Evidence map›Paper›PMID 40406243›Full record

ArticleFrontiers in oncology2025

Development of a nomogram for predicting recurrence of epithelial ovarian cancer involving traditional Chinese medicine treatment.

Xiaofeng Chen, Xudong Hu, Huanmei Lin, Ziang Li, Baijun Gao, Hongmei Ouyang, Xiangdan Hu, Jing Xiao

Abstract read
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Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiaofeng Chen *The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Xudong Hu *The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Huanmei LinDepartment of Gynecology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Ziang LiThe Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Baijun GaoThe Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Hongmei OuyangYuexiu District Maternal and Child Health Hospital, Guangzhou, Guangdong, China.
Xiangdan HuDepartment of Gynecology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Jing XiaoState Key Laboratory of Traditional Chinese Medicine Syndrome/Department of Gynecology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The treatment of epithelial ovarian cancer (EOC) is evolving towards personalization and precision. Early prediction of recurrence can provide a basis for individualized monitoring and treatment. Our study aims to develop a predictive model for early recurrence of ovarian cancer incorporating Traditional Chinese Medicine (TCM) treatment. Methods: We reviewed the clinicopathological and prognostic data of EOC patients who achieved complete clinical remission after surgery and chemotherapy at Guangdong Traditional Chinese Medicine Hospital (GPHCM) between December 2011 and July 2022. Basic information, clinical characteristics, treatment plans, and follow-up data were collected. Univariate logistic analysis was performed to identify significant variables ( Result: This study included a total of 170 patients. Multivariate logistic regression analysis revealed that surgical procedure, The International Federation of Gynecology and Obstetrics (FIGO) stage, completion of the full chemotherapy course, and exposure to TCM were independent prognostic factors for ovarian cancer recurrence. Based on these factors, this study developed a nomogram model to predict recurrence risk, incorporating four key variables. The AUC of the prediction model was 0.843 (95% CI: 0.774-0.898), and the Hosmer-Lemeshow test and calibration plot indicated good calibration. DCA showed the model provided higher net benefit across a wide range of threshold probabilities. Conclusion: The nomogram we developed effectively predicted 2-year recurrence risk in epithelial ovarian cancer patients. Notably, TCM treatment lasting more than 6 months may help prolong progression-free survival (PFS).

Indexed as

nomogramovarian cancerpredictive modelrecurrencetraditional Chinese medicine

Identifiers

PMID40406243
PMCPMC12094981

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