Retrospective analysis of PFIC data
Statistical modelling of disease trajectories and survival towards a better understanding of PFIC disease
P. Huisman (TU Delft - Electrical Engineering, Mathematics and Computer Science)
G. Jongbloed – Mentor (TU Delft - Statistics)
GF Nane – Graduation committee member (TU Delft - Applied Probability)
B.E. Hansen – Mentor (Erasmus MC)
P. Miranda Afonso – Mentor (Erasmus MC)
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Abstract
Progressive familial intrahepatic cholestasis (PFIC) is a group of rare, inherited liver diseases that affect children and are characterised by impaired bile flow. Since PFIC is a paediatric ultra-rare disease, conducting randomised controlled trials is particularly challenging, making observational data essential for improving clinical management. This thesis analyses a large multinational observational retrospective data cohort with long-term follow-up of PFIC patients. The aim is to improve our understanding of PFIC and support more informed decision-making in patient care through the investigation of two key aspects of disease monitoring and progression. First, the thesis explores longitudinal trajectories of relevant biochemical parameters, serum bile acid levels and platelet counts, in patients with a specific subtype of PFIC, PFIC2, using latent class linear mixed models. This approach effectively identified distinct longitudinal patterns of serum bile acids and platelet counts in patients with PFIC2. These patterns highlight significant heterogeneity in the progression of laboratory parameters over time. Second, a comparative analysis of event-free survival is conducted between two European regional cohorts of PFIC patients, North-West Europe and South-Central Europe. Hypothesising that there are no differences in event-free survival of PFIC patients despite different care settings. This is achieved through a weighted survival analysis combining inverse probability treatment weighting with the Kaplan-Meier estimator and the Cox proportional hazards model. The results suggest there are no significant regional differences in event-free survival among PFIC2 patients between the two cohorts. Furthermore, a sensitivity analysis and permutation test have been performed, which also support this result. Together, these findings contribute to a more detailed understanding of disease progression in PFIC patients and provide practical tools and insights that can inform patient monitoring and clinical decision-making in the absence of randomised trials.