuity of care (n=6), and 3) health services utilization (n=11). Establishing comparable algorithms across provinces was possible though time intensive. A major challenge was inconsistent data elements. Ease of data access, and a deep understanding of the data and practice context, was essential for selecting the most appropriate data elements.

CONCLUSIONS

This project is unique in creating algorithms to measure PC performance across provinces. It was essential to balance internal validity of the indicators within a province and external validity across provinces. The intuitive desire of having the exact same coding across provinces was infeasible due to lack of standardized PC data. Rather, a context-tailored definition was developed for each jurisdiction. This work serves as an example for developing comparable PC performance indicators across different provincial/territorial jurisdictions.

AB0818 SKIN INVOLVEMENT IN PSORIATIC ARTHRITIS (PsA) - THE INCREMENTAL IMPACT OF PSORIASIS ON QUALITY OF LIFE, DISABILITY AND WORK PRODUCTIVITY: REAL-WORLD SURVEY IN US AND EUROPE

Background:

PsA involves joint and skin symptom presentation that varies across patients. Differences in patients outcomes with joint only, and joint and skin involvement have not been extensively studied in a real-world setting.

Objectives:

To assess prevalence of joint only, and joint and skin disease in a real-world clinical setting, and to assess incremental impact of skin symptoms on quality of life (QoL), disability and work productivity.

Methods:

A cross-sectional survey in patients with PsA recruited by rheumatologists and dermatologists was conducted in France, Germany, Italy, Spain, UK and US. Data were collected Jun-Aug 2018 via physician-completed patient record forms and patient self-completed forms. Patients were compared by joint and skin involvement using parametric and non-parametric tests. Multiple linear regression analyses examined impact of incremental body surface area (BSA) on patient reported outcomes (PROs). Models controlled for gender, age, time since diagnosis, employment status, biologic DMARD use, BMI, number of joints affected.

Results:

Of 1,909 patients (539 US, 1,370 EU), 35% of patients had joint only disease, while 26%, 23%, and 16% experienced joint disease plus 1-3%, >3-10%, and >10% BSA respectively (Figure 1). Patients were comparable demographically (Table 1). After controlling for demographics and number of joints involved, results showed BSA independently and significantly impacted QoL, work productivity, disability (Table 2).

Table 1.

Comparison of patient demographic and disease characteristics by joint and skin disease involvement

Joints only (n=673)1-3% (n=493)>3-10% (n=447)>10%(n=296)p-valueAge, mean (SD)49.2 (13.7)49.2 (13.2)47.6 (12.4)47.6 (13.8)0.09Male, n (%)379 (56.3)260 (52.7)248 (55.5)155 (52.4)0.53BMI, mean (SD)26.9 (4.9)26.8 (4.6)26.7 (4.2)26.5 (4.7)0.52Caucasian, n (%)621 (92.3)442 (89.7)399 (89.3)270 (91.2)0.41Full-time employment, n (%)391 (60.9)275 (57.7)259 (59.1)153 (53.1)0.01Biologic tx, n (%)420 (62.4)283 (57.4)218 (48.8)141 (47.6)<0.01Months since diagnosis, mean (SD)68.4 (76.2)56.7 (68.2)54.2 (67.3)52.1 (75.1)<0.01Current BSA %, mean (SD)0.01.7 (0.8)6.3 (2.0)21.3 (10.1)<0.01*66 swollen joint count, mean (SD)1.5 (3.6)2.1 (4.2)7.1 (11.1)6.9 (10.5)<0.01*68 tender joint count, mean (SD)2.1 (4.1)3.7 (6.4)6.0 (7.7)9.8 (10.0)<0.01

*Calculated on available data, n=394

Table 2.

Incremental impact of BSA on PROs

BSA in addition to joint involvementChange in predicted PRO valuesP valueEQ5D utility (n=656)Joint only (ref)0.851-3%-0.020.31>3-10%-0.06<0.01>10%-0.06<0.01EQ5D VAS (n=668)Joint only78.140.741-3%-0.580.03>3-10%-3.780.14>10%-3.04WPAI % overall work impairment (n=369)Joint only15.880.911-3%+0.32<0.05>3-10%+5.110.01>10%+7.51HAQ-DI (n=635)Joint only0.320.411-3%+0.04<0.01>3-10%+0.22<0.01>10%+0.27PsAID12 (n=642)Joint only1.660.031-3%+0.42<0.01>3-10%+1.22<0.01>10%+1.37

α PRO key for worse outcome (range): EQ5D utility (0-1.0) = lower; EQ5D VAS (1-100) = lower; WPAI (0-100) = higher; HAQ-DI (0-3) = higher; PsAID12 (0-10) = higher

Conclusion:

Two thirds of this sample of actively treated PsA patients have skin involvement. Over half would be considered moderate-severe (BSA >3%). After controlling for joint symptoms, results show that increasing skin involvement in PsA patients adversely impacts QoL, disability and work productivity.

Disclosure of Interests:

Jessica A. Walsh Grant/research support from: AbbVie, Pfizer, Janssen, Consultant of: AbbVie, Novartis, Eli Lilly and Company, UCB, Alexis Ogdie Grant/research support from: Pfizer to Penn, Novartis to Penn, Amgen to Forward/NDB, Consultant of: Abbvie, Amgen, Bristol-Myers Squibb, Celgene, Corrona, Janssen, Eli Lilly, Novartis, Pfizer, Kaleb Michaud Grant/research support from: Janssen, Steve Peterson Employee of: Janssen Research & Development, LLC, Elizabeth Holdsworth Employee of: Adelphi Real World, Sara Bruce Wirta Employee of: Janssen-Cilag Sweden AB, Sophie Meakin Employee of: Adelphi Real World, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Agata Schubert Employee of: Janssen-Cilag, Laure Gossec Grant/research support from: Lilly, Mylan, Pfizer, Sandoz, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis, UCB

AB0821 ANXIETY AND DEPRESSION IN PSORIATIC ARTHRITIS (PsA) - PREVALENCE AND IMPACT ON PATIENT REPORTED OUTCOMES: REAL-WORLD SURVEY IN THE US AND EUROPE

Background:

Anxiety and depression are comorbidities among PsA patients. The impact of anxiety and depression on outcomes in PsA patients has not been characterized in a real-world clinical setting.

Objectives:

To describe the prevalence of anxiety and/or depression in PsA patients, assess concordance in reported anxiety and/or depression between patients and physicians, and compare clinical and patient reported outcomes (PROs) in patients who do and do not report anxiety and/or depression.

Methods:

A cross-sectional study of patients with PsA recruited by rheumatologists and dermatologists was conducted in France, Germany, Italy, Spain, UK and US. Data were collected Jun-Aug 2018 via physician-completed and patient self-completed forms. Physicians reported patient demographic, disease characteristics and diagnosed anxiety and/or depression. Patients reported experience of PsA-related anxiety/depression, quality of life [QoL] (EQ5D-5L), work productivity (WPAI), disability (HAQ-DI), and disease impact (PsAID12). Patients were compared according to patient reported anxiety/depression using parametric and non-parametric tests. Multivariate regressions explored impact of anxiety/depression on PROs. Models adjusted for age, gender, employment status, BMI, # of joints affected, body surface area (BSA).

Results:

Data were collected from 688 physician-patient pairs (524 EU; 164 US). Physicians reported anxiety and/or depression in 14.2% of patients (EU 13.3%; US 16.2%), while 36.6% (EU 36.3%; US 37.8%) of patients self-reported anxiety and/or depression. 71.4% of physician-patient pairs agreed on anxiety and/or depression presence or absence (Kappa = 0.31, fair agreement). Patients with anxiety and/or depression had worse QoL more work impairment, greater disability (Table 2).

Table 1.

Demographic and clinical characteristics by patient-reported anxiety and/or depression

No anxiety and/or depression(n=436)Anxiety and/or depression(n=252)P valueDemographicsAge, mean (SD)47.7 (12.1)49.1 (12.6)0.13Female, n (%)196 (45.0)146 (57.9)<0.01BMI, mean (SD)26.7 (5.1)26.9 (4.4)0.57Caucasian, n (%)408 (93.3)238 (94.4)0.46Working full time, n (%)293 (68.6)107 (44.8)<0.01Biologic tx, n (%)257 (58.9)160 (63.5)0.26Disease characteristicsDays since diagnosis, mean (SD)2090 (2204)2532 (2813)0.04Current overall severity, n (%)Mild277 (63.5)137 (54.4)0.02Moderate145 (33.3)106 (42.1)Severe14 (3.2)9 (3.6)Current BSA %, mean (SD)8.7 (12.3)6.4 (8.2)0.0266 swollen joint count, mean (SD)2.7 (3.6)5.6 (10.4)<0.0168 tender joint count, mean (SD)3.8 (4.3)6.0 (6.2)<0.01Table 2.

Impact of anxiety or depression on PROs*

Anxiety and/or depressionChange in predicted PRO value with anxiety and/or depression αP valueEQ5D utility score, mean N=488Without (ref)With0.83-0.10<0.01WPAI percentage overall work impairment, mean N=262WithoutWith22.3+7.4<0.01HAQ-DI score, meanN=480WithoutWith0.53+0.26<0.01PsAID12 score, meanN=482WithoutWith2.32+1.78<0.01

* Adjusted for age, gender, employment status, BMI, # of joints affected and BSA

α PRO key for worse outcome (range): EQ5D utility (0-1.0) = lower; EQ5D VAS (1-100) = lower; WPAI (0-100) = higher; HAQ-DI (0-3) = higher; PsAID12 (0-10) = higher.

Conclusion:

One third of patients self-report anxiety and/or depression. Treating physicians may not be aware of patient experience of anxiety and/or depression. Patients with anxiety and/or depression appear to have worse QoL, work productivity and disability outcomes than those without.

Disclosure of Interests:

Laure Gossec Grant/research support from: Lilly, Mylan, Pfizer, Sandoz, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis, UCB, Jessica A. Walsh Grant/research support from: AbbVie, Pfizer, Janssen, Consultant of: AbbVie, Novartis, Eli Lilly and Company, UCB, Kaleb Michaud Grant/research support from: Janssen, Elizabeth Holdsworth Employee of: Adelphi Real World, Steve Peterson Employee of: Janssen Research & Development, LLC, Sophie Meakin Employee of: Adelphi Real World, Sara Bruce Wirta Employee of: Janssen-Cilag Sweden AB, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Alexis Ogdie Grant/research support from: Pfizer to Penn, Novartis to Penn, Amgen to Forward/NDB, Consultant of: Abbvie, Amgen, Bristol-Myers Squibb, Celgene, Corrona, Janssen, Eli Lilly, Novartis, Pfizer

AB0756 GUSELKUMAB IMPROVED WORK PRODUCTIVITY AND DAILY ACTIVITY IN PATIENTS WITH PSORIATIC ARTHRITIS: RESULTS FROM A PHASE 3 TRIAL

Background:

DISCOVER 2 (DISC 2) is a Phase 3 trial of anti-IL-23-specific mAb guselkumab (GUS) in psoriatic arthritis (PsA) pts, who experience impaired physical function, resulting in disability, work productivity loss, and economic consequences.1

Objectives:

To evaluate the effect of GUS on impaired work productivity and daily activity in DISC 2 using the Work Productivity and Activity Impairment Questionnaire: Psoriatic Arthritis (WPAI-PsA).

Methods:

Bio-naïve adults with active PsA despite nonbiologic DMARDs &/or NSAIDs received subcutaneous GUS 100 mg every (q) 4 weeks (W); GUS 100 mg W0, W4, q8W; or placebo (PBO). WPAI-PsA assesses, due to PsA over the previous week, work time missed (absenteeism), impairment while working (presenteeism), and impaired overall work productivity (absenteeism + presenteeism) and daily activity. Percentage change from baseline was analyzed for WPAI-PsA domains using mixed-effect model repeated measure (MMRM). Indirect savings from improved overall work productivity were estimated with 2018 US mean yearly wage estimate (all occupations).2

Results:

At Week 24, impaired overall work productivity and daily activity were improved 20-22% in GUS-treated and 10-11% in PBO-treated pts (Table). Potential yearly indirect savings from improved overall work productivity was $10,242 with GUS q8W and $10,404 with GUS q4W vs $5,648 with PBO; $4,594 and $4,756 difference, respectively.

Conclusion:

Improvement in overall work productivity and daily activity was greater with GUS versus PBO among pts with moderate-to-severe PsA, resulting in potential annual incremental economic gains.

References:

[1]Tillett W et al. Rheumatol (Oxford). 2012;51:275–283.

[2]US Bureau of Labor Statistics. May 2018 National Occupational Employment and Wage Estimates United States.https://www.bls.gov/oes/current/oes_nat.htm#00-000

Table.

Model-based estimates of mean change from baseline in WPAI-PsA domains

% change from baselinePBOGUS 100 mg q8WGUS 100 mg q4WW16W24W16W24W16W24Work time missed (absenteeism), n155152141145145143LSMean-4.6 (-7.2,-1.9)-3.5 (-6.4,-0.6)-3.5 (-6.2,-0.7)-3.1 (-6.1,-0.1)-4.7 (-7.4,-2.0)-3.8 (-6.8,-0.8)LSMean diff1.1 (-2.6,-4.8)*0.4 (-3.7,4.5)*-0.2 (-3.9,3.5)*-0.3 (-4.4,3.8)*Impairment while working (presenteeism), n131130125129133130LSMean-10.3 (-13.9,-6.7)-10.2 (-13.7,-6.7)-16.1 (-19.7,-12.4)-19.4 (-22.9,-15.9)-15.1 (-18.7,-11.5)-19.5 (-23.0,-16.0)LSMean diff-5.8 (-10.8,-0.8)†-9.2 (-14.0,-4.4)‡-4.8 (-9.7,0.1)*-9.3 (-14.1,-4.5)‡Overall work productivity impairment (absenteeism + presenteeism), n131130125129133130LSMean-11.2 (-15.0,-7.5)-10.9 (-14.6,-7.1)-15.9 (-19.7,-12.2)-19.7 (-23.4,-16.0)-15.8 (-19.5,-12.1)-20.0 (-23.7,-16.3)LSMean diff-4.7 (-9.9,0.5)*-8.8 (-14.0,-3.7)‡-4.6 (-9.7,0.5)*-9.2 (-14.3,-4.0)‡Daily activity impairment, n244244247246243245LSMean-10.6 (-13.3,-7.9)-10.3 (-13.1,-7.6)-17.1 (-19.8,-14.4)-21.5 (-24.2,-18.7)-17.0 (-19.7,-14.3)-20.5 (-23.2,-17.7)LSMean diff-6.5 (-10.2,-2.8)‡-11.1 (-15.0,-7.4)‡-6.5 (-10.2,-2.7)‡-10.2 (-14.0,-6.4)‡

Data are % (95% CI)

*p>0.05, †p<0.05,‡p<0.001

LSmeans, p values based on MMRM

LSmean diffs, p values vs PBO

Acknowledgments:

None

Disclosure of Interests:

Jeffrey Curtis Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Iain McInnes Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Proton Rahman Grant/research support from: Janssen and Novartis, Consultant of: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Speakers bureau: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, William Tillett Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer Inc, UCB, Consultant of: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, MSD, Pfizer Inc, UCB, Speakers bureau: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, Pfizer Inc, UCB, Philip J Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – grant/research support, Consultant of: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – consultant, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau, 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, Bei Zhou Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Prasheen Agarwal Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Steve Peterson Employee of: Janssen Research & Development, LLC, Chenglong Han Employee of: Janssen Research & Development, LLC

AB0820 COMPARATIVE EFFICACY OF GUSELKUMAB IN PATIENTS WITH PSORIATIC ARTHRITIS: RESULTS FROM SYSTEMATIC LITERATURE REVIEW AND NETWORK META-ANALYSIS

Background:

The efficacy of the interleukin (IL)-23 subunit p19 inhibitor guselkumab (GUS) for psoriatic arthritis (PsA) has recently been demonstrated in two Phase 3 trials (DISCOVER-1 & -2) but has not been evaluated versus existing targeted therapies for PsA.

Objectives:

To compare GUS to targeted therapies for PsA through network meta-analysis (NMA).

Methods:

A systematic literature review was performed to identify PsA randomized controlled trials from 2000 to 2018. Bayesian NMAs were performed to compare treatments on American College of Rheumatology (ACR) 20/50/70 response, Psoriasis Area Severity Index (PASI) 75/90/100 response, Health Assessment Questionnaire Disability Index (HAQ-DI) score, resolution of enthesitis (RoE), resolution of dactylitis (RoD), adverse events (AEs) and serious adverse events (SAEs). Analyses used random effects models that adjusted for placebo response via meta-regression on baseline risk when feasible. Results are summarized by ranking treatments according to median absolute probabilities of response derived from NMAs.

Results:

Twenty-six Phase 3 studies were included in the quantitative synthesis. Studies were placebo-controlled up to 24 weeks and evaluated 13 targeted therapies for PsA. Absolute probabilities are reported for PASI 90 & ACR 20 responses according toFigure 1,and a forest plot of relative risks versus placebo for AEs is reported according toFigure 2. For ACR 20 response, GUS 100 mg every 4 weeks (Q4W) and every 8 weeks (Q8W) ranked 5th and 8th out of 20 interventions and were comparable to IL-17A inhibitor (IL-17Ai) and most tumor necrosis factor inhibitor (TNFi) agents. Similar findings were observed for ACR 50 and 70 responses. For PASI 90 response, GUS Q4W and Q8W ranked 1st and 2nd out of 15 interventions and were highly likely to provide a greater benefit than most other agents. Similar findings were observed for PASI 75 and 100 responses. For HAQ-DI score, GUS Q4W and Q8W ranked 6th and 10th out of 20 interventions and were comparable to IL-17Ai and most TNFi agents. For RoE, GUS Q4W and Q8W ranked 8th and 6th out of 13 interventions and were comparable to IL-17Ai and TNFi agents. For RoD, GUS Q4W and Q8W ranked 8th and 9th out of 13 interventions and were comparable to most IL-17Ai and TNFi agents. For AEs, GUS Q4W and Q8W ranked 3rd and 2nd out of 19 interventions and were comparable to IL-17Ai and TNFi agents. Likewise, for SAEs, GUS Q4W and Q8W ranked 4th and 5th out of 20 interventions and were comparable to IL-17Ai and TNFi agents. Analyses that controlled for previous exposure to biologics or assessed outcomes at alternative timepoints were broadly consistent with primary analysis results.

Conclusion:

NMA results indicate that GUS is comparable to most targeted PsA treatments for improvement in arthritis, soft tissue damage, physical function, and safety outcomes. For PASI outcomes, GUS is highly likely to provide a greater benefit than other targeted PsA treatments.

Disclosure of Interests:

Iain McInnes Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Philip J Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – grant/research support, Consultant of: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – consultant, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau, Kiefer Eaton Shareholder of: Test Pharma, Consultant of: Janssen, Agata Schubert Employee of: Janssen-Cilag, Steve Peterson Employee of: Janssen Research & Development, LLC, Tim Disher Consultant of: Janssen, Wim Noel Employee of: Janssen Pharmaceuticals NV, Hassan Fareen Employee of: Janssen, Chetan Karyekar Shareholder of: Johnson & Johnson, Consultant of: Janssen, Employee of: Janssen Global Services, LLC. Previously, Novartis, Bristol-Myers Squibb, and Abbott Labs., Suzy Van Sanden Employee of: Janssen, Christopher T. Ritchlin Grant/research support from: UCB Pharma, AbbVie, Amgen, Consultant of: UCB Pharma, Amgen, AbbVie, Lilly, Pfizer, Novartis, Gilead, Janssen, Wolf-Henning Boehncke Grant/research support from: Janssen Research & Development, LLC, Consultant of: Janssen

FRI0358 USAGE OF C-REACTIVE PROTEIN TESTING IN THE DIAGNOSIS AND MONITORING OF PSORIATIC ARTHRITIS (PSA): RESULTS FROM A REAL-WORLD SURVEY IN THE US AND EUROPE

Background:

C-reactive protein (CRP) is an important non-specific marker of both acute and chronic inflammation and can be elevated in patients with PsA. The role of CRP in the management of PsA is unclear.

Objectives:

To describe how CRP testing is implemented in real-world clinical practice for disease management of PsA.

Methods:

A cross-sectional study among patients with PsA recruited by rheumatologists and dermatologists was conducted in France, Germany, Italy, Spain, UK and US. Data were collected from Jun-Aug 2018 via physician-completed patient record forms. Use of CRP testing was obtained by asking the physician to state (yes/no) whether CRP was used to aid PsA diagnosis, confirm the patient’s PsA and to monitor the patient’s PsA. Where physicians stated use of CRP testing, they were then asked to provide the number of CRP tests conducted in the last 12 months.

Results:

Data were collected for 2270 patients with PsA (595 US, 1675 EU5). In EU5, 78.7% of patients had CRP conducted to aid diagnosis (vs 43.4% in US) and 72.0% had CRP conducted to monitor their condition (vs 34.6% in US). Patients seen by rheumatologists (vs dermatologists) were at least 50% more likely to have CRP used for monitoring purposes, this difference being most pronounced in the US. In EU5, CRP was conducted a mean [SD] of 2.7 [1.7] times in the last 12 months, versus 2.0 [1.4] in the US. Country level usage of CRP testing is shown in Table 2.

Table 2.

Purpose and frequency of CRP testing

CRP conducted…EU5 (n=1675)France (n=277)Germany (n=360)Italy (n=360)Spain (n=369)UK(n=309)US(n=595)To aid diagnosis, n (%)1319 (78.7)233 (84.1)282 (78.3)283 (78.6)315 (85.4)206 (66.7)258 (43.4)To confirm PsA, n (%)692 (41.3)83 (30.0)156 (43.3)151 (41.9)179 (48.5)123 (39.8)110 (18.5)To monitor PsA, n (%) [n]1190 (72.0)[1652]209 (75.7) [276]261 (74.1) [352]256 (72.9) [351]283 (77.1) [367]181 (59.2) [306]203 (34.6) [586]Patients with ≥1 CRP in last 12 months, n (%)1355 (80.9)238 (85.9)291 (80.8)304 (84.4)319 (86.4)203 (65.7)255 (42.9)Number conducted in last 12months, mean [SD]2.7 [1.7]3.1 [2.5]2.4 [1.7]2.5 [1.3]2.6 [1.2]2.9 [2.0]2.0 [1.4]Table 1.

Patient demographic and clinical characteristics

Overall (n=2270)EU5(n=1675)US(n=595)Patient seen by rheumatologist, n (%)1130 (49.8)834 (49.8)296 (49.7)Age, mean [SD]46.6 [13.3]48.1 [13.1]50.0 [13.5]Female, n (%)1047 (46.1)774 (46.2)273 (45.9)BMI, mean [SD]26.8 [4.7]26.3 [4.3]28.1 [5.5]Caucasian, n (%)2051 (90.4)1551 (92.6)500 (84.0)Current smoker, n (%)403 (20.3)352 (24.3)51 (9.5)Employment, n (%)-Working full-time1271 (58.2)894 (55.6)377 (65.3)Current disease severity, n (%)-Mild1702 (75.0)1253 (74.8)449 (75.5)-Moderate/Severe568 (25.0)422 (25.2)146 (24.5)Current treatment, n (%)-Receiving bDMARD*1231 (54.2)910 (54.3)321 (53.9)-Receiving tsDMARD*251 (11.1)121 (7.2)130 (21.8)-Receiving csDMARD*835 (36.8)698 (41.7)137 (23.0)-Receiving opioid55 (2.4)29 (1.7)26 (4.4)Total number of HCP visits in last 12months, mean [SD]6.5 [5.8]7.0 [6.3]5.0 [3.6]

*bDMARD: biologic DMARD, tsDMARD: targeted synthetic DMARD, csDMARD: conventional synthetic DMARD

Conclusion:

The majority (80.9%) of patients with PsA in EU5 had at least one CRP test in the last 12 months, versus 42.9% in the US. CRP is more commonly used for diagnosis and monitoring of PsA in Europe compared to the US and is more commonly ordered by rheumatologists than dermatologists.

Disclosure of Interests:

Alexis Ogdie Grant/research support from: Pfizer to Penn, Novartis to Penn, Amgen to Forward/NDB, Consultant of: Abbvie, Amgen, Bristol-Myers Squibb, Celgene, Corrona, Janssen, Eli Lilly, Novartis, Pfizer, William Tillett Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer Inc, UCB, Consultant of: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, MSD, Pfizer Inc, UCB, Speakers bureau: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, Pfizer Inc, UCB, Lihi Eder Grant/research support from: Abbvie, Lily, Janssen, Amgen, Novartis, Consultant of: Janssen, Speakers bureau: Abbvie, Lily, Janssen, Amgen, Novartis, Nicola Booth Consultant of: Janssen, Sara Bruce Wirta Employee of: Janssen-Cilag Sweden AB, Oliver Howell Employee of: Janssen, Agata Schubert Employee of: Janssen-Cilag, Steve Peterson Employee of: Janssen Research & Development, LLC, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Laura C Coates: None declared

AB0819 FLARES AMONG PATIENTS WITH PSORIATIC ARTHRITIS (PsA) - FREQUENCY AND IMPACT ON PATIENT OUTCOMES: REAL-WORLD SURVEY IN THE US AND EUROPE

Background:

Flares in PsA, presenting as periods of acute disease activity, are thought to negatively impact patients’ lives. This has not been extensively studied in a real-world setting.

Objectives:

Describe flares, assess impact on quality of life and work productivity, and explore predictors.

Methods:

A cross-sectional survey among patients with PsA recruited by rheumatologists and dermatologists was conducted in France, Germany, Italy, Spain, UK and US. Data were collected Jun-Aug 2018 via patient record forms and patient self-complete forms. Physicians recorded flare status (in flare currently/flared in last 12 mo/longer than 12 mo or never), demographics, physician perceived severity and clinical outcomes. Patients reported quality of life [QoL] (EQ5D-5L), work productivity (WPAI), disability (HAQ-DI), pain (PsAID12 pain scale). Patients were compared by flare status using parametric or non-parametric tests. Logistic regression explored predictors of flare. Multivariate regression explored the impact of flare status on patient reported outcomes (PRO). The model was adjusted for gender, age, BMI, physician speciality.

Results:

Data were collected for 2,238 patients (586 US, 1,652 EU). Mean age was 48.7 years (13.2 SD), 53.8% were male. Physicians reported 7.5% were currently in flare and 22.0% had flared in the last 12 mo. Patients had experienced 2.2 mean flares in the last 12 mo (4.9 SD), lasting a mean 16.4 days (16.2 SD). Patients in flare were comparable demographically with those not; however, those in flare were less likely to work full time (43.6 vs. 59.3%, p<0.01). Patients not in flare had clinically active disease (Table 1).

Table 1.

Clinical characteristics of patients by flare status

Currently in flare (n=168)Flared in last 12 mo(n=492)Not flared in last 12 mo/never flared(n=1578)p-valueIn remission, n (%)4 (2.4)157 (33.2)799 (53.5)<0.01*Current BSA affected, mean (SD)10.3 (12.0)6.5 (7.6)5.0 (7.7)<0.01*66 SJC, mean (SD)5.4 (4.6)4.5 (7.3)2.4 (6.9)<0.01*68 TJC, mean (SD)7.8 (5.8)5.5 (8.3)3.1 (5.6)<0.01Physician-perceived severity, n (%)Mild35 (20.8)346 (70.3)1297 (82.2)<0.01Moderate101 (60.1)139 (28.3)261 (16.5)Severe32 (19.0)7 (1.4)20 (1.3)

*Calculated on available data: Total base sizes: BSA=1665; SJC=514; TJC=493; Satisfaction=931

Results showed that flare status significantly impacted QoL, work productivity, disability, and pain (Table 2). Exploring predictors of flare in the last 12 mo in un-adjusted analyses showed that demographic characteristics were not predictive of flare status, however patients presenting as moderate or severe at diagnosis were at greater risk of flare. Patients who were prescribed a bDMARD at diagnosis were at lower risk (Figure 1).

Table 2.

Impact of flare status on PROs

Current flare statusChange in predicted PRO valuesP valueEQ5D utility (n=933)Not in flare (ref)In flare0.83-0.23<0.01EQ5D VAS (n=946)Not in flareIn flare76.1-21.3<0.01WPAI % overall work impairment (n=496)Not in flareIn flare20.1+28.5<0.01HAQ-DI (n=901)Not in flareIn flare0.4+0.6<0.01PsAID12 pain score (n=922)Not in flareIn flare2.5+3.0<0.01

PRO key for worse outcome (range): EQ5D utility (0-1.0) = lower; EQ5D VAS (1-100) = lower; WPAI (0-100) = higher; HAQ-DI (0-3) = higher; PsAID12 pain (0-10) = higher

Figure 1.

Predictors of flaring in last 12 months

Conclusion:

One third of patients surveyed were either currently in flare or had flared in the last 12 mo. Being in flare adversely impacted QoL, disability and work productivity. Flare may be predicted by overall physician-reported PsA disease severity at diagnosis.

Disclosure of Interests:

Ana-Maria Orbai Grant/research support from: Abbvie, Eli Lilly and Company, Celgene, Novartis, Janssen, Horizon, Consultant of: Eli Lilly; Janssen; Novartis; Pfizer; UCB. Ana-Maria Orbai was a private consultant or advisor for Sun Pharmaceutical Industries, Inc, not in her capacity as a Johns Hopkins faculty member and was not compensated for this service., William Tillett Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer Inc, UCB, Consultant of: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, MSD, Pfizer Inc, UCB, Speakers bureau: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, Pfizer Inc, UCB, Suzanne Grieb Grant/research support from: Janssen, Steve Peterson Employee of: Janssen Research & Development, LLC, Elizabeth Holdsworth Employee of: Adelphi Real World, Sophie Meakin Employee of: Adelphi Real World, Sara Bruce Wirta Employee of: Janssen-Cilag Sweden AB, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Laure Gossec Grant/research support from: Lilly, Mylan, Pfizer, Sandoz, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis, UCB

Propensity score matching/reweighting analysis comparing intravenous golimumab to infliximab for ankylosing spondylitis using data from the GO-ALIVE and ASSERT trials

Objective

To compare the relative efficacy of intravenous golimumab (GOL IV) and infliximab (IFX) for active ankylosing spondylitis (AS).

Methods

Propensity score (PS) methods were used to compare the efficacy of GOL IV 2 mg/kg and IFX 5 mg/kg using individual patient data (IPD) from the active arms of the phase 3 GO-ALIVE and ASSERT studies. Outcomes included the proportion of patients with a ≥ 20% improvement in the Assessment of Spondyloarthritis International Society Criteria (ASAS20), change from baseline in Bath Ankylosing Spondylitis Functional Index (BASFI) score, and change from baseline in C-reactive protein (CRP) levels from weeks 4–52.

Results

Before matching, 105 patients were treated with GOL IV and 201 patients were treated with IFX. After matching on all covariates, 118 patients were included in the ASAS20 analysis, 96 in the BASFI analysis, and 160 in the CRP analysis. After matching, GOL IV showed significantly greater improvement in ASAS20 response than IFX for weeks 28–44 (e.g., OR = 9.05 [95% CI 1.62–50.4] at week 44) and was comparable in change from baseline in BASFI scores and CRP levels to IFX at all time points. Results were robust for inclusion of different sets of covariates in scenario analyses.

Conclusions

This is the first analysis of its kind to leverage clinical trial data to compare two biologics using PS methods in the treatment of active AS. Overall, GOL IV was associated with greater improvement in ASAS20 response than IFX in patients with AS at 28, 36, and 44 weeks of follow-up.

Key Points • Although intravenous golimumab (GOL IV) and infliximab (IFX) are the only two IV-based tumor necrosis factor (TNF) inhibitors with demonstrated phase 3 clinical efficacy in patients with ankylosing spondylitis (AS), no study has evaluated their comparative efficacy in a head-to-head trial. • Propensity score matching was used to derive indirect treatment comparisons of GOL IV and IFX for ≥ 20% in the Assessment of Spondyloarthritis International Society Criteria (ASAS20), change in Bath Ankylosing Spondylitis Functional Index (BASFI), and change in C-reactive protein (CRP) using individual patient data from the GO-ALIVE and ASSERT phase 3 trials. • Propensity score matched indirect comparisons showed improved relative efficacy of GOL IV compared to IFX; after matching for up to 16 baseline covariates, GOL IV was associated with significantly greater odds of ASAS20 response at weeks 28, 36, and 44 than IFX as well as equivalent changes from baseline in BASFI and CRP. • This novel application of propensity score matching using data from phase 3 trials, the first analysis of its kind in AS, allowed adjustment for important imbalances in prognostic factors between trials to generate estimates of comparative efficacy between GOL IV and IFX in the absence of a head-to-head trial between these treatments.

Electronic supplementary material

The online version of this article (10.1007/s10067-020-05051-1) contains supplementary material, which is available to authorized users.

Achieving cross provincial comparisons of osteoporosis screening performance from administrative health data

Administrative databases can be used to measure healthcare performance. This can lead to identification of high-performing practice characteristics and inform innovations. However, a key challenge is that administrative data cannot be easily combined across provinces. Comparable measures must be defined across provinces but operationalized within each province. The purpose of this work is to provide an example of defining a population health concept, osteoporosis screening, and creating measures to examine it across British Columbia, Ontario, and Nova Scotia, Canada. TRANSFORMATION is a study that seeks to improve the science and reporting of Primary Health Care performance. We used administrative data from the above three provinces to examine osteoporosis screening in those aged 65 years and older. Challenges of databases with different data elements and levels of methods development (e.g. macros) can be overcome for purposes of cross-provincial comparisons. Flexibility of analytic methods and frequent communication is needed.

Rush Fracture Liaison Service for capturing "missed opportunities" to treat osteoporosis in patients with fragility fractures

In spite of being a public health problem of pandemic proportions, osteoporosis continues to be underdiagnosed and undertreated especially in older adults with fragility fractures. Confirmation of this hypothesis resulted in the development of a novel Fracture Liaison Service (Rush FLS). Results of the first 12 months of operation revealed that patients with confirmed fragility fracture do not have a timely diagnosis at fracture occurrence or treatment of their disease. The Rush FLS is an effective fracture liaison model.

INTRODUCTION

Determining the prevalence of undiagnosed and untreated osteoporosis in fragility fracture patients, either admitted to an academic tertiary care center or treated and discharged from the center's emergency department to be followed in the endocrinology bone clinic, using an innovative, educational, low-cost, physician-run Fracture Liaison Service (FLS).

METHODS

An automated alert was integrated into the electronic medical record at Rush University Medical Center (RUMC), triggered by historical and/or acute fracture(s) in patients 50 years or older, in patients that were either admitted to the hospital or in patients evaluated in the emergency department and discharged to be followed in the endocrinology bone clinic. We report the results of the first 12 months of operation in patients admitted to the hospital.

RESULTS

First acute fragility fracture(s) were identified in 36% (80/223), only historical fragility fracture(s) in 28% (63/223) and both acute and historical fragility fracture(s) in 36% (80/223). The cumulative subgroup with historical fragility fractures with/without new fractures included 67% (96/143) without a previous diagnosis of osteoporosis. First acute fragility fracture group included 83.8% (67/80) without a previous diagnosis of osteoporosis. Rush FLS "captured missed opportunities" in 73.1% (163/223) of previously undiagnosed and 77.1% (172/223) of previously untreated osteoporosis patients. Dual-energy x-ray absorptiometry (DXA) prior to FLS consult was confirmed in 30% (67/223). Vitamin D deficiency (25-hydroxy vitamin D < 20 ng/ml) in 41.9% (78/186) including undetectable levels in 16.6% (31/186) and secondary hyperparathyroidism in 43.3% (78/180) were the most common laboratory confirmed secondary etiologies for bone loss.

CONCLUSIONS

This study reported undiagnosed, uninvestigated, and untreated osteoporosis in the majority of fragility fracture patients seen by the Rush FLS in the first 12 months of operation.