Interstitial Lung Abnormalities in a CT Lung Cancer Screening Population: Prevalence and Progression Rate
Bibliographic record
Abstract
PURPOSE: To determine the prevalence of interstitial lung abnormalities (ILAs) at initial computed tomography (CT) examination and the rate of progression of ILAs on 2-year follow-up CT images in a National Lung Screening Trial population studied at a single site. MATERIALS AND METHODS: The study was approved by the institutional review board and informed consent was obtained from all participants. Image review for this study was HIPAA compliant. We reviewed the CT images of 884 cigarette smokers who underwent low-dose CT at a single site in the National Lung Screening Trial. CT findings were categorized as having no evidence of ILA, equivocal for ILA, or ILA. We categorized the type of ILA as nonfibrotic (ground-glass opacity, consolidation, mosaic attenuation), or fibrotic (ground glass with reticular pattern, reticular pattern, honeycombing). We evaluated the temporal change of the CT findings (no change, improvement, or progression) of ILA at 2-year follow-up. A χ(2) with Fisher exact test or unpaired t test was used to determine whether smoking parameters were associated with progression of ILA at 2-year follow-up CT. RESULTS: The prevalence of ILA was 9.7% (86 of 884 participants; 95% confidence interval: 7.9%, 11.9%), with a further 11.5% (102 of 884 participants) who had findings equivocal for ILA. The pattern was fibrotic in 19 (2.1%), nonfibrotic in 52 (5.9%), and mixed fibrotic and nonfibrotic in 15 (1.7%) of the 86 participants with ILA. The percentage of current smokers (P = .001) and mean number of cigarette pack-years (P = .001) were significantly higher in those with ILA than those without. At 2-year follow-up of those with ILA (n = 79), findings of nonfibrotic ILA improved in 49% of cases and progressed in 11%. Fibrotic ILA improved in 0% and progressed in 37% of cases. CONCLUSION: ILA is common in cigarette smokers. Nonfibrotic ILA improved in about 50% of cases, and fibrotic ILA progressed in about 37%.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".