Observational studyESMO open2022
Retrospective analysis of the prognostic implications of tumor spread through air spaces in lung adenocarcinoma patients treated with surgery.
Observational study in ESMO open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis.Frontiers in oncology · 2024Pooled it
- Impact of Spread Through Air Spaces on Outcomes After Uniportal VATS Resection for Lung Adenocarcinoma: A Propensity Score-Matched Analysis.Journal of personalized medicine · 2026Article
- Diffusion attention expert model for predicting and semi-automatic localizing STAS in lung cancer histopathological images.Nature communications · 2026Article
- STAS More than a Prognostic Marker-An Evolving Factor in Operative and Adjuvant Treatment Decisions in Early-Stage NSCLC.Cancers · 2026Review
- Spread Through Air Spaces in Colorectal Lung Metastases Signals Local Recurrenece and Reflects Morphologic Aggressiveness of the Primary Tumor.Pathology international · 2026Article
- CT-based intratumoral habitat and peritumoral radiomics model to predict spread through air spaces in solid lung adenocarcinoma with diameter ≤ 2 cm: a dual-center study.Frontiers in oncology · 2026Article
- A PET/CT-based 3D deep learning model for predicting spread through air spaces in stage I lung adenocarcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- A Bayesian deep learning model with consolidation-to-tumor ratio (CTR) prior revolutionizes the prediction of spread through air spaces (STAS) in stage IA lung adenocarcinoma: a large-scale diagnostic study.Translational lung cancer research · 2025Article
- Clinical implication of tumor spread through air spaces in stage IA lung adenocarcinoma: prognostic impact and association with the International Association for the Study of Lung Cancer (IASLC) grade.Translational lung cancer research · 2025Article
- Deep learning model for predicting spread through air spaces of lung adenocarcinoma based on transfer learning mechanism.Translational lung cancer research · 2025Article
- Deep learning-based detection and semi-quantitative model for spread through air spaces (STAS) in lung adenocarcinoma.NPJ precision oncology · 2024Article
- Predictors of disease recurrence after radical resection and adjuvant chemotherapy in patients with stage IIb-IIIa squamous cell lung cancer: A retrospective analysis.World journal of experimental medicine · 2024Article
- The significance of spread through air spaces in the prognostic assessment model of stage I lung adenocarcinoma and the exploration of its invasion mechanism.Journal of cancer research and clinical oncology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumor spread through air spaces (STAS) in lung adenocarcinoma is a novel mechanism of invasion. STAS has been proposed as an independent predictor of poor prognosis. The aim of this study was to evaluate the correlations between STAS status and other clinicopathologic variables and to assess the prognostic implications of STAS and the distance from the edge of the tumor to the farthest STAS in patients with resected lung adenocarcinoma. MATERIAL AND
methodsThis is a single-institution retrospective observational study. We included all patients with resected lung adenocarcinoma from January 2017 to December 2018 at La Paz University Hospital. The cut-off for the distance from the edge of the tumor to the farthest STAS was 1.5 mm and was assessed by the area under the receiver operating characteristic curve.
resultsA total of 73 patients were included. STAS was found in 52 patients (71.2%). Histological grade 3 (P = 0.035) and absence of lepidic pattern (P = 0.022) were independently associated with the presence of STAS. The median recurrence-free survival (RFS) was 48.06 months [95% confidence interval (CI) 33.58 months to not reached]. STAS-positive patients had shorter median RFS [39.23 months (95% CI 29.34-49.12 months)] than STAS-negative patients (not reached) (P = 0.04). STAS-positive patients with a distance from the edge of the tumor to the farthest STAS ≥1.5 mm had an even shorter median RFS [37.63 months (95% CI 28.14-47.11 months)]. For every 1 mm increase in distance, the risk of mortality increased by 1.26 times (P = 0.04).
conclusionsHistological grade 3 and absence of lepidic pattern were independently associated with the presence of STAS. STAS was associated with a higher risk of recurrence. The distance from the edge of the tumor to the farthest STAS also had an impact on overall survival.
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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.