Investigating the relationship between lung function decline and time to death or lung transplantation, accounting for geographical variability

Objectives: FEV1 % predicted is commonly used to monitor lung function decline and to predict mortality and transplantation in the CF population. An association between CF patients’ lung function decline and survival or lung transplantation has been previously reported, however, it is unknown how geographical location may affect this relationship.
Methods: We conducted a longitudinal cohort study of patients receiving care at a CF centre in the midwestern United States, acquiring demographic and clinical characteristics. Prior joint models applied to CF natural history cohorts indicate accelerated lung function decline increases the hazard of lung transplant or death. However, previous analysis has ignored the spatial variability among CF patients living in different regions. To explore how this association changes between different geographical areas, we first clustered zip-codes by deprivation index and included this information as a fixed effect interacting with the longitudinal outcome in the survival sub-model. Posteriorly, we extended the standard joint model to incorporate a spatial frailty effect in the survival sub-model to account for unobserved heterogeneity among individuals residing in the city location of the care centre.
Results: Preliminary results assuming 203 patients with 10,920 observations revealed that the association between FEV1 decline with survival varies across regions. The association varied from −0.14 (95%CI −0.32, 0.03) in regions with large deprivation index to −0.22 (95%CI −0.4, −0.05) in regions with small deprivation index. These results suggest that the spatial risk of death or transplantation varied across different regions.
Conclusion: Better understanding how the association between lung function decline and death or lung transplantation changes across different geographical regions could bring new insights into CF disease progression, thereby paving the way towards more personalised monitoring and treatment strategies locally.