ArticleTranslational lung cancer research2024
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.
Article in Translational lung cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of Radiomics-Based Machine Learning for Predicting Risk of Recurrence in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Prognostic stratification of T1 lung adenocarcinoma with micropapillary or solid patterns: a cohort study.Journal of thoracic disease · 2026Article
- Genomic profiles and prognostic biomarkers of resectable lung adenocarcinoma with a micropapillary component.Frontiers in oncology · 2025Article
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9 authors.
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Abstract
Background: Patients with stage IA lung adenocarcinoma (ADC) with an micropapillary (MIP) component are at a higher risk of recurrence after radical surgical resection; however, adding adjuvant chemotherapy (ACT) to their postoperative course remains controversial. This study determined the predictive factors that influence the prognosis of these patients and identified those at high risk of recurrence. Methods: Between January 2012 and December 2018, 254 eligible patients with stage IA lung ADC with an MIP component were categorized into training (n=169) and validation (n=85) cohorts. Clinicopathological and radiomics features were included in univariate and multivariate analyses, and statistically significant predictors were used to develop the nomogram. Area under the curve (AUC) of receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to validate the model. The calculated risk scores for each patient were risk-stratified using the X-tile procedure, and survival analyses were performed among the different risk subgroups. Results: T1c stage, MIP ≥1%, spread through air space (STAS), carcinoembryonic antigen (CEA) >5 µg/L, and radiomics features were independent predictors of overall survival (OS) and disease-free survival (DFS) in patients with lung ADC with an MIP component at stage IA. Incorporating this into the nomogram, the AUCs of the nomogram predicting 3-, 5-, and 7-year OS and DFS were 0.910, 0.914, and 0.904 and 0.868, 0.838, and 0.848, respectively, in the training cohort and 0.879, 0.895, and 0.899 and 0.817, 0.805, and 0.811, respectively, in the validation cohort, showing good differentiation. The OS and DFS survival analyses among different risk subgroups showed that the nomogram could well distinguish between low- and high-risk groups. Conclusions: We developed and validated a nomogram based on clinicopathological factors and radiomics features, which can be used as a powerful tool for predicting postoperative recurrence and survival in patients with stage IA lung ADC containing an MIP component.
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