ArticleBMC cancer2022
Development and validation of reassigned CEA, CYFRA21-1 and NSE-based models for lung cancer diagnosis and prognosis prediction.
Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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38 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Nanoparticle trends and hotspots in lung cancer diagnosis from 2006-2023: a bibliometric analysis.Frontiers in oncology · 2024Pooled it
- Extracellular Vesicle Protein Panel Enables Early Lung Cancer Detection in a Large Clinical Cohort.Journal of extracellular vesicles · 2025Trial
- The early diagnostic value of lung cancer autoantibodies and tumor markers in lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Clinical characteristics, treatment response, and survival outcomes in melanoma patients with cavity carcinomatosis: A retrospective analysis.International journal of cancer · 2026Article
- Development of a diagnostic model using the circulating long noncoding RNAs LINC00857 and KLHDC7B-DT in lung adenocarcinoma.Journal of thoracic disease · 2026Article
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- Machine Learning for Classification in Lung Cancer Using Routine Clinical and Laboratory Data.Annals of surgical oncology · 2026Article
- ColoLDB: a machine learning-based predictive model for colorectal cancer using routine laboratory parameters.Journal of gastrointestinal oncology · 2026Article
- Development and validation of a machine-learning-based triage model incorporating systemic inflammatory, nutritional, coagulation, and tumor marker parameters for identifying baseline distant metastasis in lung cancer.Frontiers in oncology · 2026Article
- Lactate dehydrogenase to albumin ratio as a prognostic indicator for patients with resectable non-small cell lung cancer.Annals of medicine and surgery (2012) · 2025Article
- Development and validation of a multimodal radiomics-serum biomarker model for diagnosing solid pulmonary nodules via machine learning.Journal of thoracic disease · 2025Article
- An effective and affordable blood test for lung cancer early detection using four protein markers and artificial intelligence.Translational lung cancer research · 2025Article
- Combined Serum IL-6 and CYFRA 21-1 as Potential Biomarkers for Radon-Associated Lung Cancer Risk: A Pilot Study.Biomedicines · 2025Article
- PTPRC is an immunotherapeutic predictor and serum biomarker in lung adenocarcinoma correlated with immune cell infiltration.Scientific reports · 2025Article
- Diagnostic Values of Electrochemiluminescent Detection of Urinary CYFRA21-1 and FDP and Their Combined Detection in Bladder Cancer.Cancer medicine · 2025Article
- Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical features, serum tumor marker and imaging features.Journal of cancer research and clinical oncology · 2025Article
- Prognostic factors for non-small cell lung cancer after neoadjuvant therapy and surgery: a retrospective observational study.Journal of thoracic disease · 2025Article
- Value of serum LncRNA KIF9-AS1 combined with CT signs in the diagnosis of benign and malignant early pulmonary nodules and its correlation with prognosis.Journal of cardiothoracic surgery · 2025Article
- Efficacy of three lung cancer prediction models in diagnosing benign and malignant pulmonary nodules.Translational cancer research · 2025Article
- Diagnostic accuracy of serum biomarkers MMP11 and SPP1 in non-small cell lung cancer: an analysis of sensitivity, specificity, and area under the curve.Translational lung cancer research · 2025Article
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14 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe majority of lung cancer(LC) patients are diagnosed at advanced stage with a poor prognosis. However, there is still no ideal diagnostic and prognostic prediction model for lung cancer.
methodsData of CEA, CYFRA21-1 and NSE test of patients with LC and benign lung diseases (BLDs) or healthy people from Physical Examination Center was collected. Samples were divided into three data sets as needed. Reassign three kinds of tumor markers (TMs) according to their distribution characteristics in different populations. Diagnostic and prognostic models were thus established, and independent validation was conducted with other data sets.
resultsThe diagnostic prediction model showed good discrimination ability: the area under the receiver operating characteristic curve (AUC) differentiated LC from healthy people and BLDs (diagnosed within 2 months), being 0.88 and 0.84 respectively. Meanwhile, the prognostic prediction model did great in prediction: AUC in training data set and test data set were 0.85 and 0.8 respectively.
conclusionReassigned CEA, CYFRA21-1 and NSE can effectively predict the diagnosis and prognosis of LC. Compared with the same TMs that were considered individually, this diagnostic prediction model can identify high-risk population for LC screening more accurately. The prognostic prediction model could be helpful in making more scientific treatment and follow-up plans for patients.
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