ArticleBMC pulmonary medicine2022
An individual nomogram can reliably predict tumor spread through air spaces in non-small-cell lung cancer.
Article in BMC pulmonary medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 11 citations in OpenAlex.
- Machine learning-based preoperative prediction of spread through air spaces in clinical stage IA non-small cell lung cancer: a single-center study integrating clinical and CT imaging characteristics.Journal of thoracic disease · 2026Article
- The clinicoradiological and pathological-molecular characteristics associated with spread through air spaces in stage IA invasive lung adenocarcinoma.Insights into imaging · 2026Article
- STAS More than a Prognostic Marker-An Evolving Factor in Operative and Adjuvant Treatment Decisions in Early-Stage NSCLC.Cancers · 2026Review
- Development and internal validation of predictive models for spread through air spaces in clinical stage IA lung adenocarcinoma.General thoracic and cardiovascular surgery · 2025Article
- Lobar versus sub-lobar resection for clinical stage IA (≤ 2 cm) lung neuroendocrine tumor with spread through air spaces: a multi-center study.Updates in surgery · 2025Article
- Multidisciplinary Perspective of Spread Through Air Spaces in Lung Cancer: A Narrative Review.Cancers · 2025Review
- STAS: New explorations and challenges for thoracic surgeons.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- Spatial deciphering of the transcriptomic heterogeneity of tumor spread through air spaces in lung cancer.Frontiers in pharmacology · 2025Article
- Deep learning-based detection and semi-quantitative model for spread through air spaces (STAS) in lung adenocarcinoma.NPJ precision oncology · 2024Article
- Predictive value of multiple imaging predictive models for spread through air spaces of lung adenocarcinoma: A systematic review and network meta‑analysis.Oncology letters · 2024Article
- Preoperative CT radiomic model combined with clinical and CT imaging features to predict the spread through air spaces in T1 invasive lung adenocarcinoma.American journal of translational research · 2024Article
- An individualized nomogram for predicting and validating spread through air space (STAS) in surgically resected lung adenocarcinoma: a single center retrospective analysis.Journal of cardiothoracic surgery · 2023Article
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumor spread through air spaces (STAS) has been shown to adversely affect the prognosis of lung cancer. The correlation between clinicopathological and genetic features and STAS remains unclear.
methodWe retrospectively reviewed 3075 NSCLC patients between2017-2019. We evaluated the relationship between STAS and patients' clinicopathological and molecular features. The chi-square test was performed to compare categorical variables. Univariate analysis and multivariate logistic regression analysis were performed to investigate the association of clinical factors with STAS. A nomogram was formulated to predict the presence of STAS.
resultsSTAS was identified in 617 of 3075 patients (20.07%). STAS was significantly related to sex (p < 0.001), smoking (p < 0.001), CEA (p < 0.001), differentiation (p < 0.001), histopathological type (p < 0.001), lymphatic vessel invasion (p < 0.001), pleural invasion (p < 0.001), T stage (p < 0.001), N stage (p < 0.001), M stage (p < 0.001), and TNM stage (p < 0.001). STAS was frequently found in tumors with wild-type EGFR (p < 0.001), KRAS mutations (p < 0.001), ALK rearrangements (p < 0.001) or ROS1 rearrangements (p < 0.001). For programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1), STAS was associated with PD-L1 expression level in tumor cells (p < 0.001) or stromal cells (p < 0.001), while PD-1 only in stromal cells (p < 0.001). Multivariable analyses demonstrated significant correlations between STAS and CEA level (p < 0.001), pathological grade (p < 0.001), lymphatic vessel invasion (p < 0.001), pleural invasion (p = 0.001), and TNM stage (p = 0.002). A nomogram was formulated based on the results of the multivariable analysis.
conclusionsTumor STAS was associated with several invasive clinicopathological features. A nomogram was established to predict the presence of STAS in patients with NSCLC.
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