Biologic Abatement and Capturing Kids' Outcomes and Flare Frequency in Juvenile Spondyloarthritis (BACK-OFF JSpA): study protocol for a randomized pragmatic trial.

2023

100

02/2023

1745-6215

BACKGROUND: The effectiveness of biologic therapies, primarily tumor necrosis factor inhibitors (TNFi), for children with spondyloarthritis (SpA) has made inactive disease a realistic patient outcome. However, biologic therapies are costly, primarily delivered by subcutaneous or intravenous route, and have non-trivial side effects. Many patients and families want to know if biologic medications can be discontinued after inactive disease is achieved. It remains unclear whether medication dose should remain unchanged, tapered (increase the time between doses), or discontinued once when inactive disease is attained.

METHODS: The Biologic Abatement and Capturing Kids' Outcomes and Flare Frequency in Juvenile SpA (BACK-OFF JSpA) trial is a multicenter pragmatic trial that will randomize 198 participants ages 8-21 years old with SpA and sustained inactive disease on standard TNFi dosing to (1) continue standard TNFi dosing, (2) fixed longer dosing intervals of TNFi, or (3) stop TNFi. The trial will compare the hazard rate of protocol-defined flare and participants' emotional health among the 3 groups over 12 months. Innovative aspects of this trial are the involvement of patient and parent stakeholders in the design and conduct of the study as well as an electronic health record-based enhanced recruitment strategy.

DISCUSSION: This is the first randomized pragmatic trial to assess the efficacy of TNFi de-escalation strategies in children with JSpA with sustained inactive disease. This research will improve the evidence base that patients, caregivers, and rheumatologists use to make shared decisions about continued treatment versus de-escalation of TNFi therapy in this population.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04891640. Registered on 18 May 2021.

10.1186/s13063-022-07038-6

Trials

36755328

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes.

2021

2021 Nov 03

1555-905X

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients.</p>

<p><strong>DESIGN, SETTING, PARTICIPANTS, &amp; MEASUREMENTS: </strong>Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of &gt;6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (=350) and noncases (=350).</p>

<p><strong>RESULTS: </strong>Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months.</p>

<p><strong>CONCLUSIONS: </strong>Electronic health record-based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.</p>

10.2215/CJN.07810621

Clin J Am Soc Nephrol

34732529