TUBERCULOSIS (TB) remains a persistent health concern among migrants to low-TB-incidence countries, including Canada. With systematic TB screening often cost-prohibitive, researchers have developed a groundbreaking dynamic risk prediction model to guide more effective screening practices.
Using comprehensive health administrative data from British Columbia and Ontario, the study involved over 1.67 million individuals. The model incorporated demographic, medical, and TB exposure data, including factors like age, sex, refugee status, and TB incidence in the country of origin. It demonstrated strong predictive performance, achieving a concordance statistic of 0.77 for both 2- and 5-year TB risk predictions in the Ontario cohort.
This innovative approach could transform TB screening policies by enabling targeted interventions for high-risk groups. The model’s developers emphasize its potential to improve cost-effectiveness in healthcare systems while prioritizing individuals most at risk. The tool provides an accessible platform for healthcare professionals to implement evidence-based screening decisions.
As TB incidence declines in countries like the U.S., applying tools like this could help focus resources on vulnerable populations, enhancing public health outcomes. This model represents a promising step forward in balancing global migration and healthcare challenges.
Reference: Puyat JH et al. Predicting risk of tuberculosis disease in people migrating to a low-TB incidence country: development and validation of a multivariable dynamic risk prediction model using health administrative data. Clin Infect Dis. 2024;ciae561.
Anaya Malik | AMJ
