ArticleJournal of cancer research and clinical oncology2025
Validation of mortality risk scores after esophagectomy.
Article in Journal of cancer research and clinical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Article
- Comparison of two-lung ventilation with CO₂ artificial pneumothorax and one-lung ventilation during esophagectomy: a retrospective cohort study.BMC anesthesiology · 2026Article
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8 authors.
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Abstract
purposeOncological esophagectomy is the mainstay in esophageal cancer treatment, but perioperative mortality remains a significant concern. Various scoring systems exist to identify patients at high risk for postoperative complications and death. In the following, we aim to evaluate and compare these different scoring systems.
methodsWe analyzed data from 714 patients who underwent esophagectomy between 2002 and 2021. Each patient's risk was calculated using three models: the International Esodata Study Group (IESG) 90-day mortality risk prediction, the Steyerberg 30-day mortality score, and the Fuchs et al. preoperative in-hospital mortality score (Fuchs score). The diagnostic performance of these models was assessed using the area under the receiver operating characteristic (ROC) curves.
resultsOf the 714 patients, the majority (87.67%) underwent abdomino-thoracic esophagectomy with intrathoracic anastomosis. The IESG score classified 52.1% as very low, 26.6% low, 17.5% middle, 2.8% high, and 1% as very high risk, while the Fuchs score identified 94.5% as low-risk and 5.5% as high-risk patients. Mortality rates were 6.9% at 90 days, 3.4% at 30 days, and 6.7% in-hospital. The area under the ROC curve was 0.634 (95%CI: 0.557-0.712) for the IESG model, 0.637 (95%CI: 0.526-0.747) for the Steyerberg score, and 0.686 (95%CI: 0.611-0.760) for the Fuchs score.
conclusionsExisting risk score systems provide a possibility for preoperative risk stratification, particularly for identifying high-risk patients. However, due to their limited predictive ability, improvements are needed to apply these strategies effectively in clinical practice.
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