ArticlePloS one2017
An integrated risk predictor for pulmonary nodules.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01752101 (Identification of a Plasma Proteomic Signature for Lung Cancer), which is not on this map. Cited by 12 papers.
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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.
Identification of a Plasma Proteomic Signature for Lung Cancer
Who cites it
12 citing papers in PubMed.
- Biomarkers in lung cancer diagnosis and bronchoscopy: Current landscape and future directions.Cancer biomarkers : section A of Disease markers · 2025Review
- Impact of an integrated classifier using biomarkers, clinical and imaging factors on clinical decisions making for lung nodules.Journal of thoracic disease · 2023Article
- Assessing a biomarker's ability to reduce invasive procedures in patients with benign lung nodules: Results from the ORACLE study.PloS one · 2023Observational
- Article
- Lung cancer screening by volume computed tomography: thriving to high performance.Breathe (Sheffield, England) · 2021Article
- The Liquid Biopsy for Lung Cancer: State of the Art, Limitations and Future Developments.Cancers · 2021Review
- Biomarkers for Lung Cancer Screening and Detection.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Noninvasive biomarkers for lung cancer diagnosis, where do we stand?Journal of thoracic disease · 2020Review
- Management of incidental nodules in lung cancer screening: ready for prime-time?Breathe (Sheffield, England) · 2019Article
- Extending the information content of the MALDI analysis of biological fluids via multi-million shot analysis.PloS one · 2019Article
- Observational
- Blood based biomarkers beyond genomics for lung cancer screening.Translational lung cancer research · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is estimated that over 1.5 million lung nodules are detected annually in the United States. Most of these are benign but frequently undergo invasive and costly procedures to rule out malignancy. A risk predictor that can accurately differentiate benign and malignant lung nodules could be used to more efficiently route benign lung nodules to non-invasive observation by CT surveillance and route malignant lung nodules to invasive procedures. The majority of risk predictors developed to date are based exclusively on clinical risk factors, imaging technology or molecular markers. Assessed here are the relative performances of previously reported clinical risk factors and proteomic molecular markers for assessing cancer risk in lung nodules. From this analysis an integrated model incorporating clinical risk factors and proteomic molecular markers is developed and its performance assessed on a subset of 222 lung nodules, between 8mm and 20mm in diameter, collected in a previously reported prospective study. In this analysis it is found that the molecular marker is most predictive. However, the integration of clinical and molecular markers is superior to both clinical and molecular markers separately. CLINICAL
trial registrationRegistered at ClinicalTrials.gov (NCT01752101).
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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.