Trial reportJAMA network open2019
Development and Validation of a Multivariable Lung Cancer Risk Prediction Model That Includes Low-Dose Computed Tomography Screening Results: A Secondary Analysis of Data From the National Lung Screening Trial.
Trial report in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 50 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
National Lung Screening Trial A Randomized Trial Comparing Low-dose Helical CT With Chest Xray for Lung Cancer
Understanding Lung Cancer Related Risk Factors and Their Impact
Who cites it
50 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Use and impact of risk-based eligibility models in low-dose computed tomography lung cancer screening: a systematic review.Public health reviews · 2026Pooled it
- Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- Guideline
- A radiomics nomogram integrated with radiological features for preoperative prediction of lung nodule invasiveness: comparison with Lung-RADS.Translational lung cancer research · 2026Article
- A hybrid LSTM-GRU framework for lung cancer classification using GWO-WOA algorithm for hyperparameter tuning and BPSO for feature selection.Scientific reports · 2026Article
- Beyond nodules: body composition as a biomarker for future lung cancer.European radiology · 2025Article
- Article
- Article
- Risk of second primary lung cancer among cancer survivors stratified by the site of first primary cancer and the lung cancer screening eligibility status.International journal of cancer · 2025Article
- The quality of patient decision aids for lung cancer screening: Results from an environmental scan.Cancer · 2025Review
- Constructing multicancer risk cohorts using national data from medical helplines and secondary care.NPJ digital medicine · 2025Article
- External Testing of a Deep Learning Model for Lung Cancer Risk from Low-Dose Chest CT.Radiology · 2025Article
- Te Oranga Pūkahukahu research programme: intentional steps towards a national equity-focused lung cancer screening programme in Aotearoa New Zealand.Journal of the Royal Society of New Zealand · 2025Article
- Ethical Dimensions of Population-Based Lung Cancer Screening in Canada: Key Informant Qualitative Description Study.Public health ethics · 2024Article
- The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Lung cancer screening: where do we stand?Breathe (Sheffield, England) · 2024Review
- Safety net hospital risk model demonstrates stronger, population-specific applicability in characterizing lung cancer risk.Translational cancer research · 2024Article
- Recommended approaches for screening and early detection of lung cancer in the Middle East and Africa (MEA) region: a consensus statement.Journal of thoracic disease · 2024Review
- Personal history of cancer as a risk factor for second primary lung cancer: Implications for lung cancer screening.Cancer medicine · 2024Article
- Biomarkers as a tool to reduce disparities in lung cancer screening and detection.Translational lung cancer research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Importance: Low-dose computed tomography lung cancer screening is most effective when applied to high-risk individuals. Objectives: To develop and validate a risk prediction model that incorporates low-dose computed tomography screening results. Design, Setting, and Participants: A logistic regression risk model was developed in National Lung Screening Trial (NLST) Lung Screening Study (LSS) data and was validated in NLST American College of Radiology Imaging Network (ACRIN) data. The NLST was a randomized clinical trial that recruited participants between August 2002 and April 2004, with follow-up to December 31, 2009. This secondary analysis of data from the NLST took place between August 10, 2013, and November 1, 2018. Included were LSS (n = 14 576) and ACRIN (n = 7653) participants who had 3 screens, adequate follow-up, and complete predictor information. Main Outcomes and Measures: Incident lung cancers occurring 1 to 4 years after the third screen (202 LSS and 96 ACRIN). Predictors included scores from the validated PLCOm2012 risk model and Lung CT Screening Reporting & Data System (Lung-RADS) screening results. Results: Overall, the mean (SD) age of 22 229 participants was 61.3 (5.0) years, 59.3% were male, and 90.9% were of non-Hispanic white race/ethnicity. During follow-up, 298 lung cancers were diagnosed in 22 229 individuals (1.3%). Eight result combinations were pooled into 4 groups based on similar associations. Adjusted for PLCOm2012 risks, compared with participants with 3 negative screens, participants with 1 positive screen and last negative had an odds ratio (OR) of 1.93 (95% CI, 1.34-2.76), and participants with 2 positive screens with last negative or 2 negative screens with last positive had an OR of 2.66 (95% CI, 1.60-4.43); when 2 or more screens were positive with last positive, the OR was 8.97 (95% CI, 5.76-13.97). In ACRIN validation data, the model that included PLCOm2012 scores and screening results (PLCO2012results) demonstrated significantly greater discrimination (area under the curve, 0.761; 95% CI, 0.716-0.799) than when screening results were excluded (PLCOm2012) (area under the curve, 0.687; 95% CI, 0.645-0.728) (P < .001). In ACRIN validation data, PLCO2012results demonstrated good calibration. Individuals who had initial negative scans but elevated PLCOm2012 six-year risks of at least 2.6% did not have risks decline below the 1.5% screening eligibility criterion when subsequent screens were negative. Conclusions and Relevance: According to this analysis, some individuals with elevated risk scores who have negative initial screens remain at elevated risks, warranting annual screening. Positive screens seem to increase baseline risk scores and may identify high-risk individuals for continued screening and enrollment into clinical trials. Trial Registration: ClinicalTrials.gov Identifier: NCT00047385.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.