These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Prognostic nomograms to predict overall survival and cancer-specific survival in patients with pelvic chondrosarcoma. Author: Chen L, Long C, Liu J, Duan X, Xiang Z. Journal: Cancer Med; 2019 Sep; 8(12):5438-5449. PubMed ID: 31353800. Abstract: BACKGROUND: The pelvis is the most common site of chondrosarcoma (CS), and the prognosis for patients with pelvic CS is worse than that for patients with CS in the extremities. However, clinicians have had few tools for estimating the likelihood of survival in patients with pelvic CS. Our aim was to develop nomograms to predict survival of patients with pelvic CS. METHODS: Data from the Surveillance, Epidemiology, and End Results (SEER) database of patients with pelvic CS between 2004 and 2016 were retrieved for retrospective analysis. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. On the basis of the results of the multivariate analyses, nomograms were constructed to predict the likelihood of 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) of patients with pelvic CS. The concordance index (C-index) and calibration curves were used to test the models. RESULTS: In univariate and multivariate analyses of OS, sex, pathologic grade, tumor size, tumor stage, and surgery were identified as the independent risk factors. In univariate and multivariate analyses of CSS, pathologic grade, tumor size, tumor stage, and surgery were identified as the independent risk factors. These characteristics except surgery were integrated in the nomograms for predicting 3- and 5-year OS and CSS, and the C-indexes were 0.758 and 0.786, respectively. CONCLUSION: The nomograms precisely and individually predict OS and CSS of patients with pelvic CS and could aid in personalized prognostic evaluation and individualized clinical decision-making.[Abstract] [Full Text] [Related] [New Search]