ArticleCancers2021
Exploring Volatile Organic Compounds in Breath for High-Accuracy Prediction of Lung Cancer.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 5 of them syntheses that pooled it.
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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.
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Who cites it
47 citing papers in PubMed, 5 syntheses or guidelines pooled it, 119 citations in OpenAlex.
- Advanced strategy for cancer detection based on volatile organic compounds in breath.Journal of nanobiotechnology · 2025Pooled it
- Exploring Components, Sensors, and Techniques for Cancer Detection via eNose Technology: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Inconsistencies in predictive models based on exhaled volatile organic compounds for distinguishing between benign pulmonary nodules and lung cancer: a systematic review.BMC pulmonary medicine · 2024Pooled it
- Pooled it
- Accuracy of minimal residual disease detection by circulating tumor DNA profiling in lung cancer: a meta-analysis.BMC medicine · 2023Pooled it
- Few-Shot Lung Cancer Classification via Electronic Nose Using Large Language Models: A Multicentre Prospective Study.Respirology (Carlton, Vic.) · 2026Article
- Exploratory Volatilome Profiling of Inflammation in Skin Fibroblasts: A Proof-of-Concept Study.International journal of molecular sciences · 2026Article
- Interpretable hybrid ensemble with attention-based fusion and EAOO-GA optimization for lung cancer detection.Scientific reports · 2026Article
- Early Detection of Lung Cancer: A Review of Innovative Milestones and Techniques.Journal of clinical medicine · 2025Review
- Breath Metabolome Profiling Using Porous Carbon Material for Early Diagnosis of Laryngeal Cancer: Preliminary Results.Cancers · 2025Article
- The Role of Breath Analysis in the Non-Invasive Early Diagnosis of Malignant Pleural Mesothelioma (MPM) and the Management of At-Risk Individuals.Molecules (Basel, Switzerland) · 2025Observational
- Determination of lung cancer exhaled breath biomarkers using machine learning-a new analysis framework.Scientific reports · 2025Article
- Diagnostic Potential of Volatile Organic Compounds in Detecting Insulin Resistance Among Taiwanese Women.Diagnostics (Basel, Switzerland) · 2025Article
- Innovative Approaches to Early Detection of Cancer-Transforming Screening for Breast, Lung, and Hard-to-Screen Cancers.Cancers · 2025Review
- Optimizing non small cell lung cancer detection with convolutional neural networks and differential augmentation.Scientific reports · 2025Article
- Volatile Organic Compounds in Biological Matrices as a Sensitive Weapon in Cancer Diagnosis.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Recent Advances in SAW Sensors for Detection of Cancer Biomarkers.Biosensors · 2025Review
- Development of Electronic Nose as a Complementary Screening Tool for Breath Testing in Colorectal Cancer.Biosensors · 2025Article
- Linking volatile metabolites from bacterial pathogens to exhaled breath condensate of people with cystic fibrosis.Microbiology (Reading, England) · 2025Article
- Minimally invasive biomarkers for triaging lung nodules-challenges and future perspectives.Cancer metastasis reviews · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
(1) Background: Lung cancer is silent in its early stages and fatal in its advanced stages. The current examinations for lung cancer are usually based on imaging. Conventional chest X-rays lack accuracy, and chest computed tomography (CT) is associated with radiation exposure and cost, limiting screening effectiveness. Breathomics, a noninvasive strategy, has recently been studied extensively. Volatile organic compounds (VOCs) derived from human breath can reflect metabolic changes caused by diseases and possibly serve as biomarkers of lung cancer. (2) Methods: The selected ion flow tube mass spectrometry (SIFT-MS) technique was used to quantitatively analyze 116 VOCs in breath samples from 148 patients with histologically confirmed lung cancers and 168 healthy volunteers. We used eXtreme Gradient Boosting (XGBoost), a machine learning method, to build a model for predicting lung cancer occurrence based on quantitative VOC measurements. (3) Results: The proposed prediction model achieved better performance than other previous approaches, with an accuracy, sensitivity, specificity, and area under the curve (AUC) of 0.89, 0.82, 0.94, and 0.95, respectively. When we further adjusted the confounding effect of environmental VOCs on the relationship between participants' exhaled VOCs and lung cancer occurrence, our model was improved to reach 0.92 accuracy, 0.96 sensitivity, 0.88 specificity, and 0.98 AUC. (4) Conclusion: A quantitative VOCs databank integrated with the application of an XGBoost classifier provides a persuasive platform for lung cancer prediction.
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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.