Screening Criteria Evaluation for Expansion in Pulmonary Neoplasias (SCREEN) II
Bibliographic record
Abstract
Background: There is a need to expand eligibility criteria for lung cancer screening beyond age and smoking history. In this study, we sought to assess whether light-or-never-smokers and heavy smokers differ in molecular and immunologic markers based on conventional lung cancer screening criteria. Methods: We conducted a retrospective review of lung cancer cases from 2005 to 2018 at a tertiary Canadian institution. We used multivariable logistic regression to compare the rate of molecular mutations (KRAS, EGFR, BRAF, PIK3CA, ALK, and PD-L1 [< 1%, 1%–49%, ≥ 50%]) and survival between light-or-never-smokers and heavy smokers. Results: We included 1156 patients with lung cancer. Overall, 46.4% (National Lung Screening Trial [NLST], n = 536) and 63.3% (Nederlands–Leuvens Long-kanker Screenings Onderzoek [NELSON], n = 732) of the patients were heavy smokers. Using NELSON criteria, screen-ineligible light-or-never-smokers were more frequently from areas at high risk for radon exposure (n = 175 [41.3%]) than screen-eligible heavy smokers (n = 285 [38.9%]). Light-or-never-smokers were more likely to be EGFR-positive in both NLST (odds ratio [OR] 0.79, 95% confidence interval [CI] 0.21–1.37; p = 0.008] and NELSON (OR 0.79, 95% CI 0.28–1.31; p = 0.002) models. Female light-or-never-smokers were more likely than male light-or-never-smokers to be EGFR-positive in NELSON (OR 0.59, 95% CI 0.06–1.12; p = 0.03] but not NLST (OR 0.51, 95% CI 0.02–1.05; p = 0.06) models. Light-or-never-smokers were more often PIK3CA-positive using NLST (OR 1.33, 95% CI 0.54–2.13; p = 0.001) and NELSON (OR 1.19, 95% CI 0.49–1.90; p = 0.001) models. Light-or-never-smokers in the NELSON model were at higher risk of death. Conclusion: Screen-ineligible light-or-never-smokers had a higher rate of EGFR-and PIK3CA-positive lung cancers than screen-eligible heavy smokers when defined using trial-based lung cancer screening eligibility criteria. Molecular profiling, particularly where targeted therapy is available, should be considered in future studies establishing criteria for lung cancer screening. Contexte: Il faut élargir les critères d’admissibilité au dépistage du cancer du poumon au-delà de l’âge et des antécédents tabagiques. Dans cette étude, nous avons voulu vérifier s’il y a des différences entre les personnes dont le tabagisme est léger, voire nul (groupe 1) et celles qui fument beaucoup (groupe 2) au plan des marqueurs moléculaires et immunologiques selon les critères classiques de dépistage du cancer du poumon. Méthodes: Nous avons procédé à une revue rétrospective des cas de cancer du poumon de 2005 à 2018 dans un établissement de soins tertiaires canadien. Nous avons utilisé la régression logistique multivariée pour comparer les taux de mutations moléculaires (KRAS, EGFR, BRAF, PIK3CA, ALK et PD-L1 [< 1 %, 1 %–49 %, ≥ 50 %]) et la survie entre les 2 groupes. Résultats: Nous avons inclus 1156 cas de cancer du poumon. En tout, 46,4 % (étude NLST [National Lung Screening Trial], n = 536) et 63,3 % (étude NELSON [ Nederlands–Leuvens Longkanker Screenings Onderzoek], n = 732) des malades étaient de gros fumeurs. À partir des critères de l’étude NELSON, le groupe 1, non admissible au dépistage, venait de secteurs à risque élevé d’exposition au radon (n = 175 [41,3 %]) comparativement au groupe 2, admissible au dépistage (n = 285 [38,9 %]). Le groupe 1 était plus susceptible d’être EGFR-positif, tant selon le modèle NLST (rapport des cotes [RC] 0,79, intervalle de confiance [IC] de 95 % 0,21–1,37; p = 0,008), que le modèle NELSON (RC 0,79, IC de 95 % 0,28–1,31; p = 0,002). Dans le groupe 1, les femmes étaient plus susceptibles que les hommes d’être EGFR-positives selon le modèle NELSON (RC 0,59, IC de 95 % 0,06–1,12; p = 0,03), mais non selon le modèle NLST (RC 0,51, IC de 95 % 0,02–1,05; p = 0,06). Le groupe 1 avait plus tendance à être PIK3CA-positif selon les modèles NLST (RC 1,33, IC de 95 % 0,54–2,13; p = 0,001) et NELSON (RC 1,19, IC de 95 % 0,49–1,90; p = 0,001). Selon le modèle NELSON, le groupe 1 était exposé à un risque de mortalité plus élevé. Conclusion: Les personnes dont le tabagisme est léger voire nul qui ne sont pas admissibles au dépistage ont présenté un taux plus élevé de cancer du poumon EGFRet PIK3CA-positifs comparativement aux gros fumeurs, lorsqu’on appliquait les critères d’admissibilité au dépistage du cancer du poumon des 2 essais cités. Il faudrait envisager un profilage moléculaire lors des prochaines études qui porteront sur les critères d’admissibilité au dépistage du cancer du poumon, surtout lorsqu’il existe des modalités thérapeutiques ciblées.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".