Prospective observational study in patients with obstructive lung disease: NOVELTY design.
Helen K ReddelMaria Gerhardsson de VerdierAlvar AgustíGary AndersonRichard BeasleyElisabeth H BelChrister JansonBarry J MakeRichard J MartinIan PavordDavid J PriceChristina KeenAsparuh GardevStephen RennardAlecka SveréusAruna T BansalLance BrannmanNiklas KarlssonJavier NuevoFredrik NybergSimon S YoungJørgen VestboPublished in: ERJ open research (2019)
Asthma and chronic obstructive pulmonary disease (COPD) have overlapping clinical features and share pathobiological mechanisms but are often considered distinct disorders. Prospective, observational studies across asthma, COPD and asthma-COPD overlap are limited. NOVELTY is a global, prospective observational 3-year study enrolling ∼12 000 patients ≥12 years of age from primary and specialist clinical practices in 19 countries (ClinicalTrials.gov identifier: NCT02760329). NOVELTY's primary objectives are to describe patient characteristics, treatment patterns and disease burden over time, and to identify phenotypes and molecular endotypes associated with differential outcomes over time in patients with a diagnosis/suspected diagnosis of asthma and/or COPD. NOVELTY aims to recruit real-world patients, unlike clinical studies with restrictive inclusion/exclusion criteria. Data collected at yearly intervals include clinical assessments, spirometry, biospecimens, patient-reported outcomes (PROs) and healthcare utilisation (HCU). PROs and HCU will also be collected 3-monthly via internet/telephone. Data will be used to identify phenotypes and endotypes associated with different trajectories for symptom burden, clinical progression or remission and HCU. Results may allow patient classification across obstructive lung disease by clinical outcomes and biomarker profile, rather than by conventional diagnostic labels and severity categories. NOVELTY will provide a rich data source on obstructive lung disease, to help improve patient outcomes and aid novel drug development.
Keyphrases
- chronic obstructive pulmonary disease
- lung function
- patient reported outcomes
- end stage renal disease
- healthcare
- cystic fibrosis
- newly diagnosed
- chronic kidney disease
- ejection fraction
- air pollution
- big data
- electronic health record
- peritoneal dialysis
- primary care
- case report
- systemic lupus erythematosus
- machine learning
- social media
- pulmonary embolism
- deep learning
- adipose tissue
- type diabetes
- disease activity
- insulin resistance
- combination therapy