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Prospective observational study in patients with obstructive lung disease: NOVELTY design

  • Helen K. Reddel*
  • , Maria Gerhardsson de Verdier
  • , Alvar Agustí
  • , Gary Anderson
  • , Richard Beasley
  • , Elisabeth H. Bel
  • , Christer Janson
  • , Barry Make
  • , Richard J. Martin
  • , Ian Pavord
  • , David Price
  • , Christina Keen
  • , Asparuh Gardev
  • , Stephen Rennard
  • , Alecka Sveréus
  • , Aruna T. Bansal
  • , Lance Brannman
  • , Niklas Karlsson
  • , Javier Nuevo
  • , Fredrik Nyberg
  • Simon S. Young, Jørgen Vestbo
*Corresponding author for this work
  • The University of Sydney
  • AstraZeneca
  • University of Barcelona
  • University of Melbourne
  • Medical Research Institute of New Zealand
  • Uppsala University
  • University of Colorado Denver
  • University of Oxford
  • University of Aberdeen
  • Acclarogen
  • University of Manchester

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

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.

Original languageEnglish
Article number00036-2018
JournalERJ open research
Volume5
Issue number1
DOIs
Publication statusPublished - Feb 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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