ArticleTranslational cancer research2020
Development of a nomogram to predict prognosis in ovarian cancer: a SEER-based study.
Article in Translational cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- The development and validation of a tumor-specific death predictive nomogram in patients with ovarian cancer: a cohort study.Gland surgery · 2025Article
- A Prognostic Nomogram Based on an Immunogenic Cell Death and Endoplasmic Reticulum Stress-Related Gene Signature for Ovarian Cancer.International journal of women's health · 2025Article
- Predicting Survival Outcomes for Patients with Ovarian Cancer Using National Cancer Registry Data from Taiwan: A Retrospective Cohort Study.Women's health reports (New Rochelle, N.Y.) · 2025Article
- Nomogram for predicting the early death of patients with stage IV ovarian cancer: a retrospective analysis of the SEER database.Translational cancer research · 2024Article
- Nomogram predicting the prognosis of primary liver cancer after radiofrequency ablation combined with transcatheter arterial chemoembolization.World journal of gastrointestinal surgery · 2024Article
- Predict value of tumor markers combined with interleukins for therapeutic efficacy and prognosis in ovarian cancer patients.American journal of cancer research · 2024Article
- Article
- Modified HE4, CA125, and ROMA cut-off values and predicted probability of ovarian tumor in Chinese patients.Gland surgery · 2021Article
- Identification of solute-carrier family 27A molecules (SCL27As) as a potential biomarker of ovarian cancer based on bioinformatics and experiments.Annals of translational medicine · 2021Article
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6 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundOvarian 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.
methodsInformation 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.
resultsA 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).
conclusionsWe developed a nomogram valuable for accurate prediction of 3- and 5-year OS rates of ovarian cancer patients based on individual characteristics.
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