Development of a Nomogram to Predict Prognosis in Ovarian Cancer: a SEER-based Study

Overview

Journal Transl Cancer Res

Specialty Oncology

Date 2022 Feb 4

PMID 35117197

Authors

Huizhen Sun

Li Yan

Hainan Chen

Tao Zheng

Yi Zhang

Husheng Wang

Affiliations

Soon will be listed here.

Abstract

Background: Ovarian cancer remains the most lethal gynecologic malignancy. In this study, we aimed to identify the specific risk factors affecting overall survival (OS) and develop a nomogram for prognostic prediction of ovarian cancer patients based on data from the Surveillance, Epidemiology, and End Results (SEER) database.

Methods: Information from the SEER database on ovarian cancer between 2004 and 2016 was screened and retrieved. Cases were randomly divided into the training cohort hand the validation cohort at a 7:3 ratio. The prognostic effects of individual variables on survival were evaluated via Kaplan-Meier method and Cox proportional hazards regression model using data from the training cohort. A nomogram was formulated to predict the 3- and 5-year OS rates of patients with ovarian cancer, and then validated both in the training cohort and the validation cohort.

Results: A total of 28,375 patients were selected from 75,921 samples (19,862 in training cohort and 8,513 in validation cohort). Cox regression analysis identified race, age laterality, histology, stage, grade, surgery, chemotherapy, radiotherapy, and marital status as independent risk factors for ovarian cancer prognosis. A nomogram was developed based on the results of multivariate analysis and validated using an internal bootstrap resampling approach, which demonstrated a sufficient level of discrimination according to the C-index (0.752, 95% CI: 0.746-0.758 in the training cohort, 0.755, 95% CI: 0.746-0.764).

Conclusions: We developed a nomogram valuable for accurate prediction of 3- and 5-year OS rates of ovarian cancer patients based on individual characteristics.

Citing Articles

Predicting Survival Outcomes for Patients with Ovarian Cancer Using National Cancer Registry Data from Taiwan: A Retrospective Cohort Study.

Chattopadhyay A, Wu Y, Chan H, Kang Y, Chiang Y, Chiang C Womens Health Rep (New Rochelle). 2025; 6(1):90-101.

PMID: 39882147 PMC: 11773178. DOI: 10.1089/whr.2024.0166.

Nomogram for predicting the early death of patients with stage IV ovarian cancer: a retrospective analysis of the SEER database.

Chen P, Zheng S, Zhang L Transl Cancer Res. 2024; 13(11):5845-5855.

PMID: 39697763 PMC: 11651799. DOI: 10.21037/tcr-24-625.

Predict value of tumor markers combined with interleukins for therapeutic efficacy and prognosis in ovarian cancer patients.

Cheng F, Ma X, Cheng Z, Wang Y, Zhang X, Ma C Am J Cancer Res. 2024; 14(10):4868-4879.

PMID: 39553206 PMC: 11560821. DOI: 10.62347/GSRD2580.

Nomogram predicting the prognosis of primary liver cancer after radiofrequency ablation combined with transcatheter arterial chemoembolization.

Shen H, Hong Y, Xu W, Chen L, Chen J, Yang Z World J Gastrointest Surg. 2024; 16(8):2630-2639.

PMID: 39220054 PMC: 11362921. DOI: 10.4240/wjgs.v16.i8.2630.

silencing inhibits ovarian carcinoma progression and oncogenic activity and .

Guo W, Sun Z, Zhao N, Zhou Y, Ren J, Huang L Ann Transl Med. 2022; 9(22):1669.

PMID: 34988178 PMC: 8667152. DOI: 10.21037/atm-21-5435.

References

Maringe C, Walters S, Butler J, Coleman M, Hacker N, Hanna L . Stage at diagnosis and ovarian cancer survival: evidence from the International Cancer Benchmarking Partnership. Gynecol Oncol. 2012; 127(1):75-82. DOI: 10.1016/j.ygyno.2012.06.033. View

Balachandran V, Gonen M, Smith J, DeMatteo R . Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015; 16(4):e173-80. PMC: 4465353. DOI: 10.1016/S1470-2045(14)71116-7. View

Jung J, Shih I, Park J, Gerry E, Kim T, Ayhan A . Ovarian Cancer Chemoresistance Relies on the Stem Cell Reprogramming Factor PBX1. Cancer Res. 2016; 76(21):6351-6361. PMC: 7375390. DOI: 10.1158/0008-5472.CAN-16-0980. View

Siegel R, Miller K, Jemal A . Cancer statistics, 2020. CA Cancer J Clin. 2020; 70(1):7-30. DOI: 10.3322/caac.21590. View

Lim W, Ryu S, Bazer F, Kim S, Song G . Chrysin attenuates progression of ovarian cancer cells by regulating signaling cascades and mitochondrial dysfunction. J Cell Physiol. 2017; 233(4):3129-3140. DOI: 10.1002/jcp.26150. View

Rosen D, Yang G, Liu G, Mercado-Uribe I, Chang B, Xiao X . Ovarian cancer: pathology, biology, and disease models. Front Biosci (Landmark Ed). 2009; 14(6):2089-102. PMC: 2858969. DOI: 10.2741/3364. View

Zhan C, Yang X, Song X, Yan L . Radiotherapy vs surgery for T1-2N0M0 laryngeal squamous cell carcinoma: A population-based and propensity score matching study. Cancer Med. 2018; 7(7):2837-2847. PMC: 6051150. DOI: 10.1002/cam4.1525. View

Wen J, Ye F, He X, Li S, Huang X, Xiao X . Development and validation of a prognostic nomogram based on the log odds of positive lymph nodes (LODDS) for breast cancer. Oncotarget. 2016; 7(15):21046-53. PMC: 4991511. DOI: 10.18632/oncotarget.8091. View

Khan H, Gabbidon K, Saxena A, Abdool-Ghany F, Dodge 3rd J, Lenzmeier T . Disparities in Cervical Cancer Characteristics and Survival Between White Hispanics and White Non-Hispanic Women. J Womens Health (Larchmt). 2016; 25(10):1052-1058. DOI: 10.1089/jwh.2015.5585. View

10.

Iasonos A, Schrag D, Raj G, Panageas K . How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008; 26(8):1364-70. DOI: 10.1200/JCO.2007.12.9791. View

11.

Wang F, Zhang H, Wen J, Zhou J, Liu Y, Cheng B . Nomograms forecasting long-term overall and cancer-specific survival of patients with oral squamous cell carcinoma. Cancer Med. 2018; 7(4):943-952. PMC: 5911576. DOI: 10.1002/cam4.1216. View

12.

Wang L, Wilson S, Stewart D, Hollenbeak C . Marital status and colon cancer outcomes in US Surveillance, Epidemiology and End Results registries: does marriage affect cancer survival by gender and stage?. Cancer Epidemiol. 2011; 35(5):417-22. DOI: 10.1016/j.canep.2011.02.004. View

13.

Shan W, Liu J . Epithelial ovarian cancer: focus on genetics and animal models. Cell Cycle. 2009; 8(5):731-5. DOI: 10.4161/cc.8.5.7848. View

14.

Liang W, He J, Shen Y, Shen J, He Q, Zhang J . Impact of Examined Lymph Node Count on Precise Staging and Long-Term Survival of Resected Non-Small-Cell Lung Cancer: A Population Study of the US SEER Database and a Chinese Multi-Institutional Registry. J Clin Oncol. 2016; 35(11):1162-1170. PMC: 5455598. DOI: 10.1200/JCO.2016.67.5140. View

15.

Wang S, Ma K, Chen Z, Yang X, Sun F, Jin Y . A Nomogram to Predict Prognosis in Malignant Pleural Mesothelioma. World J Surg. 2017; 42(7):2134-2142. DOI: 10.1007/s00268-017-4424-6. View

16.

Al-Niaimi A, Ahmed M, Petersen C . Epithelial ovarian cancer. Obstet Gynecol Clin North Am. 2012; 39(2):269-83. DOI: 10.1016/j.ogc.2012.03.003. View

17.

Choi N, Chang J, Kim S, Kim H . Radiation for persistent or recurrent epithelial ovarian cancer: a need for reassessment. Radiat Oncol J. 2017; 35(2):144-152. PMC: 5518454. DOI: 10.3857/roj.2017.00213. View

18.

Lim Y, Song C, Kim J . Improved survival with postoperative radiotherapy in thymic carcinoma: A propensity-matched analysis of Surveillance, Epidemiology, and End Results (SEER) database. Lung Cancer. 2017; 108:161-167. DOI: 10.1016/j.lungcan.2017.03.020. View

19.

Feng W, Dean D, Hornicek F, Shi H, Duan Z . Exosomes promote pre-metastatic niche formation in ovarian cancer. Mol Cancer. 2019; 18(1):124. PMC: 6691526. DOI: 10.1186/s12943-019-1049-4. View

20.

Sun F, Ma K, Yang X, Li M, Shi Y, Zhan C . A nomogram to predict prognosis after surgery in early stage non-small cell lung cancer in elderly patients. Int J Surg. 2017; 42:11-16. DOI: 10.1016/j.ijsu.2017.04.024. View