ArticleCancer medicine2022
Serum tumor markers level and their predictive values for solid and micropapillary components in lung adenocarcinoma.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 16 citations in OpenAlex.
- Multiple machine learning algorithms construct cuproptosis genes and oxidative stress genes-related LncRNAs signature with prognostic and therapeutic relevance in ovarian cancer.Genes & genomics · 2026Article
- Novel insights into predicting the presence of micropapillary and solid components in stage IA lung adenocarcinoma using machine learning models of modifiable risk factors.Annals of medicine · 2025Article
- A Clinical-Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma.Current oncology (Toronto, Ont.) · 2025Article
- Article
- Prognostic implications of tumor volume reduction during radiotherapy in locally advanced cervical cancer: a risk-stratified analysis.Radiation oncology (London, England) · 2025Article
- Tumor marker-based RecistTM is superior to RECIST as criteria to predict the long-term benefits of targeted therapy in advanced non-small-cell lung cancer with driver gene mutations.Neoplasia (New York, N.Y.) · 2024Article
- The diagnostic potential role of thioredoxin reductase and TXNRD1 in early lung adenocarcinoma: A cohort study.Heliyon · 2024Article
- Evaluation of the preoperative neutrophil-to-lymphocyte ratio as a predictor of the micropapillary component of stage IA lung adenocarcinoma.The Journal of international medical research · 2024Article
- The value of intratumoral and peritumoral radiomics features in differentiating early-stage lung invasive adenocarcinoma (≤3 cm) subtypes.Translational cancer research · 2024Article
- A pretreatment prediction model of grade 3 tumors classed by the IASLC grading system in lung adenocarcinoma.BMC pulmonary medicine · 2023Article
- Construction of IL-1 signalling pathway correlation model in lung adenocarcinoma and association with immune microenvironment prognosis and immunotherapy: Multi-data validation.Frontiers in immunology · 2023Article
- Serum tumor markers level and their predictive values for solid and micropapillary components in lung adenocarcinoma.Cancer medicine · 2022Article
- A Novel Secreted Protein-Related Gene Signature Predicts Overall Survival and Is Associated With Tumor Immunity in Patients With Lung Adenocarcinoma.Frontiers in oncology · 2022Article
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aims to reveal the serum tumor marker (STM) levels in lung adenocarcinoma (LUAD) histological subtypes and evaluate their values in predicting the solid and micropapillary components (SMC).
methodsWe retrospectively analyzed 3100 invasive LUAD patients between January 2017 and December 2020. Associations between preoperative STMs (CEA, CYFRA21-1, CA199, CA724, NSE, AFP) and LUAD subtypes were evaluated. Multivariate regression analyses were used to determine the independent predictors. Predictive models for SMC were constructed and AUC (area under the curve) was calculated.
resultsCEA and CYFRA21-1 levels differed across the LUAD histological subtypes, with the SPA (solid-predominant adenocarcinoma) having the highest level and the LPA (lepidic-predominant adenocarcinoma) harboring the lowest level (p <0.001). Tumors with SMC also had higher CEA and CYFRA21-1 levels than those absence of SMC. Gender, tumor size, CEA, Ki-67, EGFR mutation (solid components only), and tumor differentiation were significantly independently associated with the containing of SMC. Patients were split into two data sets (training set: 2017-2019 and validation set: 2020). The model with gender and tumor size yielded an AUC of 0.723 (training set) and 0.704 (validation set) for the solid component. Combination of CEA, gender, and tumor size led to a significant increase in the predictive accuracy (training set: 0.771, p = 0.009; validation set: 0.747, p = 0.034). The AUC of the model for micropapillary component with only gender and tumor size was 0.699 and 0.711 in the training set and validation set, respectively. Integration of CEA with gender and tumor size significantly improved the predictive performance with an AUC of 0.746 (training set, p = 0.045) and 0.753 (validation set, p <0.001).
conclusionSerum CEA and CYFRA21-1 varied considerably according to LUAD histological subtypes. The combination of serum CEA and other factors showed prominent values in predicting the SMC.
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