Our objective was to determine how to select the optimal frequency of workplace spirometry screening using diacetyl-exposed workers as an example.
A Markov model was constructed to assess the likelihood of progressing from healthy status to early or advanced disease, starting from four different exposure levels, and performing longitudinal or cross-sectional interpretation of spirometry results over time. Projected outcomes at 10 years were evaluated to inform the optimal frequency of workplace spirometry testing.
The optimal screening interval depends on the population risk and is highly sensitive to the real-life impact (utility) associated with false-positive results (eg, related to the availability of alternative work). Screening interval is particularly important for high-risk individuals with rapid transition from early to advanced disease, where the 10-year prevalence of advanced disease would be reduced from 5.3 to 2.5% using a 6-month interval rather than a 12-month interval. Longitudinal test interpretation, based on observing trends within each person over time, is marginally preferable to traditional cross-sectional spirometry interpretation.
There is no single best screening interval. For high-risk populations, annual testing may be too infrequent.