ArticleJapanese journal of radiology2020
Two nomograms based on CT features to predict tumor invasiveness of pulmonary adenocarcinoma and growth in pure GGN: a retrospective analysis.
Article in Japanese journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Development and validation of a risk prediction model for invasiveness of pure ground-glass nodules based on a systematic review and meta-analysis.BMC medical imaging · 2024Pooled it
- The long-term course of subsolid nodules and predictors of interval growth on chest CT: a systematic review and meta-analysis.European radiology · 2023Pooled it
- A predictive nomogram for two-year growth of CT-indeterminate small pulmonary nodules.European radiology · 2022Trial
- A narrative review on CT-based evaluation and prediction of lung nodule growth: current status and future directions.Translational lung cancer research · 2026Review
- East-West Disparities in Lung Cancer Screening: Subsolid Nodule Prevalence, Interval Growth, and Decision-Making Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Machine Learning Model for Predicting Pathological Invasiveness of Pulmonary Ground-Glass Nodules Based on AI-Extracted Radiomic Features.Thoracic cancer · 2025Article
- Artificial intelligence-based graded training of pulmonary nodules for junior radiology residents and medical imaging students.BMC medical education · 2024Article
- Diagnostic Efficacy of CT Radiomic Features in Pulmonary Invasive Mucinous Adenocarcinoma.Scanning · 2022Article
- Multivariate Analysis on Development of Lung Adenocarcinoma Lesion from Solitary Pulmonary Nodule.Contrast media & molecular imaging · 2022Article
- Development and Validation of a Preoperative CT-Based Nomogram to Differentiate Invasive from Non-Invasive Pulmonary Adenocarcinoma in Solitary Pulmonary Nodules.Cancer management and research · 2022Article
- Invasive adenocarcinoma manifesting as pure ground glass nodule with different size: radiological characteristics differ while prognosis remains the same.Translational cancer research · 2021Article
- Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact.Cancer imaging : the official publication of the International Cancer Imaging Society · 2021Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of the study is to construct two nomograms for predicting the invasive extent of pulmonary adenocarcinoma and nodule growth in patients with pulmonary pure ground-glass nodules (pGGN).
methodConsecutive patients with pGGNs (n = 172) were retrospectively studied at one institution, formed the development cohort in predicting IPAs' nomogram. A separate cohort of patients with pGGNs (n = 116) from another institution was used for validation. For the predicting growth nomogram, the primary cohort of patients with pGGNs (n = 80) was from the former institution. We developed the nomogram for predicting IPA using binary logistic regression model, and a Cox multivariable model for the growth nomogram. We assessed nomogram model performance by calibration and discrimination (C-index).
resultsThe variables selected in binary logistic regression model (lesion size and shape) had a significant effect on identifying IPA from preinvasive lesion. The C-index of the development and validation cohort were 0.819 (95% CI 0.753-0.874) and 0.811 (95% CI 0.728-0.878), respectively. The risk variables (lesion size, blood vessel types) were selected in the multivariable Cox model. The C-index was 0.880 in the development cohort.
conclusionOur nomograms are reliable prognostic methods that can predict the invasiveness of pulmonary adenocarcinomas and the growth of pure GGN in preoperative.
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