Philip Harber1, Jessica Levine2, Siddharth Bansal2. 1. Occupational-Environmental Preventive Medicine, Department of Family Medicine, David Geffen School of Medicine at the University of California at Los Angeles, Los Angeles, CA. Electronic address: pharber@mednet.ucla.edu. 2. Occupational-Environmental Preventive Medicine, Department of Family Medicine, David Geffen School of Medicine at the University of California at Los Angeles, Los Angeles, CA.
Abstract
BACKGROUND: Our objective was to determine how to select the optimal frequency of workplace spirometry screening using diacetyl-exposed workers as an example. METHODS: 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. RESULTS: 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. CONCLUSIONS: There is no single best screening interval. For high-risk populations, annual testing may be too infrequent.
BACKGROUND: Our objective was to determine how to select the optimal frequency of workplace spirometry screening using diacetyl-exposed workers as an example. METHODS: 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. RESULTS: 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. CONCLUSIONS: There is no single best screening interval. For high-risk populations, annual testing may be too infrequent.