Brief Report: Risk Prediction Model Versus United States Preventive Services Task Force 2020 Draft Lung Cancer
Mary M Pasquinelli1, Martin C Tammemägi2, Kevin L Kovitz1
1Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois.
Introduction:
Eligibility criteria for lung cancer screening based solely on age and smoking history are less sensitive than validated risk prediction models. The U.S. Preventive Services Task Force (USPSTF) has proposed new guidelines to improve the sensitivity for selecting high-risk individuals and to decrease race disparity. In this retrospective study, termed the Chicago Race Eligibility for Screening Cohort, we compare the sensitivity of the proposed USPSTF2020 criteria versus the PLCOm2012 risk prediction model for selecting a racially diverse lung cancer population with a smoking history for lung cancer screening.
Methods:
This Chicago Race Eligibility for Screening Cohort study applies the PLCOm2012 model with a risk threshold of 1.0%/6 years and the USPSTF2020 criteria (age 50-80 y, pack-years ≥ 20 y, quit-years ≤ 15 y) to 883 individuals with a smoking history diagnosed with having lung cancer.
Results:
The PLCOm2012 was more sensitive than the USPSTF2020 overall (79.1% versus 68.6%, p < 0.0001) in White (81.5% versus 75.4%, p = 0.029) and in African American (82.8% versus 70.6% p < 0.0001) individuals. Of the total cohort, 254 (28.8%) would not have qualified owing to less than 20 pack-years, quit-time of more than 15 years, and age less than 50 years. Of these 254 cases, 40% would have qualified by the PLCOm2012 model. For the 20 pack-year criterion, of the 497 African American individuals, 19.3% did not meet this criterion, and of these, an additional 31.3% would have qualified by the PLCOm2012 model (p = 0.002).
Conclusions:
Although more sensitive than USPSTF2013, the proposed USPSTF2020 draft guidelines still have a race disparity in eligibility for screening. This study provides "real world" evidence that use of the PLCOm2012 risk prediction model eliminates this race disparity.
