A preoperative prediction model for anastomotic leakage after rectal cancer resection based on 13.175 patients

Hoek, V.T.; Buettner, S.; Sparreboom, C.L.; Detering, R.; Menon, A.G.; Kleinrensink, G.J.; Wouters, M.W.J.M.; Lange, J.F.; Wiggers, J.K.; Dutch ColoRectal Audit Grp

doi:doi:10.1016/j.ejso.2022.06.016

Introduction: This study aims to develop a robust preoperative prediction model for anastomotic leakage (AL) after surgical resection for rectal cancer, based on established risk factors and with the power of a large prospective nation-wide population-based study cohort. Materials and methods: A development cohort was formed by using the DCRA (Dutch ColoRectal Audit), a mandatory population-based repository of all patients who undergo colorectal cancer resection in the Netherlands. Patients aged 18 years or older were included who underwent surgical resection for rectal cancer with primary anastomosis (with or without deviating ileostomy) between 2011 and 2019. Anastomotic leakage was defined as clinically relevant leakage requiring reintervention. Multivariable logistic regression was used to build a prediction model and cross-validation was used to validate the model. Results: A total of 13.175 patients were included for analysis. AL was diagnosed in 1319 patients (10%). A...Show moreIntroduction: This study aims to develop a robust preoperative prediction model for anastomotic leakage (AL) after surgical resection for rectal cancer, based on established risk factors and with the power of a large prospective nation-wide population-based study cohort. Materials and methods: A development cohort was formed by using the DCRA (Dutch ColoRectal Audit), a mandatory population-based repository of all patients who undergo colorectal cancer resection in the Netherlands. Patients aged 18 years or older were included who underwent surgical resection for rectal cancer with primary anastomosis (with or without deviating ileostomy) between 2011 and 2019. Anastomotic leakage was defined as clinically relevant leakage requiring reintervention. Multivariable logistic regression was used to build a prediction model and cross-validation was used to validate the model. Results: A total of 13.175 patients were included for analysis. AL was diagnosed in 1319 patients (10%). A deviating stoma was constructed in 6853 patients (52%). The following variables were identified as significant risk factors and included in the prediction model: gender, age, BMI, ASA classification, neo-adjuvant (chemo)radiotherapy, cT stage, distance of the tumor from anal verge, and deviating ileos-tomy. The model had a concordance-index of 0.664, which remained 0.658 after cross-validation. In addition, a nomogram was developed. Conclusion: The present study generated a discriminative prediction model based on preoperatively available variables. The proposed score can be used for patient counselling and risk-stratification before undergoing rectal resection for cancer. (c) 2022 Published by Elsevier Ltd.Show less

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A preoperative prediction model for anastomotic leakage after rectal cancer resection based on 13.175 patients