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Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis.
Li, Zhehong; Wei, Junqiang; Gan, Xintian; Song, Mingze; Zhang, Yafang; Cao, Haiying; Jin, Yu; Yang, Jilong.
Afiliación
  • Li Z; Postgraduate Medical School, Chengde Medical College, Chengde, China.
  • Wei J; Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
  • Gan X; National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
  • Song M; Department of Orthopedics, Affiliated Hospital of Chengde Medical College, Chengde, China.
  • Zhang Y; Postgraduate Medical School, Chengde Medical College, Chengde, China.
  • Cao H; Postgraduate Medical School, Chengde Medical College, Chengde, China.
  • Jin Y; Postgraduate Medical School, Chengde Medical College, Chengde, China.
  • Yang J; Department of Orthopedics, Affiliated Hospital of Chengde Medical College, Chengde, China.
J Thorac Dis ; 13(5): 3076-3092, 2021 May.
Article en En | MEDLINE | ID: mdl-34164199
BACKGROUND: This 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). METHOD: Patients 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. RESULTS: Two 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/). CONCLUSION: The 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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Thorac Dis Año: 2021 Tipo del documento: Article País de afiliación: China Pais de publicación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Thorac Dis Año: 2021 Tipo del documento: Article País de afiliación: China Pais de publicación: China