# Splenectomy during cytoreductive surgery in advanced epithelial ovarian cancer can be predicted

**Authors:** Thien-Kim Do, Yohann Dabi, Cyril Touboul, Jennifer Uzan, François Margueuritte, Geoffroy Canlorbe, Yohan Kerbage, Vincent Lavoué, Chérif Akladios, Lobna Ouldamer, Hélène Costaz, Alexandre Bricou, Henri Azaïs, Pauline Chauvet, Xavier Carcopino, Cyrille Huchon, Camille Mimoun

PMC · DOI: 10.1016/j.eurox.2025.100395 · European Journal of Obstetrics & Gynecology and Reproductive Biology: X · 2025-05-09

## TL;DR

This study developed a predictive score to identify patients likely to need a splenectomy during surgery for advanced ovarian cancer, helping improve preoperative planning and management.

## Contribution

A novel 4-variable predictive score was developed to identify high-risk patients for splenectomy during cytoreductive surgery in advanced ovarian cancer.

## Key findings

- Four independent factors were identified: age <60, omental cake, diaphragmatic carcinosis, and digestive involvement.
- The model had a ROC-AUC of 0.76 and showed positive net clinical benefit between 15% and 40% threshold probabilities.
- Patients meeting all four criteria had a 32% probability of splenectomy with high specificity and a positive likelihood ratio of 6.31.

## Abstract

Splenectomy may be necessary for complete cytoreductive surgery (CRS) in advanced stage epithelial ovarian cancer (AS-EOC), potentially raising perioperative morbidity and necessitating specific patient management.

This study aimed to develop a predictive score of splenectomy in CRS of AS-EOC.

Data from histologically confirmed AS-EOC (FIGO IIB-IV) before CRS and diagnosed between 01/01/2000 and 01/06/2017, were extracted from the FRANCOGYN multicentric database (14 French hospitals). After identifying predictive factors of splenectomy, we performed a logistic regression to develop a prediction model and construct a risk score, allowing identification of a high-risk group. Model discrimination was assessed using a Receiver Operating Characteristic (ROC) curve. Decision Curve Analysis (DCA) was then conducted to evaluate the model’s net clinical benefit across a range of threshold probabilities.

Among 1288 patients included, 7 % (n = 91) underwent splenectomy. Four independent variables statistically associated with splenectomy were identified: age < 60 years (aDOR = 1.76, 95 % CI [1.13–2.75], p = 0.015), omental cake (aDOR = 2.12, 95 % CI [1.11–4.08], p = 0.024), diaphragmatic carcinosis (aDOR = 2.36, 95 % CI [1.34–4.18], p = 0.001), and digestive involvement at initial CT and/or laparoscopy (aDOR = 3.24, 95 % CI [1.93–5.43], p < 0.001). The ROC-AUC of this prediction model was 0.76. Patients meeting all 4 criteria with a maximum of 10 points defined the high-risk group and had a splenectomy probability of 32 % (95 % CI [22.00–44.31]), with a specificity of 95.8 % (95 % CI [94.5–96.9]) and a positive likelihood ratio of 6.31 (95 % CI [4.08–9.78]). The DCA showed a positive net clinical benefit of the model between 15 % and 40 % threshold probabilities.

Using a simple 4 – variable predictive score, patients at high risk of splenectomy during CRS in AS-EOC could be identified to improve patients’ preoperative information and perioperative management.

## Linked entities

- **Diseases:** ovarian cancer (MONDO:0005140), epithelial ovarian cancer (MONDO:0005140)

## Full-text entities

- **Diseases:** AS-EOC (MESH:D000077216), FIGO IIB-IV (MESH:D006011)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

34 references — full list in the complete paper: https://tomesphere.com/paper/PMC12143630/full.md

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Source: https://tomesphere.com/paper/PMC12143630