Baseline Characteristics of Individuals with Paroxysmal Nocturnal Hemoglobinuria in an App-Based Home-Reported Outcomes Study to Evaluate Disease Burden
Authors: Dingli David , Zhang Connie , McStocker Samantha , Healey Amanda , Kuypers Nicholas , Chanpura Mohin , Anwar Hiba , Paulose Jincy , Lee Soyon , Seth Puja , Yen Glorian 
Published: December 2024

Background and significance: Paroxysmal nocturnal hemoglobinuria (PNH) is a rare condition caused by a somatic mutation in the PIG-A gene, leading to complement-mediated hemolysis and severe complications such as anemia and thrombosis. Patients often experience fatigue, dyspnea, and abdominal pain, impacting their daily lives and emotional well-being. This study aims to comprehensively explore the impact of PNH on health-related quality of life (HRQoL), alongside real-world treatment utilization and symptom burden patterns, especially as new treatments become available to this patient population. These results are based on interim baseline data from currently enrolled study participants, providing an initial assessment of their PNH disease experience. This analysis does not include any data collected prospectively during the data collection period.
Study design and methods: This ongoing, prospective, observational study (NCT06411626) aims to enroll at least 128 US-based participants aged 18 or older with PNH, regardless of treatment usage. Participants are recruited through clinician-based referrals, patient advocacy organizations, and community-based online channels. All activities can be completed remotely using the Folia Health app, the single site for this study. This app-based study aims to comprehensively assess patient-reported symptom burden, treatment use patterns, and impacts of PNH on health and FACIT-Fatigue through self-reported home-reported outcomes (HROs).
Participants will track symptoms and treatment use, including recently approved treatments (e.g., iptacopan, danicopan, crovalimab). HROs consist of participants' self-identified symptoms and personalized treatment plan that are tracked longitudinally against self-reported baselines. Semi-structured interviews and collaborative feedback sessions with PNH patients and clinicians yielded a comprehensive outcomes inventory for tracking key health outcomes specific to PNH. This inventory includes the ability to track infusion treatments and denote flare-ups in fatigue. Participants can customize their data collection to track symptoms in additional domains beyond those initially suggested (e.g., respiratory or immune).
At enrollment, participants report baseline health status and select their relevant symptoms and treatments to routinely track for 6 months. Monthly in-app surveys will collect data on overall health and the FACIT- Fatigue. The Folia app allows participants to visualize symptoms trends, set treatment reminders, and generate reports for their care team.
Results: Enrollment began on June 11, 2024. As of July 22, 2024, an interim data analysis was conducted on 20 participants; 65% (n=13) enrolled through online community-based channels and 35% (n=7) enrolled through clinic referrals. Participants selected 37 distinct symptoms and measurements and 26 distinct treatments to track over the 6-month period. The most common symptoms selected at baseline include fatigue (n=19), brain fog (n=17), and dark colored urine (n=15). PNH treatments selected for tracking include iptacopan (n=9), ravulizumab (n=5), eculizumab (n=4), and pegcetacoplan (n=3). The mean baseline FACIT- Fatigue score (n=18) was 35.7 and the median was 40 (IQR= 16). Further descriptive analyses stratified by primary treatment use will be conducted assessing characteristics of symptom burden, satisfaction with treatments-in-use, and self-reported impact on HRQoL.
Conclusions: Initial interim baseline data of recently enrolled participants with PNH show a variable disease experience. This app-based, observational study aims to establish a new real-world data source to understand patient priorities related to symptom variability, treatment patterns and preference, and impacts of condition management on HRQoL.