Development and Validation of a Site-Specific Tumor Burden Score for Predicting Surgical Outcomes in Advanced Ovarian Cancer

<b>Objective</b>: The relationship between surgical outcomes and metastatic sites in ovarian cancer (OC) is known, but the role of metastatic site-specific tumor burden remains unclear. <b>Methods</b>: We prospectively analyzed data from 202 OC patients. We developed a preoperative protocol evaluating tumor burden in 30 metastatic sites and created a predictive score for suboptimal cytoreduction, which was externally validated. <b>Results</b>: MRI-assessed tumor burdens demonstrated superior consistency with surgical findings compared to CT (κ = 0.4-1.0). Three site-specific tumor burdens (diaphragmatic spleen surface, hepatorenal recess, mesentery), upper abdominal tumor burden, and two clinical factors were identified as predictors of suboptimal cytoreduction. The predictive score incorporating these factors achieved an AUC of 0.873 (0.815 externally validated), outperforming metastatic site-integrated scores including the simulated Fagotti score (AUC: 0.656) and Suidan score (AUC: 0.8308). R0 resection rates were inversely correlated with predictive scores: 94.87% for scores of 0-3 versus 8.57% for scores >14. The peak of Youden's index reached 11, and patients with predictive scores <11 had longer median progression-free survival. <b>Conclusions</b>: We demonstrated that site-specific tumor burden is correlated with surgical outcomes in OC. Incorporating tumor burden into preoperative assessment enhances prediction performance. We developed a clinically applicable tool, marking a shift from evaluating metastatic sites to assessing metastatic site-specific tumor burden.

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Publication Details

Journal
Cancers
Published
2025-11-13
DOI
https://doi.org/10.3390/cancers17223649
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and Validation of a Site-Specific Tumor Burden Score for Predicting Surgical Outcomes in Advanced Ovarian Cancer

Xiaohui Lv, Gai‐jing Cao, Hongxi Zhao, Lingxia Li et al.
Cancers
Ovarian cancer diagnosis and treatment
article

Development and Validation of a Site-Specific Tumor Burden Score for Predicting Surgical Outcomes in Advanced Ovarian Cancer

Xiaohui Lv, Gai‐jing Cao, Hongxi Zhao, Lingxia Li, SHU‐JUAN LIU, Ying Liu, Yihua Jin, X. Li, Wei-Huan Hou, Zhiyang Xu, Yongqiang Tang
article en

Abstract

<b>Objective</b>: The relationship between surgical outcomes and metastatic sites in ovarian cancer (OC) is known, but the role of metastatic site-specific tumor burden remains unclear. <b>Methods</b>: We prospectively analyzed data from 202 OC patients. We developed a preoperative protocol evaluating tumor burden in 30 metastatic sites and created a predictive score for suboptimal cytoreduction, which was externally validated. <b>Results</b>: MRI-assessed tumor burdens demonstrated superior consistency with surgical findings compared to CT (κ = 0.4-1.0). Three site-specific tumor burdens (diaphragmatic spleen surface, hepatorenal recess, mesentery), upper abdominal tumor burden, and two clinical factors were identified as predictors of suboptimal cytoreduction. The predictive score incorporating these factors achieved an AUC of 0.873 (0.815 externally validated), outperforming metastatic site-integrated scores including the simulated Fagotti score (AUC: 0.656) and Suidan score (AUC: 0.8308). R0 resection rates were inversely correlated with predictive scores: 94.87% for scores of 0-3 versus 8.57% for scores >14. The peak of Youden's index reached 11, and patients with predictive scores <11 had longer median progression-free survival. <b>Conclusions</b>: We demonstrated that site-specific tumor burden is correlated with surgical outcomes in OC. Incorporating tumor burden into preoperative assessment enhances prediction performance. We developed a clinically applicable tool, marking a shift from evaluating metastatic sites to assessing metastatic site-specific tumor burden.

CancersVol. 17(22)
Tang Du Hospital (CN), Xijing Hospital (CN), Air Force Medical University (CN)
Fourth Military Medical University
Openalex Percentile: Top 56%
Ovarian cancer diagnosis and treatment
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