Lung cancer remains the most diagnosed malignancy and the leading cause of cancer-related mortality worldwide. Improving key clinical quality indicators (CQIs), including multidisciplinary meeting (MDM) presentation, supportive care screening, and timely diagnosis is essential for optimising patient outcomes. These indicators often co-occur, yet evidence on their shared spatio-temporal structure and the utility of joint modelling approaches remains limited. Thus, we aimed to explore the joint spatio-temporal patterns of these CQIs across Victoria, Australia. We analysed data from 12,970 lung cancer cases recorded in the Victorian Lung Cancer Registry (VLCR). A Bayesian hierarchical joint spatio-temporal shared-component model was employed to estimate the joint magnitude of MDM presentation, supportive care screening, and timely diagnosis across space (local government area) and time (year). To improve the precision of our estimates, information across the three outcomes was combined using both shared and outcome-specific components within the shared-component modelling framework. Models were estimated using Integrated Nested Laplace Approximation (INLA) in R-INLA and were compared using the Deviance Information Criterion (DIC). Approximately 35% of the total variation across CQIs was explained by shared spatial and temporal components. The shared temporal trend exhibited a modest but consistent increase over the study period, whereas outcome-specific temporal trends displayed distinct patterns. Shared spatial risk patterns closely paralleled CQI-specific distributions, highlighting regions with persistent geographic inequities in the delivery of lung cancer care. Substantial geographic and temporal disparities in lung cancer care were observed, with marked shared patterns across CQIs. These findings highlight the need for integrated, geographically targeted strategies to strengthen MDM presentation, supportive care screening, and timely diagnosis, thereby improving coordination and reducing inequities in lung cancer management.
Tesema et al. (Fri,) studied this question.