E-cigarette use and United States Preventive Services Task Force (USPSTF) lung cancer screening (LCS) eligibility.
Bibliographic record
Abstract
10531 Background: Electronic cigarettes (E-cigarettes) have become frequently used as a smoking cessation tool. Emerging research has shown that e-cigarettes have similar carcinogenic effects as combustible cigarettes. While current lung cancer screening (LCS) guidelines primarily rely on individuals’ smoking history, it's becoming increasingly important to understand the prevalence of e-cigarette use among individuals, especially in the context of their LCS eligibility. Methods: Individuals aged 40-80 years were extracted from the 2022 Behavioral Risk Factor Surveillance System. Eligibility was defined using the 2021 USPSTF LCS criteria, i.e., aged 50-80 years who ever smoked, with at least a 20-pack-year smoking history, currently smoke or quit within the past 15 years. We compared the prevalence of current and ever e-cigarette use among LCS-eligible and non-eligible populations, overall and by smoking (combustible cigarettes) status using chi-square tests. All analyses were weighted. The significance level was set at a 2-sided p-value of <0.05. Results: Among the 208,317 individuals included, 9.9% were eligible for LCS. Overall, 3.8% and 22.1% reported current and ever cigarette use, respectively. Fewer LCS-ineligible individuals reported currently using e-cigarettes than their LCS-eligible counterparts (Table). Among former combustible cigarette users, LCS-ineligible individuals were less likely to be current e-cigarette user than LCS-eligible individuals. However, among current combustible cigarette users, LCS-ineligible individuals were more likely to be current e-cigarettes users than LCS-eligible individuals. When examining the prevalence of ever e-cigarette use, similar findings were observed. Conclusions: Our study reveals a significant prevalence of e-cigarette usage among older adults (aged 40-80), with 1 in 5 individuals reporting ever having used e-cigarettes. Moreover, current cigarette users who were ineligible for LCS were more likely to use e-cigarette than their LCS-eligible counterparts. Future epidemiological studies are warranted to assess the risk of e-cigarette use (including intensity, duration and interactions with combustible cigarettes) and lung cancer risks. E-cigarette use may need to be considered in formulating future LCS guidelines. [Table: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".