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.

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.

Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.

Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.

Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

[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)