Beyond the AJR: “Using prediction-models to reduce persistent racial/ethnic disparities in draft 2020 USPSTF lung-cancer screening guidelines”

Author(s):  
Efrén J. Flores ◽  
Anand K. Narayan
Author(s):  
Rebecca Landy ◽  
Corey D Young ◽  
Martin Skarzynski ◽  
Li C Cheung ◽  
Christine D Berg ◽  
...  

Abstract We examined whether draft 2020 United States Preventive Services Task Force (USPSTF) lung-cancer screening recommendations “partially ameliorate racial disparities in screening eligibility” compared to 2013 guidelines, as claimed. Using data from the 2015 National Health Interview Survey, USPSTF-2020 increased eligibility by similar proportions for minorities (97.1%) and Whites (78.3%). Contrary to the intent of USPSTF-2020, the relative disparity (differences in percentages of model-estimated gainable life-years from National Lung Screening Trial-like screening by eligible Whites vs minorities) actually increased from USPSTF-2013 to USPSTF-2020 (African Americans: 48.3%–33.4%=15.0% to 64.5%–48.5%=16.0%; Asian Americans: 48.3%–35.6%=12.7% to 64.5%–45.2%=19.3%; Hispanic Americans: 48.3%–24.8%=23.5% to 64.5%–37.0%=27.5%). However, augmenting USPSTF-2020 with high-benefit individuals selected by the Life-Years From Screening with Computed Tomography (LYFS-CT) model nearly eliminated disparities for African Americans (76.8%–75.5%=1.2%), and improved screening efficiency for Asian/Hispanic Americans, although disparities were reduced only slightly (Hispanic Americans) or unchanged (Asian Americans). Draft USPSTF-2020 guidelines increased the number of eligible minorities versus USPSTF-2013 but may inadvertently increase racial/ethnic disparities. LYFS-CT could reduce disparities in screening eligibility by identifying ineligible people with high predicted benefit, regardless of race/ethnicity.


2020 ◽  
Author(s):  
Rebecca Landy ◽  
Corey D. Young ◽  
Martin Skarzynski ◽  
Li C. Cheung ◽  
Christine D. Berg ◽  
...  

2020 ◽  
Vol 112 (11) ◽  
pp. 1136-1142 ◽  
Author(s):  
Summer S Han ◽  
Eric Chow ◽  
Kevin ten Haaf ◽  
Iakovos Toumazis ◽  
Pianpian Cao ◽  
...  

Abstract Background Current US Preventive Services Task Force (USPSTF) lung cancer screening guidelines are based on smoking history and age (55–80 years). These guidelines may miss those at higher risk, even at lower exposures of smoking or younger ages, because of other risk factors such as race, family history, or comorbidity. In this study, we characterized the demographic and clinical profiles of those selected by risk-based screening criteria but were missed by USPSTF guidelines in younger (50–54 years) and older (71–80 years) age groups. Methods We used data from the National Health Interview Survey, the CISNET Smoking History Generator, and results of logistic prediction models to simulate lifetime lung cancer risk-factor data for 100 000 individuals in the 1950–1960 birth cohorts. We calculated age-specific 6-year lung cancer risk for each individual from ages 50 to 90 years using the PLCOm2012 model and evaluated age-specific screening eligibility by USPSTF guidelines and by risk-based criteria (varying thresholds between 1.3% and 2.5%). Results In the 1950 birth cohort, 5.4% would have been ineligible for screening by USPSTF criteria in their younger ages but eligible based on risk-based criteria. Similarly, 10.4% of the cohort would be ineligible for screening by USPSTF in older ages. Notably, high proportions of blacks were ineligible for screening by USPSTF criteria at younger (15.6%) and older (14.2%) ages, which were statistically significantly greater than those of whites (4.8% and 10.8%, respectively; P < .001). Similar results were observed with other risk thresholds and for the 1960 cohort. Conclusions Further consideration is needed to incorporate comprehensive risk factors, including race and ethnicity, into lung cancer screening to reduce potential racial disparities.


2021 ◽  
Vol 16 (10) ◽  
pp. S1173-S1174
Author(s):  
C. Olazagasti ◽  
A. Velazquez ◽  
M. Ehrlich ◽  
N. Kohn ◽  
N. Seetharamu

JAMA Oncology ◽  
2021 ◽  
Author(s):  
Alexandra L. Potter ◽  
Chi-Fu Jeffrey Yang ◽  
Kirsten M. Woolpert ◽  
Thrusha Puttaraju ◽  
Kei Suzuki ◽  
...  

2019 ◽  
Vol 112 (5) ◽  
pp. 466-479 ◽  
Author(s):  
Kevin ten Haaf ◽  
Mehrad Bastani ◽  
Pianpian Cao ◽  
Jihyoun Jeon ◽  
Iakovos Toumazis ◽  
...  

Abstract Background Risk-prediction models have been proposed to select individuals for lung cancer screening. However, their long-term effects are uncertain. This study evaluates long-term benefits and harms of risk-based screening compared with current United States Preventive Services Task Force (USPSTF) recommendations. Methods Four independent natural history models were used to perform a comparative modeling study evaluating long-term benefits and harms of selecting individuals for lung cancer screening through risk-prediction models. In total, 363 risk-based screening strategies varying by screening starting and stopping age, risk-prediction model used for eligibility (Bach, PLCOm2012, or Lung Cancer Death Risk Assessment Tool [LCDRAT]), and risk threshold were evaluated for a 1950 US birth cohort. Among the evaluated outcomes were percentage of individuals ever screened, screens required, lung cancer deaths averted, life-years gained, and overdiagnosis. Results Risk-based screening strategies requiring similar screens among individuals ages 55–80 years as the USPSTF criteria (corresponding risk thresholds: Bach = 2.8%; PLCOm2012 = 1.7%; LCDRAT = 1.7%) averted considerably more lung cancer deaths (Bach = 693; PLCOm2012 = 698; LCDRAT = 696; USPSTF = 613). However, life-years gained were only modestly higher (Bach = 8660; PLCOm2012 = 8862; LCDRAT = 8631; USPSTF = 8590), and risk-based strategies had more overdiagnosed cases (Bach = 149; PLCOm2012 = 147; LCDRAT = 150; USPSTF = 115). Sensitivity analyses suggest excluding individuals with limited life expectancies (<5 years) from screening retains the life-years gained by risk-based screening, while reducing overdiagnosis by more than 65.3%. Conclusions Risk-based lung cancer screening strategies prevent considerably more lung cancer deaths than current recommendations do. However, they yield modest additional life-years and increased overdiagnosis because of predominantly selecting older individuals. Efficient implementation of risk-based lung cancer screening requires careful consideration of life expectancy for determining optimal individual stopping ages.


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