How frequently should workplace spirometry screening be performed?: optimization via analytic models.
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.
Harber
Philip
P
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.
Levine
Jessica
J
Occupational-Environmental Preventive Medicine, Department of Family Medicine, David Geffen School of Medicine at the University of California at Los Angeles, Los Angeles, CA.
Bansal
Siddharth
S
Occupational-Environmental Preventive Medicine, Department of Family Medicine, David Geffen School of Medicine at the University of California at Los Angeles, Los Angeles, CA.
D003661:Decision Support Techniques; D003931:Diacetyl / Q000633:toxicity; D018450:Disease Progression; D006801:Humans; D008390:Markov Chains; D008962:Models, Theoretical; D016273:Occupational Exposure; D012307:Risk Factors; D013147:Spirometry / Q000592:standards*; D017132:Workplace
D003931:Diacetyl