ArticleThoracic cancer2021
Significant difference in recurrence according to the proportion of high grade patterns in stage IA lung adenocarcinoma.
Article in Thoracic cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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20 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Prognostic impact of the newly revised IASLC proposed grading system for invasive lung adenocarcinoma: a systematic review and meta-analysis.World journal of surgical oncology · 2024Pooled it
- Computed Tomography-Pathology Deep Learning Model for the Precise Prediction of Recurrence in Pathological Stage IA Lung Adenocarcinoma.Annals of surgical oncology · 2026Article
- Nonlinear association between standardized uptake value (SUV) index based onQuantitative imaging in medicine and surgery · 2026Article
- Radiological, Molecular, and Pathological Factors Unite: A Model for Predicting Recurrence-Free Survival in Pathological Stage I Lung Adenocarcinoma.Thoracic cancer · 2026Article
- Advanced characterization and grading of invasive lung adenocarcinoma: integrative analysis with spectral CT andQuantitative imaging in medicine and surgery · 2026Article
- Survival risk prediction for patients with lung adenocarcinoma containing micropapillary components based on weakly supervised pathomics.Journal of thoracic disease · 2026Article
- Radiomics to understand pre-treatment tumor biology for resectable non-small cell lung cancer.Frontiers in oncology · 2026Review
- An integrated multimodal model for early prediction of high-risk recurrence phenotype indicative of poor disease-free survival in stage IA NSCLC: a multicenter study.Frontiers in immunology · 2026Article
- Expression of cancer stem cell markers and their prognostic significance in stage IIIA non-small cell lung cancer.World journal of stem cells · 2025Article
- Machine learning algorithms for predicting malignancy grades of lung adenocarcinoma and guiding treatments: CT radiomics-based comparisons.Journal of thoracic disease · 2025Article
- Application and progress of non-invasive imaging in predicting lung invasive non-mucinous adenocarcinoma under the new IASLC grading guidelines.Insights into imaging · 2025Review
- Prognostic significance using histologic subtype in stage I lung adenocarcinoma.Journal of thoracic disease · 2024Article
- Predicting prognosis in patients with stage IA lung adenocarcinoma with a micropapillary component using a nomogram based on computed tomography radiomics and clinicopathologic factors: a retrospective analysis.Translational lung cancer research · 2024Article
- Predicting pathological grade of stage I pulmonary adenocarcinoma: a CT radiomics approach.Frontiers in oncology · 2024Article
- Significance of histologic subtype size as a prognostic indicator in stage IA lung adenocarcinoma.Journal of thoracic disease · 2023Article
- Prediction of high-grade patterns of stage IA lung invasive adenocarcinoma based on high-resolution CT features: a bicentric study.European radiology · 2023Article
- Establishment and validation of nomograms for predicting survival of lung invasive adenocarcinoma based on the level of pathological differentiation: a SEER cohort-based analysis.Translational cancer research · 2023Article
- Comparison of outcomes following lobectomy, segmentectomy, and wedge resection based on pathological subtyping in patients with pN0 invasive lung adenocarcinoma ≤1 cm.Cancer medicine · 2022Article
- [A Review on Pathological High-risk Factors and Postoperative Adjuvant Chemotherapy in Stage IA Lung Adenocarcinoma].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2022Review
- Significant difference in recurrence according to the proportion of high grade patterns in stage IA lung adenocarcinoma.Thoracic cancer · 2021Article
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4 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients with early lung cancer are the best candidates for surgical resection. However, those patients with high grade patterns (micropapillary or solid) do not have a good prognosis, even if they have been diagnosed with stage I lung adenocarcinoma. A new modified grading system has been introduced and this study aimed to identify the prognostic role of the new grading system in patients with stage IA lung adenocarcinoma.
methodsPatients with pathological stage IA lung adenocarcinoma, according to the eighth TNM classification who underwent curative resection, were reviewed. The pathological data of stage IA adenocarcinoma was reviewed 1 (grade 1: lepidic predominant with no or less than 20% of high grade patterns, grade 2: acinar or papillary predominant with no or less than 20% of high grade patterns, grade 3: any tumor with 20% or more of high grade patterns). Prognostic factors were analyzed for disease-free interval (DFI) and overall survival (OS) using Cox proportional models.
resultsThe medical records of 429 patients with stage IA lung adenocarcinoma were reviewed. DFI (p < 0.001) and OS (p < 0.001) were significantly lower in patients diagnosed with grade 3 compared with grade 1 and grade 2. Multivariate analysis showed that smoking (p = 0.013), value of SUVmax (p = 0.005), lymphovascular invasion (p = 0.004) and grade 3 (p = 0.008) were significant prognostic factors for DFI.
conclusionsThe proportion of high grade patterns showed a different prognosis, even if curative resection had been performed for stage IA adenocarcinoma. This new grading system is more simple and useful in the prediction of a prognosis in patients with stage IA lung adenocarcinoma.
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