SynthesisJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2010
Screening for lung cancer with low-dose computed tomography: a systematic review and meta-analysis of the baseline findings of randomized controlled trials.
Synthesis in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Low-dose computed tomography (LDCT) versus other cancer screenings in early diagnosis of lung cancer: A meta-analysis.Medicine · 2018Pooled it
- A predictive nomogram for two-year growth of CT-indeterminate small pulmonary nodules.European radiology · 2022Trial
- Lung cancer screening with computer aided detection chest radiography: design and results of a randomized, controlled trial.PloS one · 2013Trial
- Early Post-discharge Pain Trajectories After Thoracoscopic Sublobar Resection for Stage IA Non-small Cell Lung Cancer.Annals of surgical oncology · 2026Observational
- Review
- Exosomal Thomsen-Friedenreich Glycoantigen: A New Liquid Biopsy Biomarker for Lung and Breast Cancer Diagnoses.Cancer research communications · 2024Article
- Benign-malignant classification of pulmonary nodules by low-dose spiral computerized tomography and clinical data with machine learning in opportunistic screening.Cancer medicine · 2023Article
- X-ray Cherenkov-luminescence tomography reconstruction with a three-component deep learning algorithm: Swin transformer, convolutional neural network, and locality module.Journal of biomedical optics · 2023Article
- Article
- Article
- A 10-year prediagnostic follow-up study shows that serum RNA signals are highly dynamic in lung carcinogenesis.Molecular oncology · 2020Article
- Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.PLoS medicine · 2018Article
- Small pulmonary nodules in baseline and incidence screening rounds of low-dose CT lung cancer screening.Translational lung cancer research · 2017Review
- MDC and BLC are independently associated with the significant risk of early stage lung adenocarcinoma.Oncotarget · 2016Article
- Predicting Malignant Nodules from Screening CT Scans.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2016Article
- A unique set of 6 circulating microRNAs for early detection of non-small cell lung cancer.Oncotarget · 2016Article
- Review
- Serum biomarkers reflecting specific tumor tissue remodeling processes are valuable diagnostic tools for lung cancer.Cancer medicine · 2014Article
- [Survey and analysis of awareness of lung cancer prevention and control in a LDCT lung cancer screening project in Tianjin Dagang Oilfield of China].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2014Article
- [Advance of lung cancer screening with low-dose spiral CT].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
objectivesLung cancer is the leading cause of death among all cancers. An estimated 29% of the global population older than 15 years currently smokes tobacco. The presence of a high risk population, relatively asymptomatic nature of the disease in the early phase, and relatively good prognosis when discovered early makes screening for lung cancer an attractive proposition. We performed a systematic review and a meta-analysis of the baseline results of randomized controlled trials so far published, which included more than 14,000 patients. Analysis was used to determine whether data was for or against the screening of lung cancers using low-dose computed tomography (LDCT).
designRandom effect meta regression model of meta-analysis and systematic review.
methodsWe performed a systematic review and a meta-analysis of the current literature to determine whether screening for lung cancer in a high-risk population with computed tomography improves outcomes. A search strategy using Medline was employed, studies selected based on preset criteria and application of exclusion criteria, and data collected and analyzed for statistical significance.
resultsScreening for lung cancer using LDCT resulted in a significantly higher number of stage I lung cancers (odds ratio 3.9, 95% confidence interval [CI] 2.0-7.4), higher number of total non-small cell lung cancers (odds ratio 5.5, 95% CI 3.1-9.6), and higher total lung cancers (odds ratio 4.1, 95% CI 2.4-7.1). Screening using LDCT also resulted in increased detection of false-positive nodules (odds ratio 3.1, 95% CI 2.6-3.7) and more unnecessary thoracotomies for benign lesions (event rate 3.7 per 1000, 95% CI 3.5-3.8). For every 1000 individuals screened with LDCT for lung cancer, 9 stage I non-small cell lung cancer and 235 false-positive nodules were detected, and 4 thoracotomies for benign lesions were performed.
conclusionsThe baseline data from six randomized controlled trials offer no compelling data in favor or against the use of LDCT screening for lung cancer. We await the final results of these randomized controlled trials to improve our understanding of the effectiveness of LDCT in the screening for lung cancer and its effect on mortality.
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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.