Future risk projection to engage �near-miss� individuals in lung cancer screening eligibility: an analysis of ILST data
Bibliographic record
Abstract
Introduction Lung cancer risk increases with time, and participants who are initially ineligible for lung cancer screening (LCS) could become eligible later. The aim of this study was to determine the proportion of people (initially ineligible) who may become eligible in a risk model-based LCS programme and the impact smoking cessation could have on this cohort. Methods All potential participants for the International Lung Screening Trial aged 55�80 years, ineligible for Low-dose CT screening at baseline (PLCO m2012 <1.5% 6-year risk), were included. Assuming annual increments of change in age, smoking duration and quit time, and under the assumption of other risk variables being constant, projections of risk were made using the PLCO m2012 model from evaluation to the upper age limit of 80 years. Results 4451 subjects with a median age of 61 (IQR: 57�66) years were included. Assuming no change in smoking status post evaluation, 2239 participants (50.3%) became eligible (PLCO m2012 =1.51%) by age 80, with 26.9% and 38.7% of the cohort reaching eligibility by age 70 and 75 years, respectively. Among participants with a baseline risk=0.6%, 1518 (34.1%) reached eligibility within 10 years of initial evaluation. Smoking cessation after first evaluation can reduce the proportion of individuals who may become eligible for LCS by age 70 from 68.7% to 24.9%. Conclusions Future risk projection of eligibility could provide a time window for reassessment of risk on an individual level. It is important to provide smoking cessation services to individuals who are ineligible for LCS at the initial programme contact.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".