Clinical trial simulations in pulmonary fibrosis: patient-focused insights and adaptations

ERJ Open Res. 2023 May 30;9(3):00602-2022. doi: 10.1183/23120541.00602-2022. eCollection 2023 May.

Abstract

Background: Patient recruitment and retention are a challenge when conducting clinical trials in patients with pulmonary fibrosis, including idiopathic pulmonary fibrosis and other interstitial lung diseases. This study aimed to understand and address the barriers associated with trial participation for these populations.

Methods: Nine patients, nine caregivers and three healthcare professionals participated in virtual simulations of planned phase III trials. During the simulations, participants received information about the trials and either tested a home spirometry device or watched a home spirometry demonstration, before providing their insights in debriefs. The findings were interpreted in advisory boards with representatives from patient organisations and expert investigators.

Results: Regarding barriers to participation, patient fatigue and breathlessness were emphasised as posing challenges for travel, visit length and completion of onsite assessments. Lack of information, support and appreciation were also identified as factors that may exacerbate anxiety and negatively affect participant retention rates. Feedback on the home spirometry was mixed, with participants appreciating being able to complete the test at home but worrying about device handling. Based on the insights gained, patient-friendly adaptations were made to the trial protocol and conduct, including remote assessment of patient-reported outcomes, increased visit flexibility, travel support services, patient and caregiver information campaigns, and training of investigators on patients' needs.

Conclusions: Participants identified important barriers to participation, which led to patient-friendly changes being made to the planned trials. As a result, participation in the planned trials should be less burdensome, with improved recruitment and retention rates, and ultimately, improved data quality.