Personalized rheumatic medicine through dose reduction reduces the cost of biological treatment – a retrospective intervention analysis

Two-year results of tapered dupilumab for CRSwNP demonstrates enduring efficacy established in the first 6 months

BACKGROUND

Dupilumab is an anti-T2-inflammatory biological registered for chronic rhinosinusitis (CRS) with nasal polyps (CRSwNP), indicated by integrated CRS-care pathways when optimal medico-surgical treatment yields insufficient CRS control. This study aims to evaluate long-term results with focus on established therapeutic efficacy while tapering dupilumab.

METHODS

Real-life, prospective observational cohort study in single tertiary referral center with add-on dupilumab as primary biological treatment in adult (≥18 years) biological-naïve CRSwNP patients per the European Position Paper on Rhinosinusitis and Nasal Polyps (EPOS)2020-indication with a 2-year follow-up. Tapering (increasing interdose interval) applied every 24 weeks, conditional to sufficient treatment response and CRS control.

RESULTS

Mean scores (s.d.) of all co-primary outcomes improved significantly from baseline ( 228) to the 48 ( 214) and 96-weeks ( 99) timepoints: Nasal Polyp Score (0-8) improved from 5,3 (1,9) to 1,4 (1,8) and 1,3 (1,7); SinoNasal Outcome Test (SNOT)-22 (0-110) improved from 53,6 (19,6) to 20,2 (15,4) and 21,2 (15,6); Sniffin'Sticks-12 identification test (0-12; 0-6 anosmia, 7-10 hyposmia, 11-12 normosmia) improved from 3,7 (2,4) to 7,7 (2,9) and 7,3 (3,04); Asthma Control Test (5-25; >19 indicating well-controlled asthma) improved from 18,5 (4,8) to 21,8 (3,8) and 21,4 (3,9). Tapering was feasible in 79,5% of the patients at the 24-weeks timepoint, and in 93,7% and 95,8% at the 48- and 96-weeks timepoints, respectively. One-way repeated-measures ANOVA demonstrated no significant alterations of individual co-primary outcome mean-scores from 24 weeks onward.

CONCLUSION

This first long-term real-life prospective observational cohort study shows high therapeutic efficacy of dupilumab for severe CRswNP in the first 2 years. Therapeutic efficacy is principally established within 24 weeks and endures while tapering dupilumab conditional to treatment response and CRS control.

Interval prolongation of etanercept in rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis: a randomized controlled trial

OBJECTIVE

The majority of patients with a rheumatic disease treated with etanercept may be overexposed. Data regarding etanercept tapering are scarce, particularly in psoriatic arthritis (PsA) and ankylosing spondylitis (AS). We compared extending the dose interval to continuation of the standard dose and studied the success rate of etanercept discontinuation. Etanercept concentrations were measured throughout the study.

METHOD

160 patients with rheumatoid arthritis (RA), PsA, or AS with sustained minimal disease activity (MDA) were enrolled in this 18-month, open-label, randomized controlled trial. The intervention group doubled the dosing interval at baseline and discontinued etanercept 6 months later. The control group continued the standard dose for 6 months and doubled the dosing-interval thereafter. The primary outcome was the proportion of patients maintaining MDA at 6 month follow-up.

RESULTS

At 6 months, MDA status was maintained in 47 patients (63%) in the intervention group and 56 (74%) in the control group (p = 0.15), with comparable results in all rheumatic diseases. And median etanercept concentrations decreased from 1.50 µg/mL (interquartile range 1.06- 2.65) to 0.46 µg/mL (0.28-0.92). In total, 40% discontinued etanercept successfully with maintained MDA for at least 6 months.

CONCLUSION

Etanercept tapering can be done without losing efficacy in RA, PsA, and AS patients in sustained MDA. A substantial proportion of patients could stop etanercept for at least 6 months. In many patients, low drug concentrations proved sufficient to control disease activity. However, the risk of minor and major flares is substantial, even in patients continuing standard dosing.

Protein array-based companion diagnostics in precision medicine

INTRODUCTION

The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities.

AREA COVERED

This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests.

EXPERT OPINION

Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.

Viewpoint on Time Series and Interrupted Time Series Optimum Modeling for Predicting Arthritic Disease Outcomes

PURPOSE OF REVIEW

The propose of this viewpoint is to improve or facilitate the clinical decision-making in the management/treatment strategies of arthritis patients through knowing, understanding, and having access to an interactive process allowing assessment of the patient disease outcome in the future.

RECENT FINDINGS

In recent years, the time series (TS) concept has become the center of attention as a predictive model for making forecast of unseen data values. TS and one of its technologies, the interrupted TS (ITS) analysis (TS with one or more interventions), predict the next period(s) value(s) of a given patient based on their past and current information. Traditional TS/ITS methods involve segmented regression-based technologies (linear and nonlinear), while stochastic (linear modeling) and artificial intelligence approaches, including machine learning (complex nonlinear relationships between variables), are also used; however, each have limitations. We will briefly describe TS/ITS, provide examples of their application in arthritic diseases; describe their methods, challenges, and limitations; and propose a combined (stochastic and artificial intelligence) procedure in post-intervention that will optimize ITS modeling. This combined method will increase the accuracy of ITS modeling by profiting from the advantages of both stochastic and nonlinear models to capture all ITS deterministic and stochastic components. In addition, this combined method will allow ITS outcomes to be predicted as continuous variables without having to consider the time lag produced between the pre- and post-intervention periods, thus minimizing the prediction error not only for the given data but also for all possible future patterns in ITS. The use of reliable prediction methodologies for arthritis patients will permit treatment of not only the disease, but also the patient with the disease, ensuring the best outcome prediction for the patient.