Lung cancer screening use and implications of varying eligibility criteria by race and ethnicity: 2019 Behavioral Risk Factor Surveillance System data
Bibliographic record
Abstract
Background In 2021, the US Preventive Services Task Force (USPSTF) expanded the eligibility criteria for low‐dose computed tomographic lung cancer screening (LCS) to reduce racial disparities that resulted from the 2013 USPSTF criteria. The annual LCS rate has risen slowly since the 2013 USPSTF screening recommendations. Using the 2019 Behavioral Risk Factor Surveillance System (BRFSS), this study 1) describes LCS use in 2019, 2) compares the percent eligible for LCS using the 2013 versus 2021 USPSTF criteria, and 3) determines the percent eligible using the more detailed PLCOm2012 Race3L risk‐prediction model. Methods The analysis included 41,544 individuals with a smoking history from states participating in the BRFSS LCS module who were ≥50 years old. Results Using the 2013 USPSTF criteria, 20.7% (95% confidence interval [CI], 19.0‐22.4) of eligible individuals underwent LCS in 2019. The 2013 USPSTF criteria was compared to the 2021 USPSTF criteria, and the overall proportion eligible increased from 21.0% (95% CI, 20.2‐21.8) to 34.7% (95 CI, 33.8‐35.6). Applying the 2021 criteria, the proportion eligible by race was 35.8% (95% CI, 34.8‐36.7) among Whites, 28.5% (95% CI, 25.2‐31.9) among Blacks, and 18.0% (95% CI, 12.4‐23.7) among Hispanics. Using the 1.0% 6‐year threshold that is comparable to the 2021 USPSTF criteria, the PLCOm2012 Race3L model selected more individuals overall and by race. Conclusions Using data from 20 states and using multiple imputation, higher LCS rates have been reported compared to prior BRFSS data. The 2021 expanded criteria will result in a greater number of screen‐eligible individuals. However, risk‐based screening that uses additional risk factors may be more inclusive overall and across subgroups. Lay Summary In 2013, lung cancer screening (lung screening) was recommended for high risk individuals. The annual rate of lung screening has risen slowly, particularly among Black individuals. In part, this racial disparity resulted in expanded 2021 criteria. Survey data was used to: 1) describe the number of people screened in 2019, 2) compare the percent eligible for lung screening using the 2013 versus 2021 guidelines, and 3) determine the percent eligible using more detailed criteria. Lung screening rates increased in 2019, and the 2021 criteria will result in more individuals eligible for screening. Using additional criteria may identify more individuals eligible for lung screening.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".