Background: In the European RE-SAMPLE observational cohort, important predictors of disease progression, exacerbations and mortality of COPD patients with comorbidities are identified to further improve tailored disease management. Usually, the data collection is set at the start of the study, leaving no room for optimisation during follow up.

Aim: Optimising the data collection during cohort follow up to incorporate the most important predictors of outcomes of COPD and comorbidities.

Methods: We collected new insights via literature reviews and a citizen-science approach, in which patients and healthcare professionals (HCPs) reflected on the existing data collection.

Results: We conducted three iterations of the data collection. 36 HCPs and 41 patients from Estonia, Italy and The Netherlands proposed parameters that were important for them, but not obtained from literature (e.g., fatigue, body temperature). Patients reported a high participant burden. This led to a reduction of the number of questions, and of the frequency and length of the questionnaires supported by literature evidence. For example, the CCQ was removed as the CAT was already included. The final data collection includes, but is not limited to, patient characteristics (e.g., age, exacerbation history, nutritional status), comorbidities (e.g., Charlson index, HADS), symptoms (e.g., cough, dyspnoea), biomarkers (e.g., fibrinogen, NT-proBNP), lung function parameters (e.g., 6-MWD, FEV1), and composite scores (e.g., BODE, ADO).

Conclusion: A multidisciplinary and iterative approach, based on literature and experiences from HCPs and patients, results in an optimal data collection to predict outcomes of COPD and comorbidities.