Mycobacteroides abscessus (MABS) is within the non-tuberculous mycobacteria family. It inhabits soil and water, exhibits multi-antibiotic resistance and causes opportunistic lung infections, which may progress to symptomatic MABS-pulmonary disease (MABS-PD) associated with substantial morbidity, increased healthcare utilisation, impaired quality of life and increased mortality. Treatment regimens for MABS-PD are highly variable, not evidence-based and involve complex, expensive drug combinations administered for prolonged periods (>12 months) with frequent adverse effects and treatment failure. There is an urgent need for safe, efficacious and cost-effective MABS-PD therapy. Here, we describe the Master Protocol for the Finding the Optimal Regimen for Mycobacteroides abscessus Treatment (FORMaT) trial. FORMaT aims to determine the most effective and best tolerated treatment for MABS-PD as defined by MABS clearance from respiratory samples with good treatment tolerance.

FORMaT is an international multicentre, adaptive platform trial evaluating treatment combinations for MABS-PD. Participants are randomised multiple times during the trial, with assessment of the primary outcome of clearance of MABS infection with good treatment tolerance. Initially, therapies recommended in international consensus guidelines are being tested. Data obtained will eliminate therapies lacking efficacy or causing unacceptable toxicity. Novel treatments can then be added and tested against previously determined optimal approaches, leading in an iterative fashion to improved microbiological clearance and health outcomes. In parallel, an Observational cohort and several integrated and discovery studies are embedded in FORMaT to identify biomarkers of MABS-PD and MABS clearance, clinical and radiographic treatment response, drug pharmacokinetics and Mycobacteroides genomics and resistome.

The FORMaT Master Protocol and related documents are approved by regulatory authorities in each participating jurisdiction and/or site. Results will be published in peer-reviewed journals and presented at scientific meetings. De-identified, aggregated data will be shared on an approved online platform.

NCT04310930, ANZCTR12618001831279, 2020-000050-10, ISRCTN67303903.

Huge advances in rheumatoid arthritis (RA) treatment mean an increasing number of patients now achieve disease remission. However, long-term treatments can carry side effects and associated financial costs. In addition, some patients still experience painful and debilitating disease flares, the mechanisms of which are poorly understood. High rates of flare and a lack of effective prediction tools can limit attempts at treatment withdrawal. The BIOlogical Factors that Limit sustAined Remission in rhEumatoid arthritis (BIO-FLARE) experimental medicine study was designed to study flare and remission immunobiology. Here, we present the clinical outcomes and predictors of drug-free remission and flare, and develop a prediction model to estimate flare risk.

BIO-FLARE was a multicentre, prospective, single-arm, open-label experimental medicine study conducted across seven National Health Service Trusts in the UK. Participants had established RA in clinical remission (disease activity score in 28 joints with C reactive protein (DAS28-CRP)

The intervention was disease-modifying anti-rheumatic drug cessation, followed by observation for 24 weeks or until flare, with clinical and immune monitoring.

The primary outcome measure was the proportion of participants experiencing a confirmed flare, defined as DAS28-CRP≥3.2 or DAS28-CRP≥2.4 twice within 2 weeks, and time to flare. Exploratory predictive modelling was also performed using multivariable Cox regression to understand risk factors for flare.

121 participants were recruited between September 2018 and December 2020. Flare rate by week 24 was 52.3% (95% CI 43.0 to 61.7), with a median (IQR) time to flare of 63 (41–96) days. Female sex, baseline methotrexate use, anti-citrullinated peptide antibody level and rheumatoid factor level were associated with flare. An exploratory prediction model incorporating these variables allowed estimation of flare risk, with acceptable classification (C index 0.709) and good calibration performance.

The rate of flare was approximately 50%. Several baseline clinical parameters were associated with flare. The BIO-FLARE study design provides a robust experimental medicine model for studying flare and remission immunobiology.

ISRCTN registry 16371380