ArticleRespiratory research2024
Development of a nomogram based on the clinicopathological and CT features to predict the survival of primary pulmonary lymphoepithelial carcinoma patients.
Article in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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1 citing paper in PubMed, 1 citations in OpenAlex.
- Case report: pulmonary lymphoepithelial carcinoma mimicking tuberculosis.BMC pulmonary medicine · 2025Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThe aim of this study was to develop a nomogram by combining chest computed tomography (CT) images and clinicopathological predictors to assess the survival outcomes of patients with primary pulmonary lymphoepithelial carcinoma (PLEC).
methods113 patients with stage I-IV primary PLEC who underwent treatment were retrospectively reviewed. The Cox regression analysis was performed to determine the independent prognostic factors associated with patient's disease-free survival (DFS) and cancer-specific survival (CSS). Based on results from multivariate Cox regression analysis, the nomograms were constructed with pre-treatment CT features and clinicopathological information, which were then assessed with respect to calibration, discrimination and clinical usefulness.
resultsMultivariate Cox regression analysis revealed the independent prognostic factors for DFS were surgery resection and hilar and/or mediastinal lymphadenopathy, and that for CSS were age, smoking status, surgery resection, tumor site in lobe and necrosis. The concordance index (C‑index) of nomogram for DFS and CSS were 0.777 (95% CI: 0.703-0.851) and 0.904 (95% CI: 0.847-0.961), respectively. The results of the time‑dependent C‑index were internally validated using a bootstrap resampling method for DFS and CSS also showed that the nomograms had a better discriminative ability.
conclusionsWe developed nomograms based on clinicopathological and CT factors showing a good performance in predicting individual DFS and CSS probability among primary PLEC patients. This prognostic tool may be valuable for clinicians to more accurately drive treatment decisions and individualized survival assessment.
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