ArticleJournal of thoracic disease2021
Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis.
Article in Journal of thoracic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Web-based nomograms for predicting overall survival and cancer-specific survival in retroperitoneal leiomyosarcoma: a population-based analysis.Journal of cancer research and clinical oncology · 2023Trial
- Web-based nomogram to predict postresection risk of distant metastasis in patients with leiomyosarcoma: retrospective analysis of the SEER database and a Chinese cohort.The Journal of international medical research · 2023Article
- Prognosticators and Prognostic Nomograms for Leiomyosarcoma Patients With Metastasis.Frontiers in oncology · 2022Article
- A New Nomogram for Predicting the Postoperative Overall Survival in Patients with Middle-Aged and Elderly Rectal Cancer: A Single Center Retrospective Study in Chinese Population.International journal of general medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study sought to assess the prognostic factors for leiomyosarcoma (LMS) patients with lung metastasis and construct web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS).
methodPatients diagnosed with LMS combined with lung metastasis between 2010 and 2016 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into a training set and a testing set. The X-tile analysis provides the best age and tumor size cut-off point, and changes continuous variables into categorical variables. The independent prognostic factors were determined by Cox regression analysis, and 2 nomograms were established. Receiver operating characteristic curves and calibration curves were used to evaluate the nomograms. Based on the nomograms, 2 web-based nomograms were established.
resultsTwo hundred and twenty-eight cases were included in the OS nomogram construction, and were randomly divided into a training set (n=160) and a validation set (n=68). Age, T stage, bone metastasis, surgery, chemotherapy, marital status, tumor size, and tumor site were found to be correlated with OS. One hundred and eighty-three cases were enrolled in the CSS nomogram construction, and randomly divided into a training set (n=129) and a validation set (n=54). Age, bone metastasis, surgery, chemotherapy, tumor size, and tumor site were found to be correlated with CSS. Two nomograms were established to predict OS and CSS. In the training set, the areas under the curve of the nomogram for predicting 1-, 2-, and 3-year OS were 0.783, 0.830, and 0.832, respectively, and those for predicting 1-, 2-, and 3-year CSS were 0.889, 0.777, and 0.884, respectively. Two web-based nomograms were established to predict OS (https://wenn23.shinyapps.io/lmslmosapp/), and CSS (https://wenn23.shinyapps.io/lmslmcssapp/).
conclusionThe developed web-based nomogram is a useful tool for accurately analyzing the prognosis of LMS patients with lung metastasis, and could help clinical doctors to make personalized clinical decisions.
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