NDLI: Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study

Content Provider	Springer Nature : BioMed Central
Author	Song, Zixuan Wang, Yizi Zhou, Yangzi Zhang, Dandan
Abstract	Background Malignant ovarian germ cell tumors (MOGCTs) are rare gynecologic neoplasms. The use of nomograms that are based on various clinical indicators to predict the prognosis of MOGCTs are currently lacking. Methods Clinical and demographic information of patients with MOGCT recorded between 2004 and 2015 were obtained from the Surveillance, Epidemiology, and End Results database, and Cox regression analysis was performed to screen for important independent prognostic factors. Prognostic factors were used to construct predictive calculational charts for 1-year, 3-year, and 5-year overall survival (OS). The externally validated case cohort included a total of 121 MOGCT patients whose data were recorded from 2008 to 2019 from the database of the Shengjing Hospital of China Medical University. Results A total of 1401 patients with MOGCT were recruited for the study. A nomogram was used to forecast the 1-year, 3-year, and 5-year OS using data pertaining to age, International Federation of Gynecology and Obstetrics (FIGO) staging, histological subtype and grade, and surgical type. Nomograms have a more accurate predictive ability and clinical utility than FIGO staging alone. Internal and external validation also demonstrated satisfactory consistency between projected and actual OS. Conclusions A nomogram constructed using multiple clinical indicators provided a more accurate prognosis than FIGO staging alone. This nomogram may assist clinicians in identifying patients who are at increased risk, thus implementing individualized treatment regimens.
Related Links	https://bmccancer.biomedcentral.com/counter/pdf/10.1186/s12885-022-09324-7.pdf
Ending Page	11
Page Count	11
Starting Page	1
File Format	HTM / HTML
ISSN	14712407
DOI	10.1186/s12885-022-09324-7
Journal	BMC Cancer
Issue Number	1
Volume Number	22
Language	English
Publisher	BioMed Central
Publisher Date	2022-03-10
Access Restriction	Open
Subject Keyword	Cancer Research Oncology Surgical Oncology Health Promotion and Disease Prevention Biomedicine Medicine Public Health Malignant ovarian germ cell tumor Nomograms SEER database Prognosis Overall survival Medicine/Public Health
Content Type	Text
Resource Type	Article
Subject	Cancer Research Oncology Genetics
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	3.8/2023

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