A Surgical Decision-making Scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients

Abstract

Abstract Backgrounds Spontaneous ventilation-video-assisted thoracoscopic surgery (SV-VATS) has been applied to non-small cell lung cancer (NSCLC) patients in many centers. Since it remains a new and challenging surgical technique, only selected patients can be performed SV-VATS. In this study, we aim to develop a clinical decision-making model to make surgery decision between SV-VATS and MV-VATS in NSCLC patients more objectively and individually. Methods 5,580 NSCLC patients undergoing SV-VATS or MV-VATS in the department of thoracic surgery between 2011 and 2018 were included. Univariate and multivariate regression analysis were used to identify potential factors influencing the surgical decisions. The performance of the model was validated by area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). Results The Surgical Decision-making Scoring (SDS) model was built guided by the clinical judgment and statistically significant results of univariate and multivariate regression analyses of potential predictors, including age (p < 0.001), smoking status (p = 0.03), BMI (p < 0.001), T stage (p < 0.001), N stage (p = 0.02), ASA grade (p < 0.001) and surgical technique (p < 0.001). The AUC of the training set and the test set were 0.73 (0.13, 0.61 - 0.74) and 0.76 (0.13, 0.62 - 0.77), respectively. The calibration curves and the DCA curve revealed that the SDS model has a desired performance in predicting the surgical decision. Conclusions This SDS model is the first clinical decision-making model developed for an individual NSCLC patient to make decision between SV-VATS and MV-VATS.