Analysis of risk factors for postoperative nausea and vomiting in non-small cell lung cancer patients based on LASSO regression
Objective To construct a predictive nomogram for postoperative nausea and vomiting(PONV)in non-small cell lung cancer(NSCLC)patients based on least absolute shrinkage and selection operator(LASSO)regression and validate its predictive effect.Methods Retrospective clinical data of a-dult NSCLC patients who underwent pulmonary lobectomy surgery at the First Affiliated Hospital of Zheng-zhou University from April 2021 to February 2022 were collected.A total of 738 eligible patients were se-lected and divided into a training cohort(n=517)and a validation cohort(n=221)in a 7∶3 ratio using a random number table method.After performing LASSO regression analysis on the training cohort,inde-pendent risk factors for PONV were identified,and a nomogram model was established.The predictive effi-ciency,accuracy,and clinical utility of the model were evaluated using the area under the receiver operat-ing characteristic curve(AUC),calibration curve,and decision curve analysis(DCA).Results LASSO regression identified three independent risk factors for PONV in NSCLC patients:gender,weight,and monocyte count.A nomogram predicting PONV risk was constructed,with AUCs of 0.687[95％confi-dence interval(CI):0.641-0.714]for the training set and 0.683(95％CI:0.656-0.725)for the inter-nal validation set.The calibration plot showed good consistency between predicted and observed values.DCA results indicated maximum clinical benefit when the threshold probability ranged from 8％to 25％.Conclusion This study constructed and validated the predictive efficacy and clinical utility of a PONV no-mogram for NSCLC patients.The predictive model provides a reliable basis for the prevention and treatment of PONV in NSCLC patients.
Non-small cell lung cancerPostoperative nausea and vomiting
NETL
NSTL
万方数据
