Clinical Utility and Cost Savings in Predicting Inadequate Response to Anti-TNF Therapies in Rheumatoid Arthritis

Abstract

Introduction: The PrismRA^® test identifies rheumatoid arthritis (RA) patients who are unlikely to respond to anti-tumor necrosis factor (anti-TNF) therapies. This study evaluated the clinical and financial outcomes of incorporating PrismRA into routine clinical care of RA patients.

Methods: A decision-analytic model was created to evaluate clinical and economic outcomes in the 12-month period following first biologic treatment. Two treatment strategies were compared: (1) observed clinical decision-making based on a 175-patient cohort receiving an anti-TNF therapy as their first biologic after failure of conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) and (2) modeled clinical decision-making of the same population using PrismRA results to inform first-line biologic treatment choice. Modeled costs include biologic drug pharmacy, non-biologic pharmacy, and total medical costs. The odds of inadequate response to anti-TNF therapies and various components of patient care were calculated based on PrismRA results.

Results: Identifying predicted inadequate responders to anti-TNF therapies resulted in a modeled 38% increase in ACR50 response to first-line biologic therapies. The fraction of patients who achieved an ACR50 response to any therapy (TNFi and others) within the 12-month period was 33% higher in the PrismRA-stratified population than in the unstratified population (59 vs. 44%, respectively). When therapy prescriptions were modeled according to PrismRA results, cost savings were modeled for all financial variables: overall costs (4% decreased total, 19% decreased on ineffective treatments), total biologic drug pharmacy (4% total, 23% ineffective), non-biologic pharmacy (2% total, 19% ineffective), and medical costs (6% total, 19% ineffective). Female sex was the clinical metric that showed the greatest association with inadequate response to anti-TNF therapies (odds ratio 2.42, 95% confidence interval 1.20, 4.88).

Conclusions: If PrismRA is implemented into routine clinical care as modeled, predicting which RA patients will have an inadequate response to anti-TNF therapies could save > $7 million in overall ineffective healthcare costs per 1000 patients tested and increase targeted DMARD response rates in RA.

Keywords: Anti-TNF therapies; Budget impact; Clinical utility; Precision medicine; Rheumatoid arthritis.

Fig. 1

PrismRA result. Biologic-naïve RA patients are stratified by PrismRA results: < 9.4 means a signal of inadequate response to TNF inhibitors is absent, at or above 9.4 is a moderate signal of inadequate response associated with ≥ 85% likelihood of inadequate response, ≥ 11.5 is a high signal of inadequate response associated with ≥ 90% likelihood of inadequate response, and ≥ 16.6 is a very high signal of inadequate response associated with ≥ 95% likelihood of inadequate response. In the decision-analytic model in this study, patients with ≥ 90% likelihood of inadequate response to anti-TNF therapies (PrismRA result ≥ 11.8) were defined as predicted inadequate responders

Fig. 2

Predicted inadequate responders are less likely to achieve LDA or remission. a Patients were stratified according to their PrismRA scores (none, low, moderate, and high signals of inadequate response to TNF inhibitors). a The fraction of patients in each group that achieved LDA or remission was determined using DAS28-CRP (LDA = 2.4–2.9; remission ≤ 2.4). b Predicted inadequate responders had a lower likelihood of achieving a EULAR good response (improvement > 1.2 in DAS28-CRP and a final DAS28-CRP ≤ 2.4). c DAS28-CRP, tender 28-joint counts, swollen 28-joint counts and CDAI scores at baseline and 6 months of anti-TNF therapy in the unstratified and PrismRA stratified patient populations. Box plots indicate the interquartile range, median, 95% confidence interval, and outliers

Fig. 3

The percentage of inadequate anti-TNF therapy responders in relation to clinical metrics. For each clinical metric, the percentage of patients who inadequately respond to anti-TNF therapies (ACR50 criteria) is indicated at 6 months. The number of patients assessed in each category is reported below the category label. Clinical metrics evaluated include a sex, b BMI, c age, and d active tobacco smoking history. The OR and CI for female sex, obese BMI (≥ 30 kg/m²), age under 50 years old, and tobacco smoke exposure (current and previous) are indicated

Fig. 4

Decision-analytic model comparing two treatment strategies within a 12-month period from the start of the first biologic therapy. A decision-analytic model compared two treatment strategies within a 12-month period from the start of the first biologic therapy. The strategies are a observed clinical decision-making based on a 175-patient biologic-naïve RA patient cohort receiving an anti-TNF therapy as the first biologic after failure of csDMARDs and b a clinical decision-making model of the same population using PrismRA prediction of inadequate response to anti-TNF therapies to stratify the first-line biologic. ACR50 responses were modeled at 6 and 12 months post-therapy initiation. Inadequate response is defined as a failure to achieve an ACR50 response. The percentages of the patients directed through each arm of the modeled strategy are indicated. The second targeted therapy was modeled as 60% to a second anti-TNF therapy and 40% to an alternative MOA (a biologic or targeted therapy other than a TNF inhibitor)

Fig. 5

Decision-analytic model estimated reduction in ineffective treatment costs within a 12-month period. The cost of non-biologic pharmacy (orange), total medical cost (green), and biologic drug pharmacy (blue) is shown for the RA patient populations modeled by the two treatment strategies of the decision-analytic model. Ineffective treatment costs are indicated by the hashed pattern in the same color for each category. Data for a the entire 175-patient cohort and b the Medicare-eligible patient subcohort (≥ 65 years old) are shown