ArticleScientific reports2022
Combination of mean CT value and maximum CT value as a novel predictor of lepidic predominant lesions in small lung adenocarcinoma presenting as solid nodules.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
8 citing papers in PubMed.
- MSCT Manifestations and Quantitative Dynamic Evolution of Lung Cancer Associated with Cystic Airspaces: A Retrospective Analysis of 102 Cases with Emphasis on Adenocarcinoma.Cancer management and research · 2026Article
- Contrast-enhanced CT-based prediction models for early intervention efficacy and in-hospital mortality risk in acute necrotizing pancreatitis with persistent organ failure.European radiology · 2025Article
- A nomogram model integrating radiomics and clinical variables to predict napsin a expression in lung adenocarcinoma patients.Frontiers in oncology · 2025Article
- A clinical spectrum of resectable lung adenocarcinoma with micropapillary component (MPC) concurrently presenting as mixed ground-glass opacity nodules.Cancer biomarkers : section A of Disease markers · 2025Article
- Article
- Development and Validation of a Nomogram for Axillary Lymph Node Metastasis Risk in Breast Cancer.Journal of Cancer · 2024Article
- Effects of aging on otolith morphology and functions in mice.Frontiers in neuroscience · 2024Article
- A nomogram combining thoracic CT and tumor markers to predict the malignant grade of pulmonary nodules ≤3 cm in diameter.Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung adenocarcinomas presenting as solid nodules are occasionally diagnosed as lepidic predominant lesions. The aim of this study was to clarify the histological structure and to identify factors predictive of lepidic predominant lesions. We retrospectively reviewed 38 patients that underwent lobectomy for small (≤ 2 cm) adenocarcinoma presenting as solid nodules. Resected tumor slides were reviewed and histological components were evaluated. Clinical and radiological data were analyzed to identify factors predictive of lepidic predominant lesions. Of 38 solid nodules, 9 (23.7%) nodules were lepidic predominant lesions. Five-year disease-free survival (DFS) rates were 100% for lepidic predominant lesions (n = 9) and 74.6% for non-lepidic predominant lesions (n = 29). Mean CT values (p = 0.039) and maximum CT values (p = 0.015) were significantly lower in lepidic predominant lesions compared with non-lepidic predominant lesions. For the prediction of lepidic predominant lesions, the sensitivity and specificity of mean CT value (cutoff, - 150 HU) were 77.8% and 82.8%, respectively, and those of maximum CT value (cutoff, 320 HU) were 77.8% and 72.4%, respectively. A combination of mean and maximum CT values (cutoffs of - 150 HU and 380 HU for mean CT value and maximum CT value, respectively) more accurately predicted lepidic predominant lesions, with a sensitivity and specificity of 77.8% and 86.2%, respectively. The prognosis of lepidic predominant lesions was excellent, even for solid nodules. The combined use of mean and maximum CT values was useful for predicting lepidic predominant lesions, and may help predict prognosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.