ArticleBMC cancer2020
Establishment and verification of the nomogram that predicts the 3-year recurrence risk of epithelial ovarian carcinoma.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- A novel prognostic model based on vasculogenic mimicry in ovarian cancer.Translational cancer research · 2026Article
- Development of a Prognostic Nomogram in Epithelial Ovarian Cancer Based on KELIM: A Retrospective Study at TuDu Hospital, Vietnam.Diagnostics (Basel, Switzerland) · 2026Article
- Development and validation of a nomogram to predict recurrence in epithelial ovarian cancer using complete blood count and lipid profiles.Frontiers in oncology · 2025Article
- Development of a nomogram for predicting recurrence of epithelial ovarian cancer involving traditional Chinese medicine treatment.Frontiers in oncology · 2025Article
- Article
- Validation of a New Prognostic Score in Patients with Ovarian Adenocarcinoma.Medicina (Kaunas, Lithuania) · 2023Article
- 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
- A Nomogram Combining MRI Multisequence Radiomics and Clinical Factors for Predicting Recurrence of High-Grade Serous Ovarian Carcinoma.Journal of oncology · 2022Article
- Current status and future directions of ovarian cancer prognostic models.Journal of gynecologic oncology · 2021Article
- Nomogram for predicting the risk of bone metastasis in breast cancer: a SEER population-based study.Translational cancer research · 2020Article
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Abstract
backgroundAs we all know, patients with epithelial ovarian carcinoma have poor prognosis and high recurrence rate. It is critical and challenging to screen out the patients with high risk of recurrence. At present, there are some models predicting the overall survival of epithelial ovarian carcinoma, however, there is no widely accepted tool or applicable model predicting the recurrence risk of epithelial ovarian carcinoma patients. The objective of this study was to establish and verify a nomogram to predict the recurrence risk of EOC.
methodsWe reviewed the clinicopathological and prognostic data of 193 patients with EOC who achieved clinical complete remission after cytoreductive surgery and chemotherapy between January 2003 and December 2013 in Peking University First Hospital. The nomogram was established with the risk factors selected by LASSO regression. The medical data of 187 EOC patients with 5-year standard follow-up in Peking University Third Hospital and Beijing Obstetrics and Gynecology Hospital were used for external validation of the nomogram. AUC curve and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration.
resultsThe nomogram for 3-year recurrence risk was established with FIGO stage, histological grade, histological type, lymph node metastasis status and serum CA125 level at diagnosis. The total score can be obtained by adding the grading values of these factors together. The C statistics was 0.828 [95% CI, 0.764-0.884] and the Chi-square value is 3.6 (P = 0.731 > 0.05) with the training group. When the threshold value was set at 198, the sensitivity, specificity, positive predictive value, negative predictive value and concordance index were 88.8, 67.0, 71.8, 86.3% and 0.558 respectively. In the external validation, the C statistics was 0.803 [95%CI, 0.738-0.867] and the Chi-square value is 11.04 (P = 0.135 > 0.05). With the threshold value of 198, the sensitivity, specificity, positive predictive value, negative predictive value and concordance index of the nomogram were 75.7, 77.0, 83.2, 67.9%, and 0.52 respectively.
conclusionsWe established and validated a nomogram to predict 3-year recurrence risk of patients with EOC who achieved clinical complete remission after cytoreductive surgery and chemotherapy. This nomogram with good discrimination and calibration might be useful for screening out the patients with high risk of recurrence.
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