ArticleJournal of thoracic disease2020
The combined nomogram based on the CT features may be used as a complementary method of frozen sections to predict invasive lung adenocarcinoma manifesting as ground-glass nodules.
Article in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- CT imaging features of lung ground-glass nodule patients with upgraded intraoperative frozen pathology.Discover oncology · 2024Article
- Adding predictive and diagnostic values of pulmonary ground-glass nodules on lung cancerFrontiers in medicine · 2022Review
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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
backgroundFrozen sections (FS) deferral sometimes occurs in the intraoperative pathological classification of early lung adenocarcinoma, which is not conducive to the decision-making of surgical treatment. Here, we compared the predictive performance of the combined nomogram based on the computer tomography (CT) features with FS to investigate whether the nomogram could be used as a complementary method for FS when FS deferral occurs to predict invasive adenocarcinoma (IAC) manifesting as ground-glass nodules (GGNs) during surgery.
methodsIn this study, 205 early lung adenocarcinomas manifesting as GGNs from 178 patients who had undergone surgical treatment were included and divided into a training set (n=123) and a validation set (n=82). The training set defined a hybrid nomogram incorporating CT features and intraoperative measured tumor size based on multivariate logistic regression to predict IAC, and the validation set was used to verified the predictive performance. We also collected the diagnostic results of FS and compared the predictive performance of the established nomogram with FS.
resultsThe accuracy of combined nomogram in predicting IAC in the training and validation sets was 91.1% and 89.0%, respectively, and the predictive accuracy of FS in the training set and validation set was 87.0% and 86.6%, respectively. The predictive accuracy between the combined nomogram and FS have no significant difference.
conclusionsCompared with FS, the performance of the combined nomogram in predicting the lung IAC manifesting as GGNs is satisfactory, which has the potential to be used as a complementary method for FS when FS deferrals during surgery.
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