ReviewJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2019
Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges.
Review in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 291 papers, 13 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
291 citing papers in PubMed, 13 syntheses or guidelines pooled it, 562 citations in OpenAlex.
- Perioperative Outcomes of Complex Versus Simple Segmentectomy Via Uniportal Video-Assisted Thoracoscopic Surgery for Lung Lesions: A Systematic Review and Meta-Analysis.Interdisciplinary cardiovascular and thoracic surgery · 2026Pooled it
- Breathing insights: Biomarkers as tools for chronic obstructive pulmonary disease assessment - A systematic review.Indian journal of pharmacology · 2026Pooled it
- Cancer Risk Prediction Using Machine Learning for Supporting Early Cancer Diagnosis in Symptomatic Patients: A Systematic Review of Model Types.Cancer medicine · 2025Pooled it
- Mitochondrial DNA Copy Numbers and Lung Cancer: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2025Pooled it
- Salivary Extracellular Vesicles in Detection of Cancers Other than Head and Neck: A Systematic Review.Cells · 2025Pooled 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
- GDF-15 as a biomarker for diagnosis and prognosis of lung cancer: a meta-analysis.Frontiers in oncology · 2025Pooled it
- AI models for the identification of prognostic and predictive biomarkers in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Pooled it
- High SNHG expression may predict a poor lung cancer prognosis based on a meta-analysis.BMC cancer · 2023Pooled it
- Lung Cancer Screening With Low-Dose Computed Tomography.Deutsches Arzteblatt international · 2023Pooled it
- CT radiomics for differentiating oncocytoma from renal cell carcinomas: Systematic review and meta-analysis.Clinical imaging · 2023Pooled it
- [China National Lung Cancer Screening Guideline with Low-dose Computed Tomography (2023 Version)].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023Guideline
- A nomogram based on metabolic profiling to discriminate lung cancer among patients with lung nodules.The Journal of international medical research · 2023Trial
- Circulating tumor-associated autoantibody signatures for diagnosis and prognosis in small-cell lung cancer and lung adenocarcinoma.British journal of cancer · 2026Article
- PDLIM2 acts as a central regulator of ubiquitination, immune signaling, and mitochondrial metabolism in lung cancer suppression (Review).International journal of oncology · 2026Review
- Elevated glucose metabolism via the hexosamine biosynthesis pathway: A metabolic signature of high-fluorodeoxyglucose-uptake lung adenocarcinoma.Surgery today · 2026Article
- Tumor-associated collagen signature in relation to metastasis in lung adenocarcinoma.Journal of thoracic disease · 2026Article
- Over- and underscreening for lung cancer.Translational lung cancer research · 2026Review
- Artificial intelligence in lung cancer: a bibliometric analysis of emerging trends and research hotspots.Annals of medicine and surgery (2012) · 2026Article
231 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 9 institutions in 5 countries.
Funding
Abstract
The present review is an update of the research and development efforts regarding the use of molecular biomarkers in the lung cancer screening setting. The two main unmet clinical needs, namely, the refinement of risk to improve the selection of individuals undergoing screening and the characterization of undetermined nodules found during the computed tomography-based screening process are the object of the biomarkers described in the present review. We first propose some principles to optimize lung cancer biomarker discovery projects. Then, we summarize the discovery and developmental status of currently promising molecular candidates, such as autoantibodies, complement fragments, microRNAs, circulating tumor DNA, DNA methylation, blood protein profiling, or RNA airway or nasal signatures. We also mention other emerging biomarkers or new technologies to follow, such as exhaled breath biomarkers, metabolomics, sputum cell imaging, genetic predisposition studies, and the integration of next-generation sequencing into study of circulating DNA. We also underline the importance of integrating different molecular technologies together with imaging, radiomics, and artificial intelligence. We list a number of completed, ongoing, or planned trials to show the clinical utility of molecular biomarkers. Finally, we comment on future research challenges in the field of biomarkers in the context of lung cancer screening and propose a design of a trial to test the clinical utility of one or several candidate biomarkers.
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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 Socratic graph.