Ascertainment of aortic valve disease using administrative claims

Background

Administrative claims may be useful for characterizing patients with aortic stenosis (AS) and aortic regurgitation (AR) and estimating disease prevalence. However, the accuracy of diagnostic codes for aortic valve disease has not been well studied.

Purpose

To evaluate the validity of International Classification of Diseases, 10th Revision (ICD-10) codes for identification of AS and AR.

Methods

Using a large, transthoracic echocardiographic (TTE) report dataset linked to Medicare Fee-for-service (FFS) claims, 2017–2018, the performance of candidate claims to ascertain AS/AR status using standard TTE definitions was evaluated. Recursive partitioning with 10-fold cross validation was used to build the optimal prediction tree for AS/AR status using all ICD-10 codes as candidate predictors. The optimal performing claims algorithm was tested against patient outcomes in a separate 100% sample of Medicare FFS inpatient and outpatient claims, 2017–2019.

Results

Of those included in the derivation dataset (N=5497, mean age 74.4±11.0 years, 49.7% female), any AS or AR was present in 24% and 38.8%, respectively. The code I35.0 was optimal for identification of any AS with a sensitivity and specificity for any AS of 53.1% and 94.8%, respectively (Table 1). Amongst those with an I35.0 code, 40.3% had severe AS. Claims were unable to distinguish disease severity (i.e. severe vs. non-severe) or subtypes (e.g. bicuspid or rheumatic AS), and were insensitive and nonspecific for AR of any severity. Among all Medicare beneficiaries who received an TTE (N=3,783,249), those with an I35.0 code, compared to those without, had a higher risk of all-cause mortality (HR 1.65, 95% CI 1.63–1.67), heart failure hospitalization (HR 2.17, 95% CI 2.11–2.24), and aortic valve replacement (HR 32.35, 95% CI 31.46–33.27) (Table 2).

Conclusions

Amongst those receiving TTE, the ICD-10 code I35.0 in any position was optimal for identification of AS and identified a population at significant greater risk of all-cause mortality, heart failure hospitalization, and receipt of aortic valve replacement. Though 40.3% of those with I35.0 had severe AS, claims were unable to distinguish disease severity of subtype. Claims may be feasibly used to identify those with AS who may be at risk for adverse valve-related cardiovascular events and require future treatment.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): National, Heart, Lung, and Blood Institute

THIRD bedside ultrasound protocol for rapid diagnosis of undifferentiated shock: a prospective observational study

INTRODUCTION

It is clinically challenging to differentiate the pathophysiological types of shock in emergency situations. Here, we evaluated the ability of a novel bedside ultrasound protocol (Tamponade/tension pneumothorax, Heart, Inferior vena cava, Respiratory system, Deep venous thrombosis/aorta dissection [THIRD]) to predict types of shock in the emergency department.

METHODS

An emergency physician performed the THIRD protocol on all patients with shock who were admitted to the emergency department. All patients were closely followed to determine their final clinical diagnoses. The kappa index, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the initial diagnostic impression provided by the THIRD protocol, compared with each patient's final diagnosis.

RESULTS

In total, 112 patients were enrolled in this study. The kappa index between initial impression and final diagnosis was 0.81 (95% confidence interval=0.73-0.89; P<0.001). For hypovolaemic, cardiogenic, distributive, and obstructive types of shock, the sensitivities of the THIRD protocol were 100%, 100%, 93%, and 100%, respectively; the sensitivity for a 'mixed' shock aetiology was 86%. The negative predictive value of the THIRD protocol for all five types of shock was ≥96%.

CONCLUSION

Initial diagnostic judgements determined using the THIRD protocol showed favourable agreement with the final diagnosis in patients who presented with undifferentiated shock. The THIRD protocol has great potential for use as a bedside approach that can guide the rapid management of undifferentiated shock in emergency settings, particularly for patients with obstructive, hypovolaemic, or cardiogenic shock.

[Evaluation of CD107a and perforin expression detection in the diagnosis of primary hemophagocytic lymphohistiocytosis]

Objective: To evaluate the efficacy of rapid immunological indicator-degranulation function (CD107a) and perforin expression in the diagnosis of primary hemophagocytic lymphohistiocytosis (pHLH). Methods: The clinical data of 295 HLH patients who underwent genetic screening from April 2015 to June 2020 in Beijing Friendship Hospital, Capital Medical University, Beijing Jingdu Children's Hospital and Beijing Children's Hospital, Capital Medical University was collected and analyzed. The fitness of CD107a and Perforin expression with genetic screening was compared to evaluate the sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) of the two indicators, and the receiver operating characteristic (ROC) curves were generated and used to determine the optimal threshold (cut-off values) of CD107a and Perforin expression assays that would identify pHLH patients with a maximum sensitivity and specificity (Youden index). Results: In all 295 patients included, there were 156 males and 139 females, aged from 2 months to 70 years, with a median age of 18 years. In terms of distinguishing the type of pHLH associated with degranulation gene defect from all other genetic screening results, in the CD107a testing, the ROC curve was generated and showed an area under the curve (AUC) of 0.920 (P<0.001), and the optimal cut-off value was determined to be 7.15% with a sensitivity of 83.3% and specificity of 89.2% when the corresponding Youden index was maximized. The PPV and NPV were 33.3% and 98.8%, respectively. CD107a>10% had an accuracy of 81.6% in judging patients without degranulation-related gene defect and negative genetic screening results. In addition, in terms of distinguishing the type of familial hemophagocytic lymphohistiocytosis type 2 (FHL2) from all other genetic screening results, the sensitivity, specificity, PPV and NPV of the Perforin expression testing were 88.2%, 64.2%, 20.3% and 98.1%, respectively, based on the normal laboratory test value (≥ 81%). The ROC curve was established to further optimize the cut-off value. The AUC was 0.933 (P<0.001). The cut-off value corresponding to the maximum Youden index was 62.34%, and the sensitivity remained at 88.2%. While the specificity, PPV and NPV rose to 91.5%, 51.7% and 98.7%, respectively. Conclusions: CD107a and Perforin assays have good significance of early prediction for pHLH involved in impaired cytotoxic function. Selecting appropriate cut-off values can provide basis for accurate clinical diagnosis.

[Effect of outdoor time on the incidence of myopia among primary school students in 9 provinces of China]

Objective: We aimed to assess the effects of outdoor time in preventing incident myopia among primary school students and evaluate its differences among different grades to provide evidence for policy formulation related to myopia prevention. Methods: This study is a cohort study. We investigated 6 046 grade 1 to 5 students in 9 provinces, Jiangsu, Shanghai, Fujian, Shanxi, Henan, Hunan, Gansu, Chongqing, and Guangxi. In 2019, we measured their myopia on site. In 2020, we did a follow-up visit on those students to detect the myopia incidence rate. Information regarding outdoor time and myopia-related behaviors were obtained from a questionnaire within one week of visual acuity measurement in 2020. The chi-square test and Cochran-Armitage trend test compared the differences between groups. The Cox proportional hazards risk model was used to test the relationship between outdoor time and myopia. Results: In 2020, the overall myopia incidence rate of grade 1 to 5 students in the baseline was 27.5%; while 23.0% in grades 1 and 2 students and 31.7% in grades 3 to 5 students, respectively. After controlling for covariates, for students in grade 1 to 2, those with ≥1 hour of outdoor time per day were at 0.76 (95%CI: 0.62-0.93, P=0.008) times risk of being myopia than that of students with <1 hour of outdoor time per day; while for students in grades 3 to 5, an average of ≥3 hours of outdoor time per day was required to have a significant protective effect on myopia. The students with ≥3 hours of outdoor time per day were less likely to be myopia (OR=0.75, 95%CI: 0.61-0.93, P=0.007) than those students with <3 hours of outdoor time per day. Conclusions: For grade 1 and 2 students, 1 hour of outdoor time per day could reduce the incidence of myopia, whereas for grade 3 to 5 students, 3 hours of outdoor time per day could effectively reduce the incidence of myopia. Therefore, the recommendations for outdoor time as myopia prevention should be different for different grades. The higher the grade is, the more outdoor time should be spent to reduce myopia incidence. Moreover, other factors that affect myopia's incidence should be also paid attention to, and a comprehensive approach should be adopted to prevent and control the incidence of myopia.

[Overexpression of NAT10 induced platinum drugs resistance in breast cancer cell]

Objective: To observe the platinum drugs resistance effect of N-acetyltransferase 10 (NAT10) overexpression in breast cancer cell line and elucidate the underlining mechanisms. Methods: The experiment was divided into wild-type (MCF-7 wild-type cells without any treatment) group, NAT10 overexpression group (H-NAT10 plasmid transfected into MCF-7 cells) and NAT10 knockdown group (SH-NAT10 plasmid transfected into MCF-7 cells). The invasion was detected by Transwell array, the interaction between NAT10 and PARP1 was detected by co-immunoprecipitation. The impact of NAT10 overexpression or knockdown on the acetylation level of PARP1 and its half-life was also determined. Immunostaining and IP array were used to detect the recruitment of DNA damage repair protein by acetylated PARP1. Flow cytometry was used to detect the cell apoptosis. Results: Transwell invasion assay showed that the number of cell invasion was 483.00±46.90 in the NAT10 overexpression group, 469.00±40.50 in the NAT10 knockdown group, and 445.00±35.50 in the MCF-7 wild-type cells, and the differences were not statistically significant (P>0.05). In the presence of 10 μmol/L oxaliplatin, the number of cell invasion was 502.00±45.60 in the NAT10 overexpression group and 105.00±20.50 in the NAT10 knockdown group, both statistically significant (P<0.05) compared with 219.00±31.50 in wild-type cells. In the presence of 10 μmol/L oxaliplatin, NAT10 overexpression enhanced the binding of PARP1 to NAT10 compared with wild-type cells, whereas the use of the NAT10 inhibitor Remodelin inhibited the mutual binding of the two. Overexpression of NAT10 induced PARP1 acetylation followed by increased PARP1 binding to XRCC1, and knockdown of NAT10 expression reduced PARP1 binding to XRCC1. Overexpression of NAT10 enhanced PARP1 binding to LIG3, while knockdown of NAT10 expression decreased PARP1 binding to LIG3. In 10 μmol/L oxaliplatin-treated cells, the γH2AX expression level was 0.38±0.02 in NAT10 overexpressing cells and 1.36±0.15 in NAT10 knockdown cells, both statistically significant (P<0.05) compared with 1.00±0.00 in wild-type cells. In 10 μmol/L oxaliplatin treated cells, the apoptosis rate was (6.54±0.68)% in the NAT10 overexpression group and (12.98±2.54)% in the NAT10 knockdown group, both of which were statistically significant (P<0.05) compared with (9.67±0.37)% in wild-type cells. Conclusion: NAT10 overexpression enhances the binding of NAT10 to PARP1 and promotes the acetylation of PARP1, which in turn prolongs the half-life of PARP1, thus enhancing PARP1 recruitment of DNA damage repair related proteins to the damage sites, promoting DNA damage repair and ultimately the survival of breast cancer cells.

[Prevalence of malnutrition among elderly in the community of China: a Meta-analysis]

Objective: The prevalence of malnutrition in the community-dwelling older population of China was analyzed by Meta-analysis. Methods: Papers on the nutrition of community-dwelling elderly (≥60 years old) in China from August 1, 2011, to July 31, 2021, were retrieved through PubMed, Embase, the Cochrane Library, Web of Science, Wanfang Digital Database and China National Knowledge Infrastructure Database. Malnutrition was defined by nutritional assessment and screening tools of different studies. The random-effect model was fitted to calculate the prevalence. Subgroup analysis and inter-group difference analysis were performed according to the data included in the paper. Results: A total of 13 articles met the inclusion criteria, including 19 938 participants ≥60 years old. There are a total of seven methods for diagnosing criteria and defining malnutrition. The prevalence of malnutrition reported in papers varies greatly (2.4%-52.5%), of which seven pieces reported the prevalence of malnutrition risk (21.3%-67.0%). The Meta-analysis shows that the combined prevalence of malnutrition and risk of malnutrition was 41.2% (95%CI: 29.5%-54.0%, I²=99.6%, P<0.05) in the community-dwelling older population of China. The prevalence after 2017 is lower than that before 2017 (29.6% vs. 66.6%, χ²=274.20, P<0.05). The prevalence of men was lower than that of women (44.9% vs. 52.2%, χ²=10.67, P=0.001). The prevalence of non-living alone is lower than that of the older population living alone (41.2% vs. 49.6%, χ²=14.23, P<0.05). Conclusion: Malnutrition is common among the community-based older people in China. The prevalence of malnutrition is higher among older women and the elderly who live alone.

POS0683 EFFICACY AND SAFETY OF UPADACITINIB IN TNFi-IR PATIENTS WITH RHEUMATOID ARTHRITIS FROM THREE PHASE 3 CLINICAL TRIALS

Background

For patients with RA who are refractory to biologic DMARDs (bDMARDs), such as tumor necrosis factor inhibitors (TNFis), optimal disease control is less likely to be achieved with subsequent therapy.1 In line with recommendations from EULAR and ACR, switching to a treatment with a different mechanism of action is appropriate for these patients.

Objectives

To describe the efficacy and safety of upadacitinib (UPA) 15 mg once daily in patients with RA and an inadequate response or intolerance to TNFis (TNFi-IR).

Methods

A post hoc subgroup analysis was conducted in TNFi-IR patients who were treated with UPA 15 mg once daily in three Phase 3 clinical trials: SELECT-BEYOND,2 -CHOICE,3 and -COMPARE.4 For COMPARE, only patients treated with adalimumab and switched to UPA as rescue therapy were included. ≥20/50/70% improvement in ACR criteria, DAS28(CRP), CDAI, and SDAI, as well as change from baseline in HAQ-DI and other patient-reported outcomes (PROs) were reported through 24 weeks. Non-responder imputation was used for all missing categorical outcomes; as observed (COMPARE) or multiple imputation (CHOICE, BEYOND) were used for missing continuous outcomes. Pooled safety results were presented as exposure-adjusted event rates (EAERs) with a cut-off of June 30, 2021.

Results

568 TNFi-IR patients were included: 146 from BEYOND, 263 from CHOICE, and 159 from COMPARE. Mean duration since RA diagnosis was longer for BEYOND and CHOICE versus COMPARE; cardiovascular (CV) risk factors were common among this refractory population (Table 1). ACR20/50/70 and disease activity outcomes observed in the TNFi-IR population were generally consistent with the overall BEYOND2 and CHOICE3 bDMARD-IR populations, and consistent across the three studies in the TNFi-IR subgroups (Figure 1). Improvements in PROs including HAQ-DI, fatigue, pain, and morning stiffness over 24 weeks were observed (data not shown). Pooled safety results reporting 1574.8 patient-years (PY) of exposure in the TNFi-IR subgroup showed similar results to the overall BEYOND2 and CHOICE3 bDMARD-IR study populations, with EAERs of 3.1 events/100 PY for herpes zoster and 0.8 events/100 PY for adjudicated major adverse CV events, adjudicated venous thromboembolism (VTE), and malignancy excluding non-melanoma skin cancer. The EAER of any AE leading to death was 1.4 events/100 PY.

Table 1.

Baseline characteristics of TNFi-IR patients treated with UPA 15 mg

n (%), unless specifiedSELECT-BEYOND (n=146)SELECT-CHOICE (n=263)SELECT-COMPARE (ADA → UPA) (n=159)Female122 (83.6)219 (83.3)133 (83.6)Mean (SD) age, years56.6 (11.0)55.5 (11.1)53.9 (10.6)Mean (SD) duration of RA diagnosis, years13.2 (9.5)12.5 (9.4)8.2 (8.5)Concomitant csDMARDs MTX alone100 (70.4)195 (74.1)159 (100.0) MTX and other csDMARDs20 (14.1)25 (9.5)0 csDMARDs other than MTX22 (15.5)38 (14.4)0Concomitant oral steroids73 (50.0)140 (53.2)98 (61.6)1 prior bDMARD68 (46.6)172 (65.4)142 (89.3)2 prior bDMARDs40 (27.4)62 (23.6)17 (10.7)a≥3 prior bDMARDs38 (26.0)29 (11.0)0Failed ≥1 prior TNFi due to lack of efficacyb131 (89.7)223 (84.8)159 (100.0)History of VTE / CV event3 (2.1) / 28 (19.2)6 (2.3) / 20 (7.6)4 (2.5) / 14 (8.8)CV risk factors Hypertension72 (49.3)109 (41.4)68 (42.8) Diabetes mellitus22 (15.1)34 (12.9)17 (10.7) Smoking (current former past)68 (46.6)109 (41.5)55 (34.6) Elevated LDL-C (≥3.36 mmol/L)38 (26.0)52 (20.0)48 (30.2) Low HDL-C (≤1.55 mmol/L)80 (54.8)171 (65.0)88 (55.3)

aThese patients received one bDMARD before entry into SELECT-COMPARE.

bRemaining patients were intolerant to ≥1 prior TNFi.

Conclusion

In this post hoc subgroup analysis, TNFi-IR patients treated with UPA 15 mg achieved clinically meaningful efficacy responses over 24 weeks, with safety consistent with the overall bDMARD-IR patient population in the Phase 3 program.

References

[1]Rendas-Baum R, et al. Arthritis Res Ther 2011;13:R25;

[2]Genovese C, et al. Lancet 2018;391:2513–24;

[3]Rubbert-Roth A, et al. NEJM 2020;383:1511–21;

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

Acknowledgements

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. AbbVie and the authors thank all study investigators for their contributions and the patients who participated in this study. No honoraria or payments were made for authorship. Medical writing support was provided by Amy Wilson, MSc, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests

Roy M. Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Galvani, Gilead, GSK, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Biosplice, Bristol-Myers Squibb, Flexion, Gilead, Horizon, Eli Lilly, Galvani, Janssen, Novartis, Pfizer, Sanofi-Aventis, Selecta, Teva, UCB, Viela, and Vorso, Louis Bessette Speakers bureau: AbbVie, Amgen, Bristol-Meyers Squibb, Celgene, Eli Lilly, Fresenius Kabi, Gilead, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi-Aventis, Teva, and UCB, Consultant of: AbbVie, Amgen, Bristol-Meyers Squibb, Celgene, Eli Lilly, Fresenius Kabi, Gilead, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi-Aventis, Teva, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Meyers Squibb, Celgene, Eli Lilly, Fresenius Kabi, Gilead, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi-Aventis, Teva, and UCB, Jeffrey Sparks Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Gilead, Inova Diagnostics, Janssen, Optum, and Pfizer, Stephen Hall Consultant of: AbbVie, Amgen, Bristol-Meyers Sqibb, Eli Lilly, Gilead, Janssen, Merck, Novartis, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Meyers Sqibb, Eli Lilly, Gilead, Janssen, Merck, Novartis, and UCB, Manish Jain Consultant of: AbbVie, Amgen, Eli Lilly, Novartis, and Pfizer, Grant/research support from: AbbVie, Amgen, Eli Lilly, Novartis, and Pfizer, Adriana Kakehasi Speakers bureau: AbbVie, Amgen, Eli Lilly, Fresenius Kabi, Janssen, Novartis, Pfizer, Sandoz, and UCB, Consultant of: AbbVie, Amgen, Eli Lilly, Fresenius Kabi, Janssen, Novartis, Pfizer, Sandoz, and UCB, Grant/research support from: AbbVie, Amgen, Eli Lilly, Fresenius Kabi, Janssen, Novartis, Pfizer, Sandoz, and UCB, Yanna Song Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Sebastian Meerwein Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Ryan DeMasi Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Jessica Suboticki Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Andrea Rubbert-Roth Consultant of: AbbVie, AbbVie Deutschland, Amgen, Bristol-Myers Squibb, Chugai Pharmaceuticals, Eli Lilly, F. Hoffman-La Roche, Gilead Sciences, Janssen Global Services, Novartis, and Sanofi Pasteur

POS0677 CONSISTENCY IN TIME TO RESPONSE WITH UPADACITINIB AS MONOTHERAPY OR COMBINATION THERAPY AND ACROSS PATIENT POPULATIONS WITH RHEUMATOID ARTHRITIS

Background

Upadacitinib (UPA) has demonstrated efficacy in patients with moderate-to-severe rheumatoid arthritis (RA) across various patient populations.1–4

Objectives

This post hoc analysis aimed to evaluate the consistency in time to achieving meaningful clinical response with UPA 15 mg + conventional synthetic (cs) DMARDs in biologic (b) DMARD-inadequate responder (IR) versus csDMARD-IR patients with RA as well as with UPA 15 mg monotherapy versus UPA 15 mg + csDMARDs in csDMARD-IR patients.

Methods

Patients originally randomized to UPA 15 mg once daily from four Phase 3 trials were included in this analysis: SELECT-BEYOND1 and SELECT-CHOICE2 (UPA 15 mg + csDMARDs in bDMARD-IR patients), SELECT-NEXT3 (UPA 15 mg + csDMARDs in csDMARD-IR patients), and SELECT-MONOTHERAPY4 (UPA 15 mg monotherapy in methotrexate-IR patients). Time to response was estimated using the Kaplan–Meier method for clinical outcomes over 24 weeks (26 weeks in SELECT-MONOTHERAPY). Clinical outcomes included achievement of 28-joint Disease Activity Score with C-reactive protein (DAS28[CRP]) ≤3.2; low disease activity (LDA) defined as Clinical Disease Activity Index (CDAI) ≤10 and Simple Disease Activity Index (SDAI) ≤11; and 50% improvement in American College of Rheumatology (ACR) core components and morning stiffness (MS) duration/severity. Data presented were as observed.

Results

Overall, 905 patients were included (SELECT-BEYOND: n=164; SELECT-CHOICE: n=303; SELECT-NEXT: n=221; SELECT-MONOTHERAPY: n=217). csDMARD-IR patients had a mean disease duration of 7.3 (SELECT-NEXT) or 7.5 years (SELECT-MONOTHERAPY); bDMARD-IR patients had a mean disease duration of 12.4 years, with a more refractory population (≥3 prior bDMARDs) in SELECT-BEYOND (23%) than SELECT-CHOICE (10%). In general, the median time to DAS28(CRP) ≤3.2, CDAI LDA, 50% improvement in ACR core components, and 50% improvement in MS duration/severity were consistent across the studies in bDMARD-IR and csDMARD-IR patients. For SELECT-BEYOND, SELECT-CHOICE, SELECT-NEXT, and SELECT-MONOTHERAPY, the median (95% CI) time to achieve DAS28(CRP) ≤3.2 was 12 (12, 16), 12 (8, 12), 12 (8, 12), and 14 (8, 14) weeks, respectively (Figure 1), and the median time to achieve CDAI LDA was 20 (12, 24), 16 (12, 16), 16 (12, 16), and 20 (14, 20) weeks, respectively (Figure 2). A longer median (95% CI) time to achieve SDAI LDA was observed with UPA monotherapy (20 [14, 20] weeks) versus UPA + csDMARDs (12 [12, 16] weeks) in csDMARD-IR patients. Among bDMARD-IR patients, the median (95% CI) time to 50% improvement in pain was longer in SELECT-BEYOND versus SELECT-CHOICE (16 [12, 20] versus 8 [8, 12] weeks).

Conclusion

In diverse patient populations with RA, patients treated with UPA 15 mg, as monotherapy or with csDMARDs, generally demonstrated consistent time to achieving DAS28(CRP) ≤3.2, CDAI LDA, and 50% improvement in clinical outcomes.

References

[1]Genovese MC, et al. Lancet 2018;391:2513–24.

[2]Rubbert-Roth A, et al. N Engl J Med 2020;383:1511–21.

[3]Burmester GR, et al. Lancet 2018;391:2503–12.

[4]Smolen JS, et al. Lancet 2019;393:2303–11.

Acknowledgements

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

Disclosure of Interests

Andrea Rubbert-Roth Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Chugai, Eli Lilly, Gilead, Janssen, Novartis, Roche, and Sanofi, Bernard Combe Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead/Galapagos, Janssen, Merck, Novartis, Pfizer, Roche/Chugai, and Sanofi, Consultant of: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead/Galapagos, Janssen, Merck, Novartis, Pfizer, Roche/Chugai, and Sanofi, Zoltán Szekanecz Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Gedeon Richter, MSD, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Gedeon Richter, MSD, Pfizer, Roche, Sanofi, and UCB, Stephen Hall Speakers bureau: Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB; and research grants from AbbVie, Janssen, Merck, and UCB, Consultant of: Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB; and research grants from AbbVie, Janssen, Merck, and UCB, Boulos Haraoui Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Suzan Attar: None declared, Anna-Karin H Ekwall Consultant of: AbbVie and Pfizer, Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Tim Shaw Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Orsolya Nagy Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Ricardo Xavier Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, and UCB

AB0333 SUSTAINABILITY OF RESPONSE TO UPADACITINIB AMONG PATIENTS WITH ACTIVE RHEUMATOID ARTHRITIS REFRACTORY TO BIOLOGICAL DISEASE-MODIFYING ANTI-RHEUMATIC DRUGS

Background

Sustained clinical remission (REM) is the primary treatment goal for patients with rheumatoid arthritis (RA), with low disease activity (LDA) being an appropriate target for treatment-refractory patients.1,2

Objectives

To evaluate the sustainability of response to the JAK inhibitor, upadacitinib (UPA) 15 mg once daily (QD), among patients with prior inadequate response or intolerance to biologic DMARDs.

Methods

Data come from the 12-week, phase 3 randomized, placebo (PBO)-controlled SELECT-BEYOND trial of UPA 15 mg or 30 mg QD in patients with moderate to severe RA on stable background conventional synthetic (cs) DMARDs. Initiation, change, or discontinuation of background RA medications, including ≤2 csDMARDs, was allowed starting at Week 24. Patients completing the 12-week trial were able to enter a long-term extension of up to 5 yrs with all PBO patients switching to UPA.3 This post hoc analysis evaluated REM (CDAI ≤2.8; SDAI ≤3.3), LDA (CDAI≤10; SDAI≤11), and DAS28(CRP) <2.6/≤3.2 at first occurrence of response before Week 60, as well as at 3, 6, and 12 months following initial response in patients randomized to UPA 15 mg. For those patients who achieved REM/LDA, Kaplan-Meier was used to define the time from when the response was first achieved to the earliest date at which the response was lost at two consecutive visits or discontinuation of study drug. The predictive ability of time to REM/LDA was evaluated using Harrell’s concordance (c)-index (range: 0 to 1, where 0.5 indicates a model that is no better at predicting an outcome than random chance). The date of the last follow up was 16 April 2018, when all patients had reached the Week 60 visit. Non-responder imputation was used for missing data. Only data from the approved 15 mg dosage are reported here.

Results

In patients with active RA despite prior treatment with at least one bDMARD, 34% and 79% of those receiving UPA 15 mg + background csDMARD(s) achieved CDAI REM or LDA through Week 60, respectively. Sustained CDAI REM was attained by 30%, 26%, and 16% of patients randomized to UPA at 3, 6, and 12 months post initial response, while CDAI LDA was achieved by 68%, 61%, and 50% of patients during the same time points (Figure 1). Time to initial clinical response weakly predicted sustained REM but did not predict sustained LDA, with a c-index (95% CI) of 0.62 (0.49, 0.74) and 0.52 (0.44, 0.61), respectively. Through the last follow-up visit at Week 60, 39/61% of patients on UPA remained in CDAI REM/LDA (Figure 2). Of those who lost CDAI REM, 58% remained in CDAI LDA, and 22% recaptured REM by the cut-off date; 18% of patients who lost CDAI LDA recaptured response. Similar results were observed for REM and LDA based on SDAI and for DAS28(CRP) <2.6/≤3.2.

Conclusion

Among patients with inadequate response or intolerance to bDMARDs, over three-quarters on UPA 15 mg achieved CDAI LDA, a relevant therapeutic target for these treatment-refractory patients, and nearly two-thirds of those maintained this response through 60 weeks. Additionally, about one-third of UPA-treated patients attained CDAI REM and maintained that response over 60 weeks.

References

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

[2]Singh et al. Arthritis Rheumatol 2016;68:1–26.

[3]Genovese, et al. Lancet 2018;391:2513–24.

Acknowledgements

AbbVie funded these studies and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. No honoraria or payments were made for authorship. Medical writing support was provided by Matthew Eckwahl, PhD, of AbbVie.

Disclosure of Interests

Ronald van Vollenhoven Consultant of: AbbVie, AstraZeneca, Biotest, Bristol-Myers Squibb, Celgene, Eli Lilly, GSK, Janssen, Medac, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Arthrogen, Bristol-Myers Squibb, Eli Lilly, GSK, Pfizer, and UCB, Stephen Hall Consultant of: AbbVie, BMS, Lilly, Janssen, Pfizer, UCB, and Novartis., Grant/research support from: AbbVie, BMS, Lilly, Janssen, Pfizer, UCB, and Novartis., Alvin F. Wells Consultant of: AbbVie, Sebastian Meerwein Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Jessica Suboticki Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Roy M. Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, and UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Genentech, Janssen, Novartis, Pfizer Inc, Regeneron, Roche, Sanofi-Aventis and UCB

POS0686 EFFECTIVENESS OF UPADACITINIB IN THE TREATMENT OF RHEUMATOID ARTHRITIS: ANALYSIS OF 6-MONTH REAL-WORLD DATA FROM THE UNITED RHEUMATOLOGY NORMALIZED INTEGRATED COMMUNITY EVIDENCE (UR-NICETM) DATABASE

Background

The efficacy of upadacitinib (UPA), an oral Janus kinase inhibitor (JAKi), in the treatment of rheumatoid arthritis (RA) has been demonstrated in the phase 3 SELECT clinical trial program.1–6 However, few real-world data have been reported to date.

Objectives

To assess the 6-month effectiveness of UPA in patients (pts) with RA initiating UPA treatment in clinical practice.

Methods

This observational study included US-based pts from the United Rheumatology Normalized Integrated Community Evidence (UR-NICE) database who initiated UPA 15 mg once daily from Aug 2019 to the data cut-off in Nov 2021. Pts with ≥6 months of baseline (BL) data before UPA initiation, and with Clinical Disease Activity Index (CDAI) score recorded at BL and 6 months (±45 days) after initiation, were included in the analysis. Effectiveness measures included CDAI score, Routine Assessment of Patient Index Data 3 (RAPID3), and Disease Activity Score in 28 joints based on C-reactive protein (DAS28-CRP); patient-reported outcomes (PROs) including Health Assessment Questionnaire-Disability Index (HAQ-DI), Pain, and Patient’s Global Assessment of Disease Activity (PtGA); and Physician’s Global Assessment of Disease Activity (PhGA). Subgroup analyses were conducted by prior tumor necrosis factor inhibitor (TNFi) and tofacitinib (TOFA) treatment history.

Results

363 pts were included in the analysis and most were female (80.2%) (Table 1). 140 (39%) received UPA monotherapy and 223 (61%) received UPA plus conventional synthetic (cs) disease-modifying antirheumatic drugs (DMARDs). 83% of pts received prior csDMARDs, 72% prior biologics (TNFi 55%), and 41% JAKis (TOFA 39%). Overall, 46% (166/363), 23% (57/245), and 55% (95/173) of pts achieved LDA by CDAI, RAPID3, and DAS28-CRP, respectively, and 14% (51/363), 16% (39/245), and 36% (62/173) of pts achieved remission (REM) by CDAI, RAPID3, and DAS28-CRP, respectively. Results were similar regardless of prior TNFi or TOFA exposure (Figure 1). Improvements from BL were seen in PhGA and all PROs in the total population and all subgroups.

Table 1.

Demographic and baseline characteristics

Parameter, n (%)Full analysis setPrior TNFiPrior TOFA(N=363)(n=199)(n=143)Female291 (80.2)156 (78.4)119 (83.2)Age, years<4022 (6.1)11 (5.5)8 (5.6)40–<65240 (66.1)132 (66.3)94 (65.7)≥65101 (27.8)56 (28.1)41 (28.7)Oral steroid use185 (51.0)103 (51.8)83 (58.0)Parameter, mean (SD)NMean (SD)nMean (SD)nMean (SD)Duration of RA, years2764.5 (3.1)1625.1 (3.0)1135.1 (2.9)Body mass index, kg/m232130.0 (6.9)17529.9 (6.6)12529.2 (6.7)Oral steroid dose (prednisone equivalent), mg/day1547.9 (6.9)877.8 (6.5)707.6 (6.1)Methotrexate dose, mg/week11918.3 (4.9)7417.8 (5.2)3718.2 (4.7)C-reactive protein, mg/L2289.6 (16.2)1329.4 (15.0)9011.3 (17.9)CDAI36321.2 (12.8)19922.1 (13.0)14321.7 (13.3)RAPID32684.7 (2.1)1414.7 (2.2)1004.9 (2.1)DAS28-CRP2283.9 (1.3)1324.0 (1.4)904.2 (1.3)HAQ-DIa2732.6 (2.1)1482.8 (2.2)1063.0 (2.2)Painb33859.6 (26.6)18658.4 (27.2)13161.3 (25.1)PtGAb36354.1 (25.6)19954.7 (26.9)14355.9 (25.2)PhGAb36341.3 (26.0)19941.2 (24.8)14340.7 (26.8)

a0–10 visual analog scale. b0–100 visual analog scale. SD, standard deviation.

Conclusion

In this study, almost half (46%) of pts treated with UPA achieved CDAI LDA at 6 months and 14% achieved CDAI REM. Improvements in all PROs and PhGA were observed. Effectiveness of UPA was not impacted by prior TNFi or TOFA exposure, supporting UPA as an effective treatment option in clinical practice, including in pts with prior exposure to advanced therapy.

References

[1]Burmester GR, et al. Lancet 2018;391:2503–12.

[2]Smolen JS, et al. Lancet 2019;393:2303–11.

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

[4]Genovese MC, et al. Lancet 2018;391:2513–24.

[5]van Vollenhoven R, et al. Arthritis Rheumatol 2020;72:1607–20.

[6]Rubbert-Roth A, et al. N Engl J Med 2020;383:1511–21.

Acknowledgements

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. AbbVie and the authors thank all study investigators for their contributions and the patients who participated in this study. No honoraria or payments were made for authorship. Medical writing support was provided by Laura Chalmers, PhD, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests

Allan Gibofsky Shareholder of: AbbVie, Amgen, Johnson & Johnson, and Pfizer (stocks), Consultant of: AbbVie, Celgene, Eli Lilly, Flexion, Pfizer, Relburn Pharma, and Samumed (consulting fees); and Gerson Lehrman Group (paid consultant with investment analysts), Mark E. Pearson Shareholder of: AbbVie (may own stock or options), Andrew Concoff Speakers bureau: Flexion Therapeutics and Exagen, Consultant of: Flexion Therapeutics and Exagen, Anna Shmagel Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Patrick Zueger Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Yanna Song Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Lauren Smith Shareholder of: AbbVie (may own stock or options), Employee of: AbbVie, Grace C. Wright Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Exagen, Myriad Autoimmune, Novartis, Sanofi/Regeneron, UCB, and Vindico, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Exagen, Gilead, Janssen, Myriad Autoimmune, Novartis, Pfizer, Sanofi/Regeneron, and UCB, Employee of: Association of Women in Rheumatology (President and Founder)

POS1163 PHARMACOKINETICS OF PEGLOTICASE AND METHOTREXATE POLYGLUTAMATE(S) IN PATIENTS WITH UNCONTROLLED GOUT RECEIVING PEGLOTICASE AND CO-TREATMENT WITH METHOTREXATE

Background

In a prior open-label, single-arm trial in adults with uncontrolled gout (MIRROR open-label [OL] trial), methotrexate (MTX) co-treatment with pegloticase suggested improved efficacy of pegloticase by reducing its immunogenicity.1,2 The current randomized, controlled trial (MIRROR RCT) confirmed that pegloticase-MTX co-therapy markedly increased pegloticase response rate (response defined as serum uric acid <6 mg/dL during ≥80% of Month 6) compared to pegloticase-placebo (PBO) co-therapy (71.0% vs. 38.5%) with a decreased infusion reaction rate and no new safety signals reported.

Objectives

To evaluate systemic exposures of pegloticase and its immunogenicity in uncontrolled gout patients receiving pegloticase with and without MTX as part of the MIRROR RCT; and to determine exposure of methotrexate polyglutamate(s) (MTX-PGs) in uncontrolled gout patients through Month 6 of treatment.

Methods

In MIRROR RCT, MTX (15 mg/wk) or matching PBO was given orally 4 weeks prior to the first pegloticase dose and continued weekly, in combination with pegloticase 8 mg given intravenously every 2 weeks, over a 52-week treatment period. Pre-infusion blood samples were collected to measure MTX polyglutamates (MTX-PGs, including MTX-PG1-5) in red blood cells and pre- and post-infusion serum samples were obtained to measure trough (Cmin) and peak (Cmax) concentrations of pegloticase, respectively, at multiple visits. MTX-PG and pegloticase concentrations were summarized by visit and by treatment group. Pre-infusion serum samples for anti-polyethylene glycol (PEG) antibody (Ab) measurement were also collected at multiple pre-defined time points. Anti-PEG Ab incidence and titer were summarized by visit and by treatment group.

Results

Overall, higher Cmax and Cmin of pegloticase were observed in the pegloticase + MTX group than in the pegloticase + PBO group (Figure 1). At Week 14, median (first quartile [Q1], third quartile [Q3]) Cmin was 1.32 (0.73, 1.74) µg/mL and 0.63 (0.30, 1.28) µg/mL for the pegloticase + MTX and pegloticase + PBO groups, respectively. Median (Q1, Q3) Cmax was 3.01 (1.94, 3.94) µg/mL and 2.66 (1.45, 3.20) µg/mL for the pegloticase + MTX and pegloticase + PBO groups, respectively. Improved pegloticase response was associated with higher pegloticase concentrations. At Week 14, Cmin was below the quantitation limit (0.6 µg/mL) for 8 of 10 non-responders and 1.26 (0.72, 1.71) µg/mL for responders. MTX co-administration reduced the incidence of new anti-PEG antibody formation. The proportion of subjects with an increase from baseline in anti-PEG Ab titers or who were negative at baseline and developed an anti-PEG Ab response at ≥1 post-dose time point during pegloticase treatment was 29.5% and 51.0%, for the pegloticase + MTX and pegloticase + PBO groups, respectively. The pegloticase + MTX group had overall lower titer levels than those in the pegloticase + PBO group. Positive anti-PEG Ab status was associated with a lower pegloticase Cmin. Concentrations of MTX-PGs were maintained during the treatment course in the pegloticase + MTX group, suggesting compliance with MTX administration. There was no apparent difference in concentrations of MTX-PGs (including MTX-PG3, the predominant form of MTX-PGs4) between responders and non-responders. MTX-PG concentrations were in the same range as those reported for low-dose oral MTX use in patients with rheumatoid arthritis,3 suggesting no impact of pegloticase on MTX PK.

Conclusion

Pegloticase 8 mg IV every 2 weeks with MTX co-treatment (oral 15 mg weekly) reduced anti-PEG Ab incidence and resulted in higher pegloticase exposures compared to pegloticase administered with PBO, consistent with the increased clinical efficacy observed with pegloticase + MTX co-administration.

References

[1]Botson J, et al. J Rheumatol 2021;48:767-74

[2]Song Y, et al. Arthritis Rheum 2020;72(suppl 10)

[3]Dervieux T, et al. Ann Rheum Dis 2013;72:908-10

[4]Choi R. J Pharm Biomed Anal 2021;201:114124

Disclosure of Interests

Yan Xin Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Yang Song Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Michael E. Weinblatt Consultant of: Horizon Therapeutics, Jason Chamberlain Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Jennifer Zarzoso Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Katie Obermeyer Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Stephen Sainati Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Colleen Canavan Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics, Srini Ramanathan Shareholder of: Horizon Therapeutics, Employee of: Horizon Therapeutics

POS0643 SUSTAINABILITY OF RESPONSE BETWEEN UPADACITINIB AND ADALIMUMAB IN PATIENTS WITH RHEUMATOID ARTHRITIS: RESULTS THROUGH 3 YEARS FROM THE SELECT-COMPARE TRIAL

Background

The primary treatment target for patients with active rheumatoid arthritis (RA) is sustained clinical remission (REM) or low disease activity (LDA).1,2 A greater proportion of patients with RA and inadequate response to methotrexate (MTX) receiving the JAK inhibitor, upadacitinib (UPA), achieved REM/LDA compared with adalimumab (ADA), both with background MTX, through 26 weeks in the phase 3, SELECT-COMPARE trial.3

Objectives

We assessed sustainability of response over 3 years in UPA-treated patients with RA.

Methods

SELECT-COMPARE included a 26-week, double-blind, placebo (PBO)-controlled period, a 48-week, double-blind active comparator-controlled period, and an ongoing long-term extension for up to 10 years. Patients on background MTX received UPA 15 mg once daily, PBO, or ADA 40 mg every other week. Patients who did not achieve at least 20% improvements in tender and swollen joint counts (Weeks 14-22) or LDA (CDAI ≤10 at Week 26) were rescued from UPA to ADA or PBO/ADA to UPA. This post hoc analysis evaluated clinical REM (CDAI ≤2.8; SDAI ≤3.3), LDA (CDAI ≤10; SDAI ≤11), and DAS28(CRP) <2.6/≤3.2 at first occurrence (prior to treatment switch [rescue]), as well as over 3 years following initial response in patients randomized to UPA or ADA. For those patients who achieved REM/LDA, Kaplan-Meier was used to define the time from when the response was first achieved to the earliest date at which the response was lost at two consecutive visits, discontinuation of study drug, or losing response at the time of rescue. The predictive ability of time to CDAI REM/LDA was assessed using Harrell’s concordance (c)-index (range: 0 [all predictions wrong] to 1.0 [perfect predictive ability]. Non-responder imputation was used for missing data.

Results

Through 3 years, a significantly higher proportion of patients receiving UPA + MTX vs ADA + MTX achieved CDAI REM (47% vs 35%, P = 0.001) as well as CDAI LDA (70% vs 60%, P = 0.001). At 30 months after first occurrence of response, CDAI REM/LDA was sustained in 19%/42% of patients randomized to UPA and 10%/30% of patients randomized to ADA (Figure 1). Time to initial clinical response did not appear to be predictive of sustained disease control. The c-index for CDAI REM/LDA was 0.50/0.60 on UPA vs 0.49/0.56 on ADA. Through the last follow-up visit, 37%/58% of patients receiving UPA and 27%/48% on ADA remained in CDAI REM/LDA, respectively (Figure 2). Of patients who lost CDAI REM, 68% on UPA and 55% on ADA remained in LDA. Additionally, roughly similar proportions on UPA and ADA recaptured CDAI REM/LDA (UPA, 40%/17%; ADA, 48%/19%). Similar results were observed for REM/LDA based on SDAI and for DAS28(CRP) <2.6/≤3.2.

Conclusion

Among patients with inadequate response to MTX, a higher proportion receiving UPA + MTX achieved remission or LDA across disease activity measures vs ADA + MTX. UPA-treated patients demonstrated a consistently higher sustained response rate over 3 years compared to those receiving ADA. Furthermore, significant proportions of patients who lost response on either UPA or ADA were able to recapture remission or LDA.

References

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

[2]Singh et al. Arthritis Rheumatol 2016;68:1–26.

[3]Fleischmann et al. Arthritis Rheumatol 2019;71:1788–1800.

Acknowledgements

AbbVie funded these studies and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. No honoraria or payments were made for authorship. Medical writing support was provided by Matthew Eckwahl, PhD, of AbbVie.

Disclosure of Interests

Peter Nash Speakers bureau: AbbVie, BMS, Pfizer, Gilead/Galapagos, Sanofi, Celgene, Novartis, Lilly, Janssen, UCB, Samsung, MSD, Roche, Consultant of: AbbVie, BMS, Pfizer, Gilead/Galapagos, Sanofi, Celgene, Novartis, Lilly, Janssen, UCB, Samsung, MSD, Roche, Grant/research support from: AbbVie, BMS, Pfizer, Gilead/Galapagos, Sanofi, Celgene, Novartis, Lilly, Janssen, UCB, Samsung, MSD, Roche, Arthur Kavanaugh Consultant of: AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, and UCB, Grant/research support from: AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, and UCB, Maya H Buch Speakers bureau: AbbVie, Boehringer Ingleheim, Eli Lilly, Merck-Serono, and Sanofi, Consultant of: AbbVie, Boehringer Ingleheim, Eli Lilly, Merck-Serono, and Sanofi, Grant/research support from: Pfizer, Gilead, and UCB, Bernard Combe Consultant of: AbbVie, BMS, Celltrion, Gilead, Galapagos, Janssen, Eli Lilly, MSD, Pfizer, Roche Chugai, Louis Bessette Speakers bureau: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, Consultant of: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, Grant/research support from: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, In-Ho Song Shareholder of: AbbVie Inc., Employee of: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, Tim Shaw Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Jessica Suboticki Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Roy M. Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, and UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Genentech, Janssen, Novartis, Pfizer Inc, Regeneron, Roche, Sanofi-Aventis and UCB

POS0693 IMPACT OF UPADACITINIB VERSUS ABATACEPT ON INDIVIDUAL DISEASE OUTCOMES IN PATIENTS WITH RHEUMATOID ARTHRITIS AND INADEQUATE RESPONSES TO BIOLOGIC DMARDS

Background

The phase 3 SELECT-CHOICE trial of patients with rheumatoid arthritis (RA) and prior inadequate response to biologic DMARD(s) (bDMARD-IR) demonstrated superiority of the JAK inhibitor upadacitinib (UPA) vs abatacept (ABA) in the mean change from baseline (BL) in DAS28(CRP) and in the proportion achieving DAS28(CRP) <2.6 at week (wk) 12, with higher incidence of serious adverse events reported in the UPA treatment group.

Objectives

To evaluate the impact of UPA vs ABA on individual components of composite measures of disease activity in SELECT-CHOICE.

Methods

In SELECT-CHOICE, a double-blind phase 3 trial, bDMARD-IR patients were randomly assigned to UPA 15 mg once daily or ABA, each with background conventional synthetic DMARDs, for 24 wks. For this post hoc analysis, the proportions of patients achieving improvement from BL through wk 24 in ACR core variables (including SJC, TJC, Patient Global Assessment [PtGA], Physician Global Assessment [PhGA], pain, HAQ-DI, and hsCRP) and Boolean remission criteria were evaluated. Differences in the cumulative distributions of CDAI, DAS28(hsCRP), SDAI, and ACR-n (the lowest of percent change in TJC, percent change in SJC, or median of the other 5 ACR components) were determined using the Kolmogorov-Smirnov test and are reported as observed. For all other variables, non-responder imputation was applied for missing data. Nominal P values are provided throughout.

Results

A total of 616 bDMARD-IR patients with moderate to severe RA were randomized in SELECT-CHOICE (UPA 15 mg, n=303; ABA, n=309). BL demographic and disease characteristics were generally comparable between treatment groups, with a mean disease duration of approximately 12 years and mean CDAI of 39.6. At wk 12, more patients receiving UPA vs ABA achieved ≥50% improvements from BL in TJC68, PtGA, and hsCRP, with comparable proportions observed between UPA and ABA for the remaining ACR components (Figure 1). At wk 24, similar proportions of patients receiving UPA and ABA achieved ≥50% improvements in all but the hsCRP component. Overall, 15% and 26% of patients on UPA compared with 6% and 15% on ABA demonstrated ≥50% improvements across all ACR components at wks 12 and 24, respectively. At wks 12 and 24, Boolean remission was achieved by 6% and 14% of patients on UPA vs 2% and 10% of patients on ABA, respectively; the proportion of patients in both treatment groups achieving the individual Boolean components were also reported (Table 1). While comparable at BL, cumulative distributions of CDAI, SDAI, DAS28(hsCRP), and ACR-n were improved on UPA vs ABA at wk 12 (all nominal P <0.05); differences persisted for most measures at wk 24.

Table 1.

Proportions of Patients Achieving Boolean Remission and Its Components at Week 12 and 24 (NRI)

Week 12Week 24n (%)UPA 15 mgABAUPA 15 mgABA(N=303)(N=309)(N=303)(N=309)Boolean Remission19 (6)***5 (2)42 (14)*30 (10) PtGA ≤1054 (18)***29 (9)80 (26)*66 (21) TJC ≤189 (29)***64 (21)134 (44)*115 (37) SJC ≤1127 (42)**106 (34)169 (56)*152 (49) hsCRP ≤1 mg/dL257 (85)***209 (68)244 (81)***199 (64)

Nominal ***P <.001, **P <.01, *P <.05 for UPA vs ABA. ABA, abatacept; PtGA, Patient’s Global Assessment of disease severity; UPA, upadacitinib.

Conclusion

In this post hoc analysis of bDMARD-IR RA patients, improvements in components of disease measures were reported for both UPA and ABA through 24 weeks, with numeric differences noted for several components. Nominally higher attainment of Boolean remission and its components were observed for UPA over ABA.

References

[1]Rubbert-Roth A, et al. N Engl J Med 2020; 383:1511-21.

Acknowledgements

AbbVie and the authors thank the patients, study sites, and investigators who participated in these clinical trials. AbbVie funded these studies and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship. Medical writing support was provided by Matthew Eckwahl, PhD, of AbbVie.

Disclosure of Interests

Ronald van Vollenhoven Speakers bureau: AbbVie, Galapagos, GSK, Janssen, Pfizer, R-Pharma, UCB, Consultant of: AbbVie, AstraZeneca, Biogen, BMS, Galapagos, Janssen, Miltenyi, Pfizer, UCB, Grant/research support from: Research: BMS, GSK, UCB; Educational programs: MSD, Pfizer, Roche, Andrea Rubbert-Roth Speakers bureau: AbbVie, Pfizer, Sanofi, UCB, BMS, Lilly, Gilead, Roche, Consultant of: AbbVie, Gilead, Lilly, BMS, Sanofi, R-Pharm, Stephen Hall Consultant of: AbbVie, BMS, Lilly, Janssen, Pfizer, UCB, Novartis, Grant/research support from: AbbVie, BMS, Lilly, Janssen, Pfizer, UCB, Novartis, Ricardo Xavier Consultant of: AbbVie, Amgen, BMS, Lilly, Janssen, Novartis, Pfizer, UCB, Anna Shmagel Shareholder of: AbbVie, Employee of: AbbVie, Yanna Song Shareholder of: AbbVie, Employee of: AbbVie, Samuel Anyanwu Shareholder of: AbbVie, Employee of: AbbVie, Vibeke Strand Consultant of: AbbVie, Amgen, Arena, AstraZeneca, Bayer, BMS, Boehringer Ingelheim, Chemocentryx, BMS, Celltrion, Lilly, Genentech/Roche, Gilead, GlaxoSmithKline, Ichnos, Inmedix, Janssen, Kiniksa, Lilly, Merck, Myriad Genetics, Novartis, Pfizer, Regeneron Pharmaceuticals, Rheos, R-Pharma, Samsung, Sandoz, Sanofi, Scipher, Setpoint, Sorrento, Spherix, UCB

POS0540 CLINICAL OUTCOMES ASSOCIATED WITH GLUCOCORTICOID DISCONTINUATION AMONG PATIENTS WITH RHEUMATOID ARTHRITIS RECEIVING UPADACITINIB OR ADALIMUMAB

Background

Patients (pts) with rheumatoid arthritis (RA) are often administered glucocorticoids (GCs) as bridging therapy when initiating or adjusting disease-modifying antirheumatic drugs (DMARDs). Due to their systemic effects, short-term use of GCs at the lowest possible dose is recommended with rapid tapering.1

Objectives

We describe GC discontinuation patterns and the associated clinical outcomes in pts with RA receiving upadacitinib (UPA) or adalimumab (ADA).

Methods

SELECT-COMPARE is a randomized phase 3 trial of UPA vs placebo and ADA with a 48-week (wk) double-blind treatment period and a 10-year long-term extension in pts with RA receiving concomitant methotrexate (MTX) who had an inadequate response to MTX.2 Background GCs (≤10 mg/day prednisone or equivalent) were permitted and could be tapered or discontinued starting at wk 26 per physician discretion. This post hoc analysis included pts who received ≥1 dose of UPA 15 mg once daily or ADA 40 mg every other wk while on concomitant GCs at baseline. The proportion of pts with disease worsening (Clinical Disease Activity Index [CDAI] >2 and Disease Activity Score 28-joint count C-reactive protein [DAS28-CRP] >0.6) following GC discontinuation through follow-up is described. Maintenance of clinical response, including remission and low disease activity based on CDAI ≤2.8 and ≤10, respectively, as well as DAS28-CRP <2.6 and ≤3.2, were assessed among pts who discontinued GCs. Adverse events (AEs) were assessed before and after GC discontinuation through follow-up. Data were analyzed descriptively.

Results

Of 1,629 pts randomized, 978 (60%) used GCs at baseline; 128 (13%) discontinued use at/after wk 26 (UPA, n=97; ADA, n=31). Baseline demographics and clinical characteristics were broadly similar between pts who continued or discontinued GCs. Median follow-up time after GC discontinuation was 60 wks for UPA and 84 wks for ADA. At the time of GC discontinuation, a numerically higher proportion of pts treated with UPA vs ADA were in disease control (CDAI ≤2.8: 55% vs 32%; CDAI ≤10: 85% vs 68%; DAS28-CRP <2.6: 71% vs 48%; DAS28-CRP ≤3.2: 87% vs 62%) (Table 1). Few pts receiving UPA experienced disease worsening following GC discontinuation (1% CDAI increase >2; 7% DAS28-CRP increase >0.6) and none on ADA (Table 1). At 6 months follow-up after GC discontinuation, most pts treated with UPA and ADA maintained CDAI ≤2.8 (74% vs 88%) and ≤10 (92% vs 95%) and DAS28-CRP <2.6 (89% vs 85%) and ≤3.2 (91% vs 94%), respectively (Table 1). GCs were reintroduced (albeit usually temporarily) in 14% of pts on UPA and 19% on ADA (Figure 1). AEs were generally similar across treatment groups. Rates of serious infection before and after GC discontinuation were 0.8 (95% CI 0.0–4.2) and 1.5 (0.2–5.4) events per 100 patient-years (E/100 PY) for UPA and 7.7 (1.6–22.4) and 0 E/100 PY for ADA, respectively. Interpretation of results is limited by small pt numbers and different exposure times.

Table 1.

Clinical outcomes of pts who discontinued GCs at/after wk 26

n/N (%)Pts who discontinued GCs N=128UPAn=97ADAn=31CDAI≤10 at discontinuation79/93 (85%)21/31 (68%) Maintained at 6 months post discontinuationa61/66 (92%)18/19 (95%)≤2.8 at withdrawal51/93 (55%)10/31 (32%) Maintained at 6 months post discontinuationa32/43 (74%)7/8 (88%)Increase >2 any visit after withdrawal1/93 (1%)0DAS28-CRP≤3.2 at withdrawal78/90 (87%)18/29 (62%) Maintained at 6 months post discontinuationa58/64 (91%)15/16 (94%)<2.6 at withdrawal64/90 (71%)14/29 (48%) Maintained at 6 months post discontinuationa47/53 (89%)11/13 (85%)Increase >0.6 any visit after withdrawal6/92 (7%)0

aAs a proportion of pts achieving outcome at GC discontinuation and with observed data 6 months post GC discontinuation.

Conclusion

In pts who achieved disease control and discontinued GCs, disease control was maintained in almost all without worsening disease activity over time following GC discontinuation.

Conclusion

In pts who achieved disease control and discontinued GCs, disease control was maintained in almost all without worsening disease activity over time following GC discontinuation.

References

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

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

Acknowledgements

AbbVie funded this study and participated in the study design, research, analysis, data collection, interpretation of data, review, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship. Medical writing assistance was provided by Julia Zolotarjova, MSc, MWC of AbbVie Inc.

Disclosure of Interests

Roy M. Fleischmann Consultant of: AbbVie, Amgen, BMS, Galvani, Gilead, GSK, Janssen, Eli Lilly, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Astra-Zeneca, BMS, Flexion, Galvani, Gilead, GSK, Janssen, Eli Lilly, Novartis, Noven, Pfizer, Samumed, Selecta, Teva, UCB, Viela, and Vorso., Bernard Combe Speakers bureau: AbbVie, BMS, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and Roche-Chugai, Consultant of: AbbVie, BMS, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and Roche-Chugai, Grant/research support from: Pfizer and Roche-Chugai, Andrew Ostor Consultant of: AbbVie, BMS, Eli Lilly, Gilead, Janssen, Novartis, Paradigm, Pfizer, Roche, and UCB., Cesar Francisco Pacheco Tena Consultant of: AbbVie, Astra-Zeneca, Eli Lilly, Gilead, Janssen, Pfizer, Roche, R-Pharm, Sanofi Regeneron, and UCB., Grant/research support from: AbbVie, Astra-Zeneca, Eli Lilly, Gilead, Janssen, Pfizer, Roche, R-Pharm, Sanofi Regeneron, and UCB., Nasser Khan Shareholder of: May own AbbVie stock or stock options, Employee of: AbbVie, Jessica Suboticki Shareholder of: May own AbbVie stock or stock options, Employee of: AbbVie, Anna Shmagel Shareholder of: May own AbbVie stock or stock options, Employee of: AbbVie, Yanna Song Shareholder of: May own AbbVie stock or stock options, Employee of: AbbVie, Ivan Lagunes-Galindo Shareholder of: May own AbbVie stock or stock options, Employee of: AbbVie, Gerd Rüdiger Burmester Speakers bureau: AbbVie, Eli Lilly, Galapagos, Gilead, Janssen, MSD, Pfizer, Roche, Sanofi, and UCB., Consultant of: AbbVie, Eli Lilly, Galapagos, Gilead, Janssen, MSD, Pfizer, Roche, Sanofi, and UCB.

AB0352 IMPACT OF SEROLOGIC STATUS ON CLINICAL RESPONSES TO UPADACITINIB OR ABATACEPT IN PATIENTS WITH RHEUMATOID ARTHRITIS AND PRIOR INADEQUATE RESPONSE TO BIOLOGIC DMARDs: SUB-GROUP ANALYSIS FROM THE PHASE 3 SELECT-CHOICE STUDY

Background

In patients with RA who had a prior inadequate response or intolerance to biologic DMARDs, the oral Janus kinase inhibitor, upadacitinib (UPA), demonstrated superiority in change from baseline in DAS28(CRP) and DAS28(CRP)<2.6 at week 12 and improved responses across additional endpoints compared to abatacept (ABA) in the phase 3 SELECT-CHOICE study. Seropositive patients have been reported to respond better to treatment than seronegative patients.

Objectives

To evaluate clinical responses with UPA versus ABA among RA patients based on serologic status.

Methods

In SELECT-CHOICE (24-week, phase 3, double-blind, controlled trial), RA patients were randomized to oral UPA (15 mg once daily) or intravenous (IV) ABA (at day 1 and weeks 2, 4, 8, 12, 16, and 20; <60 kg, 500 mg; 60-100 kg, 750 mg; >100 kg, 1000 mg).1 UPA patients also received IV placebo and ABA patients also received oral placebo. All patients continued stable background conventional synthetic DMARDs. Starting at week 12, background RA medications were adjusted or added if patients did not experience ≥20% improvement compared to baseline in tender and swollen joint counts at two consecutive visits. For this sub-group analysis, patients were categorized as follows: RF+ and ACPA+, RF+ and/or ACPA+, and RF- and ACPA-. Mean change from baseline in DAS28(CRP), Clinical Disease Activity Index (CDAI), ACR responses, HAQ-DI, patient’s assessment of pain, and Functional Assessment of Chronic Illness Therapy - Fatigue scale (FACIT-F) were evaluated at weeks 12 and 24. Statistical inference was conducted using Chi-square tests or analysis of covariance (ANCOVA) with non-responder imputation or multiple imputation used for missing data and nominal P-values shown.

Results

Of the total population (N=612), the majority of patients were seropositive for RF and/or ACPA at baseline (80.4%) (Table 1). Most patients were female (~80%), ~55 years old, and one-third had previously experienced ≥2 biologic DMARDs. Mean change from baseline in DAS28(CRP) and CDAI were numerically higher with UPA vs ABA at weeks 12 and 24 across all sub-groups (Figure 1). Regardless of serologic status, UPA demonstrated numerically higher responses vs ABA for ACR 20/50/70 and proportions of patients in low disease activity and remission at both timepoints (Table 1). Mean change from baseline in the HAQ-DI and the patient’s assessment of pain was numerically higher with UPA compared to ABA across all sub-groups and timepoints (data not shown). Clinical responses were generally numerically higher at week 24 compared to week 12, and for the seropositive groups compared to the seronegative group, with both UPA and ABA.

Table 1.

Clinical Responses with UPA 15 mg or ABA in RA Patients Across Serologic Status Sub-Groups at Weeks 12 and 24

RF+ and ACPA+ (n=390)RF+ and/or ACPA+ (n=492)RF- and ACPA- (n=120)UPA n=189ABA n=201UPA n=242ABA n=250UPA n=61ABA n=59Proportion of Patients (%) (NRI)† WeekACR201281*7179*71624724847882776759ACR501251*4051**4026*122463*5363*544432ACR7012231624*151172439*2840**282520DAS28(CRP) ≤3.21254***3454***3333**102465**4965**505437DAS28(CRP) <2.61232***1733***1518*52446**3348***333925CDAI ≤10124239433933*1724595560565134CDAI ≤2.81210*310**3202423*1423**141112

*P<0.05; **P<0.01; ***P<0.001 UPA vs. ABA; nominal P-values are presented and not adjusted for multiple comparisons

†NRI was used for missing data

Conclusion

Across serologic statuses, clinical responses with UPA 15 mg vs ABA were numerically higher at weeks 12 and 24 among RA patients with prior inadequate response or intolerance to biologic DMARDs. In addition, clinical responses were numerically higher for seropositive patients compared to seronegative patients across all endpoints assessed, although the seronegative group had a smaller sample size in this post-hoc analysis.

Acknowledgements

AbbVie funded these studies and participated in the study design, research, analysis, data collection, interpretation of data. No honoraria or payments were made for authorship. Medical writing support was provided by Monica R.P. Elmore, PhD of AbbVie.

Disclosure of Interests

Andrea Rubbert-Roth Speakers bureau: AbbVie, BMS, Chugai, Roche, Gilead, Janssen, Lilly, Sanofi, Amgen, Novartis, Consultant of: AbbVie, BMS, Chugai, Roche, Gilead, Janssen, Lilly, Sanofi, Amgen, Novartis, Jeffrey Sparks Consultant of: Bristol-Myers Squibb, Gilead, Inova Diagnostics, Optum, and Pfizer., Arnaud Constantin Speakers bureau: AbbVie, BMS, Galapagos, Janssen, Lilly, Novartis, Pfizer, Sanofi, and UCB, Consultant of: AbbVie, BMS, Galapagos, Janssen, Lilly, Novartis, Pfizer, Sanofi, and UCB, Ricardo Xavier Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Jessica Suboticki Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Roy M. Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, and UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Genentech, Janssen, Novartis, Pfizer Inc, Regeneron, Roche, Sanofi-Aventis and UCB