ArticleOncotarget2017
A novel nomogram based on LODDS to predict the prognosis of epithelial ovarian cancer.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Prognostic Factors and a Predictive Nomogram of Cancer-Specific Survival of Epithelial Ovarian Cancer Patients with Pelvic Exenteration Treatment.International journal of clinical practice · 2023Trial
- Association between log odds of positive lymph nodes and survival in surgically treated cervical cancer patients: a SEER database-based cohort study.World journal of surgical oncology · 2026Article
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- Speculation on optimal numbers of examined lymph node for early-stage epithelial ovarian cancer from the perspective of stage migration.Frontiers in oncology · 2023Article
- Lymphadenectomy Benefits Small Cell Carcinoma of Ovary: A Population-Based Analysis.Current oncology (Toronto, Ont.) · 2022Article
- Development and External Validation of a Novel Model for Predicting Postsurgical Recurrence and Overall Survival After Cytoreductive R0 Resection of Epithelial Ovarian Cancer.Frontiers in oncology · 2022Article
- A Nomogram Based on SEER Database for Predicting Prognosis in Patients with Mucinous Ovarian Cancer: A Real-World Study.International journal of women's health · 2022Article
- Development and Validation of Nomograms to Predict Overall Survival Outcomes in Serous Ovarian Cancer Patients with Satisfactory Cytoreductive Surgery and Chemotherapy.International journal of general medicine · 2022Article
- A prognostic system for epithelial ovarian carcinomas using machine learning.Acta obstetricia et gynecologica Scandinavica · 2021Article
- Association of Copy Number Variation Signature and Survival in Patients With Serous Ovarian Cancer.JAMA network open · 2021Article
- Nomogram Based on Log Odds of Positive Lymph Nodes Predicting Cancer-Specific Survival in Patients With T3 and T4 Gallbladder Cancer After Radical Resection.Frontiers in surgery · 2021Article
- The individualized significance of lymphadenectomy across all age groups and histologies in malignant ovarian germ cell tumors.Archives of gynecology and obstetrics · 2020Article
- A prognosis-predictive nomogram of ovarian cancer with two immune-related genes:Oncology letters · 2020Article
- Nomograms for predicting overall and cancer-specific survival in patients with papillary renal cell carcinoma: a population-based study using SEER database.Translational andrology and urology · 2020Article
- Survival Analysis of Lymph Node Resection in Ovarian Cancer: A Population-Based Study.Frontiers in oncology · 2020Article
- A Novel Diagnostic Nomogram for Noninvasive Evaluating Liver Fibrosis in Patients with Chronic Hepatitis B Virus Infection.BioMed research international · 2020Article
- Nomogram for predicting the survival of patients with malignant melanoma: A population analysis.Oncology letters · 2019Article
- Immunohistochemical Characterization Improves the Reproducibility of the Histological Diagnosis of Ovarian CarcinomaAsian Pacific journal of cancer prevention : APJCP · 2018Article
- Survival effect of different lymph node staging methods on ovarian cancer: An analysis of 10 878 patients.Cancer medicine · 2018Article
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Authors and funding
16 authors.
Funding
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Abstract
backgroundTo develop and validate a nomogram based on log of odds between the number of positive lymph node and the number of negative lymph node (LODDS) in predicting the overall survival (OS) and cancer specific survival (CSS) for epithelial ovarian cancer (EOC) patients. MATERIALS AND
methodsA total of 10,692 post-operative EOC patients diagnosed between 2004 and 2013 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training (n = 7,021) and validation (n = 3,671) cohorts. Multiple clinical pathological parameters were assessed and compared with outcomes. Parameters significantly correlating with outcomes were used to build a nomogram. Bootstrap validation was subsequently used to assess the predictive value of the model.
resultsIn the training set, age at diagnosis, race, marital status, tumor location, stage, grade and LODDS were correlated significantly with outcome in both the univariate and multivariate analyses and were used to develop a nomogram. The nomogram demonstrated good accuracy in predicting OS and CSS, with a bootstrap-corrected concordance index of 0.757 (95% CI, 0.746-0.768) for OS and 0.770 (95% CI, 0.759-0.782) for CSS. Notably, in this population our model performed favorably compared to the currently utilized Federation of Gynecology and Obstetrics (FIGO) model, with concordance indices of 0.699 (95% CI, 0.688-0.710, P < 0.05) and 0.719 (95% CI, 0.709- 0.730, P < 0.05) for OS and CSS, respectively. Using our nomogram in the validation cohort, the C-indices were 0.757 (95% CI, 0.741-0.773, P < 0.05, compared to FIGO) for OS and 0.762 (95% CI, 0.746-0.779, P < 0.05, compared to FIGO) for CSS.
conclusionsLODDS works as an independent prognostic factor for predicting survival in patients with EOC regardless of the tumor stage. By incorporating LODDS, our nomogram may be superior to the currently utilized FIGO staging system in predicting OS and CSS among post-operative EOC patients.
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