Clinical Utility of Whole-Genome Analysis as One-for-All Test for Breast Cancer: A Case Series

Introduction

Breast cancer exhibits vast genomic diversity, leading to varied clinical manifestations. Integrating molecular subtyping with in-depth genomic profiling is pivotal for informed treatment choices and prognostic insights. Whole-genome clinical analysis provides a holistic view of genome-wide variations, capturing structural changes and affirming tumor suppressor gene loss of heterozygosity.

Case Presentation

Here we detail four unique breast cancer cases from Seoul St. Mary's Hospital, highlighting the actionable benefits and clinical value of whole-genome sequencing (WGS). As an all-in-one test, WGS demonstrates significant clinical utility in these cases, including: (1) detecting homologous recombination deficiency with underlying somatic causal variants (case 1), (2) distinguishing double primary cancer from metastasis (case 2), (3) uncovering microsatellite instability (case 3), and (4) identifying rare germline pathogenic variants in TP53 gene (case 4). Our observations underscore the enhanced clinical relevance of WGS-based testing beyond pinpointing a few driver mutations in conventional targeted panel sequencing platforms.

Conclusion

With genomic advancements and decreasing sequencing costs, WGS stands out as a transformative tool in oncology, paving the way for personalized treatment plans rooted in individual genetic blueprints.

POS0548 EVALUATION OF PHYSICIAN GLOBAL ASSESSMENT IN PATIENTS WITH b/tsDMARD THERAPY SELECTION ALIGNED WITH A MOLECULAR SIGNATURE RESPONSE CLASSIFIER RESULTS: AN ANALYSIS FROM THE STUDY TO ACCELERATE INFORMATION OF MOLECULAR SIGNATURES (AIMS) IN RHEUMATOID ARTHRITIS

Background

Despite drug therapies that improve lives, tens of millions of patients annually are prescribed therapy using a “trial and error” approach because, until recently, it was not possible to personalize treatment using a patient’s unique molecular profile. A blood-based molecular signature response classifier (MSRC) was shown to predict non-response to TNFi therapies in patients. MSRC integrates disease-associated RNA transcripts, and clinical features (anti-CCP, sex, BMI, PGA).[1] A recent study demonstrated that patient response to treatment informed by MSRC was more than 3 times better when MRSC informed therapy selection (predicted non-responders [alt-MOA] =34.8% vs predicted non-responders [TNFi] = 10.3%, p-value = 0.05).[1] Furthermore, when patients without a non-response signal from MSRC were prescribed a TNFi for treatment, their outcomes were improved by 5 times compared to the cohort receiving TNFi therapy despite a signal of non-response from MSRC (no prediction -[TNFi] = 45.8% vs predicted non-responder[TNFi]= 10.3%, p-value = 0.005) [1]

Objectives

The objective of the Study to Accelerate Information of Molecular Signatures (AIMS) in RA is to build a clinical/molecular database of longitudinal data from RA patients managed a real-world, settings with a focus on utilization of the MSRC test (PrismRA Scipher Medicine). Physician Global Assessment scores were measured and assessed as the objective of this analysis.

Methods

This analysis reports on data from patients enrolled in AIMS who initiated a new b/tsDMARD, or continued existing therapy, following MSRC testing (n = 560). Patients were ≥18 years of age with a clinical diagnosis of RA. The cohort was divided into patients whose targeted therapy selection was Aligned (predicted non-responder (PNR)- [altMOA], no prediction of non-response (NP)- [TNFi] or [altMOA] and Not Aligned (PNR- [TNFi]) with the MSRC test results. Improvement from baseline of MDGA was evaluated at 3 & 6 ms and swollen joints at 3ms.

Results

Predicted non-responders prescribed an alt-MOA had significant improvement in MDGA scores at 3 & 6 ms compared to predicted non-responders prescribed a TNFi (3m: PNR-[altMOA]- 18.4% (n=163) vs PRN-[TNFi] 7.2% (n=140), p-value – 0.010, 6m: PNR-[altMOA]- 13.1% (n=80) vs PRN-[TNFi] -1.11% (n=90), p-value – 0.013). Patients without the molecular signature prescribed a TNFi showed a trend of more improvement in MDGA scores at 3 & 6ms compared to patients with the molecular signature prescribed a TNFi (3m: NP-[TNFi]- 11.5% (n=134) vs PRN-[TNFi] 7.2% (n=140), p-value – 0.791, 6m: NP-[TNFi]- 13.3% (n=76) vs PRN-[TNFi] -1.11% (n=90), p-value – 0.075) (Figure 1). Moreover, predicted non-responders prescribed an alt-MOA showed a trend of improvement in swollen joints at 3ms compared to predicted non-responders prescribed a TNFi (PNR-[altMOA]- 3.15% (n=163) vs PRN-[TNFi] 1.7% (n=140), p-value – 0.08). Patients without the molecular signature prescribed a TNFi showed significantly more improvement in swollen joints at 3ms (NP-[TNFi]- 3.71% (n=134) vs PRN-[TNFi] 1.7% (n=140), p-value – <0.001). Characteristics of the cohort are reported in the Table 1.

Table 1.CharacteristicPNR-TNFin=159PNR-altMOAn=176NP-TNFin=145NP-altMOAn=80P-value (PNR-TNFi vs NP-TNFi)P-value (PNR-TNFi vs PNR-altMOA)Age,mean (SD)53.5 (13.8)57.6 (12.9)55.9 (14.4)59.7 (13.2)0.1350.005Race, n (%)0.3460.896White128 (81)142 (81)124 (86)64 (80)Black11 (7)11 (6)9 (6)5 (6)Other20(13)23(13)12(8)11 (14)CDAI at baseline (SD)34.1 (15.8)38.5 (16.3)28.5 (15)26.5 (15.6)0.0020.012TNFi Navie at baseline, n (%)128 (81)148 (84)120 (83)71 (89)0.6720.473Figure 1.

Conclusion

The incorporation of MSCR testing into the b/tsDMARD selection process can improve patient outcomes and can help identify which patient may be more or less responsive TNFi therapies.

References

[1]Strand, V., et al.Expert Rev Mol Diagn, 2021

Disclosure of Interests

Erin Connolly-Strong Shareholder of: Scipher, Lixia Zhang Shareholder of: Scipher, Sam Asgarian Shareholder of: Scipher.

Improvement in clinical disease activity index when treatment selection is informed by the tumor necrosis factor-ɑ inhibitor molecular signature response classifier: analysis from the study to accelerate information of molecular signatures in rheumatoid arthritis

BACKGROUND

A blood-based molecular signature response classifier (MSRC) predicts non-response to tumor necrosis factor-ɑ inhibitors (TNFi) in rheumatoid arthritis (RA).

RESEARCH DESIGN AND METHODS

This is an interim analysis of data collected in the Study to Accelerate Information of Molecular Signatures (AIMS) in RA from patients who received the MSRC test between September 2020 and November 2021. Absolute changes in clinical disease activity index (CDAI) scores from baseline were evaluated at 12 weeks (n = 470) and 24 weeks (n = 274).

RESULTS

Predicted TNFi non-responders who received a biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) with an alternative mechanism of action (altMOA) experienced up to 1.8-fold greater improvements in CDAI scores than those treated with a TNFi (12 weeks: 12.2 vs 8.0; p-value = 0.083; 24 weeks: 14.2 vs 7.8 p-value = 0.009). In patients with a molecular signature of non-response to TNFi in high disease activity at baseline, this corresponded to 43.2% relative improvement in achieving a lower CDAI disease activity level when likely TNFi non-responders were treated with a non-TNFi therapy (38.9% vs 55.7%). Commensurate improvements in efficiency of spend are expected when TNFi are avoided in favor of altMOA.

CONCLUSIONS

RA treatment selection informed by MSRC test results improves clinical outcomes in real-world care and offers improvements in efficiency of healthcare spending.

Clinical utility of therapy selection informed by predicted nonresponse to tumor necrosis factor-ɑ inhibitors: an analysis from the Study to Accelerate Information of Molecular Signatures (AIMS) in rheumatoid arthritis

BACKGROUND

The molecular signature response classifier (MSRC) is a blood-based precision medicine test that predicts nonresponders to tumor necrosis factor-ɑ inhibitors (TNFi) in rheumatoid arthritis (RA) so that patients with a molecular signature of non-response to TNFi can be directed to a treatment with an alternative mechanism of action.

RESEARCH DESIGN AND METHODS

This study evaluated decision choice and treatment outcomes resulting from MSRC-informed treatment selection within a real-world cohort.

RESULTS

Therapy selection by providers was informed by MSRC results for 73.5% (277/377) of patients. When MSRC results were not incorporated into decision-making, 62.0% (62/100) of providers reported deviating from test recommendations due to insurance-related restrictions. The 24-week ACR50 responses in patients prescribed a therapy in alignment with MSRC results were 39.6%. Patients with a molecular signature of non-response had significantly improved responses to non-TNFi therapies compared with TNFi therapies (ACR50 34.8% vs 10.3%, p-value = 0.05). This indicates that predicted non-responders to TNFi therapies are not nonresponders to other classes of RA targeted therapy. Significant changes were also observed for CDAI, ACR20, ACR70, and for responses at 12 weeks.

CONCLUSIONS

Adoption of the MSRC into patient care could fundamentally shift treatment paradigms in RA, resulting in substantial improvements in real-world treatment outcomes.

Guided therapy selection in rheumatoid arthritis using a molecular signature response classifier: an assessment of budget impact and clinical utility

BACKGROUND: Patients with moderate to severe rheumatoid arthritis (RA) can be treated with a range of targeted therapies following inadequate response to conventional synthetic disease-modifying antirheumatic drugs such as methotrexate. Whereas clinical practice guidelines provide no formal recommendations for initial targeted therapies, the tumor necrosis factor alpha inhibitor (TNFi) class is the prevalent first-line selection based on clinician experience, its safety profile, and/or formulary requirements, while also being the costliest. Most patients do not achieve adequate clinical response with a first-line TNFi, however. A molecular signature response classifier (MSRC) test that assesses RA-related biomarkers can identify patients who are unlikely to achieve adequate response to TNFi-class therapies. OBJECTIVE: To model cost-effectiveness of MSRC-guided, first-line targeted therapy selection compared with current standard care. METHODS: This budget impact analysis used data sourced from August to September 2020. The prevalence of each first-line targeted therapy was obtained using market intelligence from Datamonitor/Informa PLC Rheumatology Dashboard Forecast 2020, and the average first-year cost of treatment for each class was calculated using wholesale acquisition costs from IBM Micromedex RED BOOK Online. Average effectiveness for each class was based on manufacturer-reported ACR50 response rates (American College of Rheumatology adequate response criteria of 50% improvement at 6 months after therapy initiation). The impact of MSRC testing on first therapy selection was predicted based on a third party-generated decision-impact study that analyzed potential alterations in rheumatologist prescribing patterns after receiving MSRC test reports. Sensitivity analysis evaluated potential impacts of variation in first-year medication cost, adherence to MSRC report, and test price on the first-year cost of treatment. Cost for response (first-year therapy cost therapy divided by probability of achieving ACR50) was compared between standard care and MSRC-guided care. RESULTS: The estimated cost for first-year, standard-care treatment was $65,117, with 80% of patients initiating treatment with a TNFi. Cost for achieving ACR50 response was $177,046. After applying MSRC-guided patient stratification and therapy selection, the first-year cost was $56,543, net of test price, with 49.0% of patients initiating with a TNFi. First-year MSRC-guided care cost, including test price, was estimated at $117,103, a 33.9% improvement over standard care. Sensitivity analysis showed a net cost improvement for guided care vs standard care across all scenarios. Patients predicted to be inadequate TNFi responders, when modeled with lower-priced alternatives, were predicted to show increased ACR50 response rates. Those with MSRC test results indicating a first-line TNFi were predicted to show an ACR50 response rate superior to that for any other class. In this model, if implemented clinically, MSRC-guided care might save the US health care system more than $850 million annually and improve ACR50 by up to 31.3%. CONCLUSIONS: Precision medicine using MSRC-guided patient stratification and therapy selection may both decrease cost and improve efficacy of targeted RA therapies. DISCLOSURES: This work was funded in full by Scipher Medicine Corporation, which participated in data analysis and interpretation and drafting, reviewing, and approving the publication. All authors contributed to data analysis and interpretation and publication preparation, maintaining control over the final content. Arnell, Withers, and Connolly-Strong are employees of and have stock ownership in Scipher Medicine Corporation. Bergman has received consulting fees from AbbVie, Gilead, GlaxoSmithKline, Novartis, Pfizer, Regeneron, Sanofi, and Scipher Medicine and owns stock or stock options in Johnson & Johnson. Kenney, Logan, and Lim-Harashima are consultants for Scipher Medicine Corporation. Basu has nothing to disclose.

AB0138 A MOLECULAR SIGNATURE RESPONSE CLASSIFIER STRATIFIES SEROPOSITIVE RHEUMATOID ARTHRITIS PATIENTS BASED ON THEIR LIKELIHOOD OF INADEQUATE RESPONSE TO TNF INHIBITOR THERAPIES

Background:

There is an urgent need for precision medicine in targeted therapy selection for the treatment of rheumatoid arthritis (RA). TNF inhibitor (TNFi) therapies are the most prescribed targeted therapy for RA patients, yet the majority of patients fail to achieve a clinically meaningful response using this medication class. A blood-based molecular signature test evaluates RNA and clinical metrics to stratify RA patients based on their likelihood of having an inadequate response to TNFi therapies.1 Patients unlikely to respond to TNFi therapies can be directed to a different treatment option such as a JAK inhibitor, thus reducing the time needed to identify an effective therapy, improving confidence in and adherence to treatment, and increasing the patients’ chance of reaching treat-to-target goals.

Objectives:

High-titers of anti-cyclic citrillunated protein (anti-CCP) have been independently associated with reduced response to TNFi therapy;2 thus, we evaluated the ability of a blood-based molecular signature response classifier (MSRC) test to stratify RA patients by their likelihood of inadequate response to TNFi therapies – regardless of their positive or negative anti-CCP status.

Methods:

A subset of patients enrolled in the Network-04 prospective observational trial evaluating the ability of a molecular signature response classifier to stratify patients were subdivided into two groups based upon whether they were positive (N = 72) or negative (N = 74) for anti-CCP. The odds of inadequate response to TNFi therapies were calculated based on whether or not a patient had a molecular signature of non-response to TNFi therapy at baseline before the start of treatment. Odds ratios and confidence intervals were calculated3,4 to represent the strength of association between detecting the molecular signature of non-response and the patient’s failure to achieve ACR50 at 6 months.

Results:

The odds that a patient with a molecular signature of non-response failed to meet ACR50 criteria at 6 months was approximately three times greater than among those patients who lacked the signal (Table 1). No significant difference in odds ratios was observed between patients who were positive or negative for anti-CCP.

Table 1.

The odds of patients with a molecular signature of non-response failing to achieve an ACR50 response 6 months after TNF inhibitor therapy initiation

Odds ratio (95% confidence interval)Anti-CCP positive3.5 (1.3-9.7)Anti-CCP negative3.1 (1.2-8.3)

Conclusion:

The MSRC test evaluates RA disease biology and accurately stratifies patients based on their likelihood of having an inadequate response to TNFi therapies, regardless of being negative or positive for anti-CCP autoantibodies. Rheumatologists can use the results of the MSRC test to inform targeted therapy selection for RA patients, instead of their anti-CCP serostatus, eliminating the variability inherent to the anti-CCP measurement and its inability to consistently predict TNFi therapy incompatibility. With the MSRC test, providers can rely on a more predictable and accurate assessment of TNFi therapy success or failure when coordinating patient management.

References:

[1]Mellors, T. et al. Clinical Validation of a Blood-Based Predictive Test for Stratification of Response to Tumor Necrosis Factor Inhibitor Therapies in Rheumatoid Arthritis Patients. Network and Systems Medicine3, 91-104, doi:10.1089/nsm.2020.0007 (2020).

[2]Braun-Moscovici, Y. et al. Anti-cyclic citrullinated protein antibodies as a predictor of response to anti-tumor necrosis factor-alpha therapy in patients with rheumatoid arthritis. J Rheumatol33, 497-500 (2006).

[3]Szumilas, M. Explaining odds ratios. J Can Acad Child Adolesc Psychiatry19, 227-229 (2010).

[4]Sperandei, S. Understanding logistic regression analysis. Biochem Med (Zagreb) 24, 12-18, doi:10.11613/BM.2014.003 (2014).

Disclosure of Interests:

Stanley Cohen: None declared, Vibeke Strand Consultant of: Abbvie, Amgen, Arena, BMS, Boehringer Ingelheim, Celltrion, Galapagos, Genentech/Roche, Gilead, GSK, Ichnos, Inmedix, Janssen,Kiniksa, Lilly,Merck, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Setpoint, UCB, Erin Connolly-Strong Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Johanna Withers Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Lixia Zhang Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Ted Mellors Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Viatcheslav Akmaev Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation

POS0492 A MOLECULAR SIGNATURE RESPONSE CLASSIFIER PREDICTS THE LIKELIHOOD OF EULAR NON-RESPONSE TO TNF INHIBITOR THERAPIES IN RA: RESULTS FROM A RETROSPECTIVE COHORT ANALYSIS

Background:

Following RA treatment recommendations, most people with rheumatoid arthritis (RA) begin targeted therapy with TNF inhibitors (TNFi), even though inadequate response to TNFi therapies is widespread. Treatment changes from one medication to the next are currently fueled by disease-activity measures and eventually result in disease control for most patients; however, this “trial-and-error” approach wastes precious time on ineffective treatments. A delay in reaching treat-to-target goals has a negative effect on patient burden and, possibly, disease progression.1 Useful predictors for TNFi response have been challenging to identify but a specific molecular signature response classifier (MSRC) test was shown to be predictive for inadequate response to TNFi therapies.2 The impact of such identification has the potential to result in improved patient outcomes, but further validation would be welcome, especially for response criteria other than ACR50, and in a stringent treat-to-target setting with lower baseline disease activity.

Objectives:

To validate the predictive value of the MSRC test in identifying those patients who do not meet EULAR good response criteria after 6 months of TNFi treatment.

Methods:

Data from a prospective cohort study conducted in the Sint Maartenskliniek (Nijmegen, the Netherlands) of RA patients who started adalimumab or etanercept TNFi as their first biologic were included.3 Baseline RNA samples and clinical assessments were used to identify patients who had a molecular signature1 of non-response to TNFi therapy. Outcomes were calculated at six months using DAS28-CRP-based EULAR good response, and high and low confidence responders and non-responders were identified using Monte Carlo simulation with 2,000 repeats and 70% precision cut off. Outcome measurements were blinded for test results. Treatment switch before 6 months was imputed as non-response. Odds ratios and area under the ROC curve (AUC) assessments were used to evaluate the ability of the MSRC test to predict inadequate response at 6 months against EULAR good response criteria.

Results:

A total of 68 out of 88 RA patients were identified to have a high-confidence response status and were included in analyses (Table 1). EULAR good response was observed in 45.5% (31/68) of patients. Patients were stratified according to detection of a molecular signature of non-response with an AUC of 0.61. The odds that a patient with the molecular signature of non-response at baseline failed to achieve a EULAR good response at 6 months was four times greater than that of a patient lacking the molecular signature (odds ratio 4.0, 95% confidence interval 1.2-13.3).

Table 1.

Patient demographics

CharacteristicRA patients (N = 68)Age, median (SD)57 (11)Female, n (%)43 (63.2)CCP positive, n (%)34 (50.0)RF positive, n (%)38 (55.9)Prescribed adalimumab at baseline, n (%)11 (16.2)Prescribed etanercept at baseline, n (%)57 (83.8)

Conclusion:

In this validation study, the molecular signature of non-response identified patients who did not fulfill the EULAR good response criteria to TNFi therapies. The patient selection process for this study had limitations; additional analysis in an alternative cohort would further verify the performance of the MSRC test. Nevertheless, the test, previously validated for ACR50, now has been validated using EULAR good response in a treat-to-target setting.

References:

[1]Schipper LG et al, Time to achieve remission determines time to be in remission. Arthritis Res Ther 201

[2]Mellors T, et al. Clinical Validation of a Blood-Based Predictive Test for Stratification of Response to Tumor Necrosis Factor Inhibitor Therapies in Rheumatoid Arthritis Patients. Network and Systems Medicine 2020

[3]Tweehuysen L et al. Predictive value of ex-vivo drug-inhibited cytokine production for clinical response to biologic DMARD therapy in rheumatoid arthritis. Clin Exp Rheumatol 2019

Disclosure of Interests:

Lixia Zhang Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Celeste van der Tog: None declared, Alfons den Broeder Consultant of: Abbvie, Amgen, Cellgene, Roche, Biogen, Lilly, Novartis, Celltrion Sanofi, Gilead., Grant/research support from: Abbvie, Amgen, Cellgene, Roche, Biogen, Lilly, Novartis, Celltrion Sanofi, Gilead., Ted Mellors Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Erin Connolly-Strong Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Johanna Withers Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Alex Jones Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Viatcheslav Akmaev Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation

The ALPHA Project: Establishing consensus and prioritisation of global community recommendations to address major challenges in lupus diagnosis, care, treatment and research

The Addressing Lupus Pillars for Health Advancement (ALPHA) Project is a global consensus effort to identify, prioritise and address top barriers in lupus impacting diagnosis, care, treatment and research. To conduct this process, the ALPHA Project convened a multistakeholder Global Advisory Committee (GAC) of lupus experts and collected input from global audiences, including patients. In phase I, the ALPHA Project used expert interviews and a global survey of lupus experts to identify and categorise barriers into three overarching pillars: drug development, clinical care and access to care. In phase II, reported here, the GAC developed recommended actionable solutions to address these previously identified barriers through an in-person stakeholder meeting, followed by a two-round scoring process. Recommendations were assessed for feasibility, impact and timeline for implementation (FIT), where potential FIT component values were between 1 and 3 and total scores were between 3 and 9. Higher scores represented higher achievability based on the composite of the three criteria. Simplifying and standardising outcomes measures, including steroid sparing as an outcome (drug development) and defining the lupus spectrum (clinical care) ranked as the highest two priority solutions during the GAC meeting and received high FIT scores (7.67 and 7.44, respectively). Leveraging social media (access to care) received the highest FIT score across all pillars (7.86). Cross-cutting themes of many solutions include leveraging digital technology and applying specific considerations for special populations, including paediatrics. Implementing the recommendations to address key barriers to drug development, clinical care and access to care is essential to improving the quality of life of adults and children with lupus. Multistakeholder collaboration and guidance across existing efforts globally is warranted.

Patient-reported flare frequency is associated with diminished quality of life and family role functioning in systemic lupus erythematosus

PURPOSE

To understand the influence of the systemic lupus erythematosus (SLE)-related flares on patient's health-related quality of life (HRQoL).

METHODS

An online survey included individuals with self-reported physician's diagnosis of SLE or lupus nephritis (LN). Lupus impact tracker (LIT) assessed lupus symptoms and HRQoL, SLE-Family questionnaire measured family role functioning, and Healthy Days Core Module (HDCM) measured overall mental and physical health. Chi-square and analysis of variance evaluated differences by flare frequency. Multivariable linear regression and generalized linear models evaluated the independent relationships of flare frequency to HRQoL.

RESULTS

1066 respondents with SLE or LN completed the survey. Mean (SD) duration of illness was 12.4 (10.1) years. 93.4% (n = 996) were women, 82.3% (n = 830) were White, and 49.7% (n = 530) were employed or students. More frequent flares were associated with significantly worse scores on all HRQoL measures: LIT (adjusted means: 0 flares, 31.8; 1-3 flares, 47.0; 4-6 flares, 56.1; ≥ 7 flares, 63.6; P < 0.001); SLE-Family (adjusted means: 0 flares, 3.1; 1-3 flares 3.8; 4-6 flares, 4.3; ≥ 7 flares, 4.6, P < 0.001); HDCM unhealthy days (0 flares, 8.7; 1-3 flares, 17.4; 4-6 flares, 21.5; ≥ 7 flares, 26.2 days, P < 0.001).

CONCLUSION

Lupus flares contributed to impaired functional and psychological well-being, family functioning, and number of monthly healthy days. Better understanding of the burden of flare activity from the patient's perspective will support a holistic approach to lupus management.

Treatment Patterns and Health Care Costs of Lupus Nephritis in a United States Payer Population

Objective

To describe the characteristics, treatment patterns, health care resource utilization (HCRU), and cost of care for members of a large United States (US) health insurance plan with lupus nephritis (LN).

Methods

A retrospective observational study was conducted using a health insurance plan database to identify adult members with a diagnosis of LN. Medical and pharmacy claims were used to describe demographics, comorbidities, HCRU, and cost patterns over a 12-month follow-up period for each patient, between January 1, 2014, and December 31, 2016. All study variables were examined descriptively.

Results

A total of 1039 patients were available for analysis (median age, 47 years; 83% female). The median Charlson Comorbidity Index (CCI) was 3.3. Less than half (41%) of patients received immunosuppressive therapies commonly used to treat LN. Evidence indicated that 58% of the study population were prescribed corticosteroid therapy, in most cases (73%) for more than 60 days. Adverse events known to be associated with corticosteroid therapy were recorded in 58% of patients. Guideline-recommended preventive therapy with hydroxychloroquine was prescribed for 54% of members with LN. Nearly half (47%) of members with LN did not see a nephrologist and more than one-third (36%) did not see a rheumatologist over 1 year of follow-up. Rates of all-cause hospitalization and emergency department (ED) use were 25% and 35%, respectively. The mean all-cause per-member-per-month (PMPM) medical cost for the study population was $2801, with LN-specific costs accounting for $1147 PMPM.

Conclusion

Patients with LN who are insured through a large US health plan appeared to underutilize outpatient specialist services and guideline-recommended hydroxychloroquine therapy. Corticosteroid use and adverse events known to be associated with corticosteroids were common in this cohort.

Repository Corticotropin Injection for Active Rheumatoid Arthritis Despite Aggressive Treatment: A Randomized Controlled Withdrawal Trial

INTRODUCTION

The objective of this study was to assess efficacy and safety of repository corticotropin injection (RCI) in subjects with active rheumatoid arthritis (RA) despite treatment with a corticosteroid and one or two disease-modifying antirheumatic drugs (DMARDs).

METHODS

All subjects received open-label RCI (80 U) twice weekly for 12 weeks (part 1); only those with low disease activity [LDA; i.e., Disease Activity Score 28 joint count and erythrocyte sedimentation rate (DAS28-ESR) < 3.2] were randomly assigned to receive either RCI (80 U) or placebo twice weekly during the 12-week double-blind period (part 2). The primary efficacy endpoint was the proportion of subjects who achieved LDA at week 12. Secondary efficacy endpoints included proportions of subjects who maintained LDA during weeks 12 through 24 and achieved Clinical Disease Activity Index (CDAI) ≤ 10 at weeks 12 and 24. Safety was assessed via adverse event reports.

RESULTS

Of the 259 enrolled subjects, 235 completed part 1; 154 subjects (n = 77 each for RCI and placebo) entered part 2, and 127 (RCI, n = 71; placebo, n = 56) completed. At week 12, 163 subjects (62.9%) achieved LDA and 169 (65.3%) achieved CDAI ≤ 10 (both p < 0.0001). At week 24, 47 (61.0%) RCI-treated and 32 (42.1%) placebo-treated subjects maintained LDA (p = 0.019); 66 (85.7%) RCI-treated and 50 (65.8%) placebo-treated subjects maintained CDAI ≤ 10 (p = 0.004). No unexpected safety signals were observed.

CONCLUSIONS

RCI was effective and generally safe in patients with active RA despite corticosteroid/DMARD therapy. By week 12, > 60% of patients achieved LDA, which was maintained with 12 additional weeks of treatment. Most patients who achieved LDA maintained it for 3 months after RCI discontinuation.

TRIAL REGISTRATION

Clinicaltrials.gov identifier NCT02919761.

Acthar Gel (repository corticotropin injection) for persistently active SLE: study design and baseline characteristics from a multicentre, randomised, double-blind, placebo-controlled trial

Objective

SLE is a chronic inflammatory autoimmune disease characterised by the excessive production of autoantibodies, immune complexes and proinflammatory cytokines. Repository corticotropin injection (RCI) is a naturally sourced complex mixture of adrenocorticotropic hormone analogues and other pituitary peptides. RCI is approved by the US Food and Drug Administration for use during an exacerbation or as maintenance therapy in select cases of SLE. This paper discusses the design and baseline characteristics of a multicentre, double-blind, randomised, placebo-controlled, 24-week clinical trial evaluating the effect of RCI in reducing disease activity for patients with persistently active SLE despite moderate-dose corticosteroid use.

Methods

Efficacy will be evaluated using the SLE Responder Index-4 (SRI-4), SLE Disease Activity Index-2000 (SLEDAI-2K), British Isles Lupus Assessment Group-2004 (BILAG-2004) and Physician's Global Assessment (PGA). The primary efficacy endpoint will be the proportion of SRI-4 responders at week 16. Secondary and exploratory endpoints will include changes in disease activity scores over time, prednisone dose and biomarkers of inflammation and bone turnover. The safety and tolerability profile of RCI will also be evaluated through adverse event profiles, physical examination, clinical laboratory tests and serum cortisol levels.

Results

Target enrolment for this global study is 270 patients, and as of 15 November 2019, the modified intent-to-treat population included 169 patients. The study cohort had 91.7% women, had a mean age of 39.7 years, mean SLEDAI-2K total score of 9.9, mean BILAG-2004 total score of 18.1, mean PGA of 59.7 and mean prednisone or equivalent daily dose of 11.1 mg. A total of 79.3% and 64.5% of patients were receiving concomitant antimalarial or immunosuppressive therapy, respectively.

Conclusions

Data from this study will provide valuable insights into the therapeutic role of RCI in refractory SLE, as well as important information regarding its safety profile.

Patient-Reported Lupus Flare Symptoms Are Associated with Worsened Patient Outcomes and Increased Economic Burden

BACKGROUND

Lupus flares significantly contribute to health resource utilization and hospitalizations. Identification of flare activity may be hindered since validated assessment scales are rarely used in clinical practice and flare severity may fall below clinician-assessed thresholds. Therefore, patient-reported outcomes of lupus flare frequency are important assessment tools for lupus management.

OBJECTIVE

To better understand the relationship between lupus flares as reported by persons with lupus and specific direct and indirect costs, including hospital admission, unplanned urgent care (UC)/emergency department (ED) visits, work productivity loss, and nonwork activity impairment.

METHODS

In this cross-sectional analysis, persons with lupus were drawn from 2 enriched sampling sources. Data were collected via an online survey and included individuals with self-reported physician's diagnosis of systemic lupus erythematosus, skin or discoid lupus, or lupus nephritis. Respondents were asked the total number of hospitalizations and ED/UC visits for any reason and for lupus-related hospitalizations and ED/UC visits. Work productivity loss and nonwork activity impairment were measured via the Work Productivity and Activity Impairment - General Health scale. The sample was stratified into those with 0 flares, 1-3 flares, 4-6 flares, and 7 or more flares, with 0 flares used as the reference. Chi-square tests for trend and analyses of variance were used to evaluate differences among flare frequency groups. Multivariable regression modeling was conducted to evaluate the independent relationship of flare frequency to health care use and productivity loss.

RESULTS

We studied 1,288 survey respondents with known flare frequency in the past 12 months. Flare frequency increased with duration of illness. The mean number of lupus-related hospital admissions was significantly associated with increasing flare frequency for the total sample (F = 3.9; P < 0.009). Compared to patients with no flare, those who reported flare activities had 1.72-3.13 times higher rates of hospitalizations. The mean number of lupus-related ED/UC visits were also found to be significantly associated with increasing flare frequency for the total sample (F = 23.4; P < 0.001), and rates were increased by 6.98- to 16.12-fold for unplanned ED/UC visits depending on flare frequency. Rates of employment were significantly related to increasing flare frequency. With respect to work-related impairment, absenteeism increased with greater lupus flare frequency (F = 6.2; P < 0.001), as did presenteeism (F = 31.5; P < 0.001) and the combined value of total work productivity loss (F = 30.4; P < 0.001). Mean work-related activity impairment was 12%-32% more among patients who reported flare activities compared to those who reported no flares.

CONCLUSIONS

Increased lupus-related flare frequency is associated with worsened patient outcomes as measured by increased hospitalizations, visits to the ED/UC, work productivity loss, and activity impairment. This association may be an important indicator of disease severity and resource burden and therefore suggests an unmet need among patients experiencing lupus-related flares.

DISCLOSURES

This study was sponsored by Mallinckrodt Pharmaceuticals via grants to Vedanta Research and The Lupus Foundation of America. Katz received consulting fees from Vedanta Research, which received grant support from Mallinckrodt Pharmaceuticals to support data collection and analysis. Nelson and Connolly-Strong are employees of Mallinckrodt Pharmaceuticals and are stockholders in the company. Reed is an employee of Vedanta Research. Daly and Topf are employees of the Lupus Foundation of America, which received grant funding to support data collection. This study was a podium presentation at The American College of Rheumatology (ACR) Annual Meeting 2018; October 19-24, 2018; Chicago, IL.