Key result
An intraoperative factor-based classifier successfully stratified patients into high- and low-risk groups for 30-day morbidity (70.1% vs 7.2%, P<0.001) after radical oesophagectomy.
Why the study?
Oesophagectomy for malignancy is a complex procedure with considerable complications, and the ability of an intraoperative factor-based classifier to predict postoperative complications needed evaluation.
Can an intraoperative factor-based classifier predict postoperative morbidity in patients undergoing radical oesophagectomy?
Cohort (n=251)
Can an intraoperative factor-based classifier predict postoperative morbidity in patients undergoing radical oesophagectomy?
An intraoperative factor-based nomogram can reliably predict the risk of 30-day postoperative morbidity and mortality after radical oesophagectomy.
May aid postoperative risk stratification after oesophagectomy; leaves open need for prospective validation before clinical adoption.
OBJECTIVES: Oesophagectomy for malignancy is a highly complex and difficult procedure associated with considerable postoperative complications. In this study, we aimed to identify the ability of an intraoperative factor (IPFs)-based classifier to predict complications after oesophagectomy. METHODS: This retrospective review included 251 patients who underwent radical oesophagectomy from October 2015 to December 2017. Using the least absolute shrinkage and selection operator regression model, we extracted IPFs that were associated with postoperative morbidity and then built a classifier. Preoperative variables and the IPF-based classifier were analysed using univariable and multivariable logistic regression analysis. A nomogram to predict the risk of postoperative morbidity was constructed and validated using bootstrap resampling. RESULTS: Following the least absolute shrinkage and selection operator regression analysis, we discovered that those 4 IPF (surgical approach, lowest heart rate, lowest mean arterial blood pressure and estimated blood loss) were associated with postoperative morbidity. After stratification into low-and high-risk groups with the IPF-based classifier, the differences in 30-day morbidity (7.2% vs 70.1%, P < 0.001, respectively) and mortality (0% vs 4.7%, P = 0.029, respectively) were found to be statistically significant. The multivariable analysis demonstrated that the IPF-based classifier was an independent risk factor for predicting postoperative morbidity for patients with oesophageal cancer. The performance of the nomogram was evaluated and proven to be clinically useful. CONCLUSIONS: We demonstrated that an IPF-based nomogram could reliably predict the risk of postoperative morbidity. It has the potential to facilitate the individual perioperative management of patients with oesophageal cancer.
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Xi et al. (2019) conducted a cohort in Oesophageal cancer (n=251). High-risk classification by intraoperative factor (IPF)-based classifier vs. Low-risk classification was evaluated on 30-day morbidity (p=< 0.001). An intraoperative factor-based classifier successfully stratified patients into high- and low-risk groups for 30-day morbidity (70.1% vs 7.2%, P<0.001) after radical oesophagectomy.
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