ASO Author Reflections: Prediction of Morbidity and Mortality After Esophagectomy: A Systematic Review
M. P. van Nieuw Amerongen, H. J. de Grooth, G. L. Veerman, K. A. Ziesemer, M. I. van Berge Henegouwen, P. R. Tuinman

Abstract
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEsophageal Cancer Research and Treatment · Esophageal and GI Pathology · Gastric Cancer Management and Outcomes
Past
Treatment of esophageal malignancies with surgical esophagectomy is a high-risk procedure with a complication rate of up to 60%.^1^ Predicting the risk of complications could have several potentially important health care benefits. A large number of preoperative prediction models on morbidity and mortality after esophagectomy have been developed in recent years, but their usefulness has not yet been assessed systematically.
Present
We conducted a systematic review that included 22 studies with 33 different models, of which 18 models were newly developed.^2^ The prognostic accuracy of models differed between 0.51 and 0.85. For most models, the required variables are readily available. Many studies showed a high risk of bias and none of the prediction models were rigorously validated. Two prediction models for mortality and one model for pulmonary complications have the potential to be developed further.^3–5^ None of the models were ready for clinical implementation.
Future
This review shows that several models are promising but need to be further developed. If improved, the models could provide significant benefits for patients with esophageal cancer. Early identification of high-risk patients allows for informed decision making, personalized preventive measures targeting modifiable risk factors, and closer monitoring of those at the highest risk for timely complication detection, potentially avoiding non-cost-effective interventions for the entire population. However, future models do need to be robustly developed and validated in other populations.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Di Siena M Perelman A Birk J Rezaizadeh H Esophageal cancer: an updated review South Med J 2021114316116810.14423/SMJ.000000000000122633655310 · doi ↗ · pubmed ↗
- 2van Nieuw Amerongen M Pde Grooth HJ Veerman GL Ziesemer K Avan Berge Henegouwen MI Tuinman PR Prediction of morbidity and mortality after esophagectomy: a systematic review Ann Surg Oncol 202410.1245/s 10434-024-14997-4PMC 1099770538383661 · doi ↗ · pubmed ↗
- 3Takeuchi H Miyata H Gotoh M Kitagawa Y Baba H Kimura WA risk model for esophagectomy using data of 5354 patients included in a Japanese nationwide web-based database Ann Surg 2014260225926610.1097/SLA.000000000000064424743609 · doi ↗ · pubmed ↗
- 4D'Journo XB Boulate D Fourdrain A Risk prediction model of 90-day mortality after esophagectomy for Cancer JAMA Surg 2021156983684510.1001/jamasurg.2021.237634160587 PMC 8223144 · doi ↗ · pubmed ↗
- 5Thomas M Defraene G Lambrecht M Deng W Moons J Nafteux PNTCP model for postoperative complications and one-year mortality after trimodality treatment in oesophageal cancer Radiother Oncol 2019141334010.1016/j.radonc.2019.09.01531630867 · doi ↗ · pubmed ↗
