摘要
BACKGROUND Prolonged postoperative ileus(PPOI)is one of the common complications in gastric cancer patients who underwent gastrectomy.Evidence on the predictors of PPOI after gastrectomy is limited and few prediction models of nomogram are used to estimate the risk of PPOI.We hypothesized that a predictive nomogram can be used for clinical risk estimation of PPOI in gastric cancer patients.AIM To investigate the risk factors for PPOI and establish a nomogram for clinical risk estimation.METHODS Between June 2016 and March 2017,the data of 162 patients with gastrectomy were obtained from a prospective and observational registry database.Clinical data of patients who fulfilled the criteria were obtained.Univariate and multivariable logistic regression models were performed to detect the relationship between variables and PPOI.A nomogram for PPOI was developed and verified by bootstrap resampling.The calibration curve was employed to detect the concentricity between the model probability curve and ideal curve.The clinical usefulness of our model was evaluated using the net benefit curve.RESULTS This study analyzed 14 potential variables of PPOI in 162 gastric cancer patients who underwent gastrectomy.The incidence of PPOI was 19.75%in patients with gastrectomy.Age older than 60 years,open surgery,advanced stage(III–IV),and postoperative use of opioid analgesic were independent risk factors for PPOI.We developed a simple and easy-to-use prediction nomogram of PPOI after gastrectomy.This nomogram had an excellent diagnostic performance[area under the curve(AUC)=0.836,sensitivity=84.4%,and specificity=75.4%].This nomogram was further validated by bootstrapping for 500 repetitions.The AUC of the bootstrap model was 0.832(95%CI:0.741–0.924).This model showed a good fitting and calibration and positive net benefits in decision curve analysis.CONCLUSION We have developed a prediction nomogram of PPOI for gastric cancer.This novel nomogram might serve as an essential early warning sign of PPOI in gastric cancer patients.
BACKGROUND Prolonged postoperative ileus(PPOI) is one of the common complications in gastric cancer patients who underwent gastrectomy.Evidence on the predictors of PPOI after gastrectomy is limited and few prediction models of nomogram are used to estimate the risk of PPOI.We hypothesized that a predictive nomogram can be used for clinical risk estimation of PPOI in gastric cancer patients.AIM To investigate the risk factors for PPOI and establish a nomogram for clinical risk estimation.METHODS Between June 2016 and March 2017,the data of 162 patients with gastrectomy were obtained from a prospective and observational registry database.Clinical data of patients who fulfilled the criteria were obtained.Univariate and multivariable logistic regression models were performed to detect the relationship between variables and PPOI.A nomogram for PPOI was developed and verified by bootstrap resampling.The calibration curve was employed to detect the concentricity between the model probability curve and ideal curve.The clinical usefulness of our model was evaluated using the net benefit curve.RESULTS This study analyzed 14 potential variables of PPOI in 162 gastric cancer patients who underwent gastrectomy.The incidence of PPOI was 19.75% in patients with gastrectomy.Age older than 60 years,open surgery,advanced stage(III-IV),and postoperative use of opioid analgesic were independent risk factors for PPOI.We developed a simple and easy-to-use prediction nomogram of PPOI after gastrectomy.This nomogram had an excellent diagnostic performance [area under the curve(AUC)=0.836,sensitivity=84.4%,and specificity=75.4%].This nomogram was further validated by bootstrapping for 500 repetitions.The AUC of the bootstrap model was 0.832(95%CI:0.741-0.924).This model showed a good fitting and calibration and positive net benefits in decision curve analysis.CONCLUSION We have developed a prediction nomogram of PPOI for gastric cancer.This novel nomogram might serve as an essential early warning sign of PPOI in gastric cancer patients.
基金
Supported by the National Nature Science Foundation of China,No.81672319,No.81602507,and No.81773135
the National Key Research and Development Plan,No.2017YFC0908300
Beijing Nova Program,No.Z181100006218011
