Systemic Immune-inflammation Index In Predicting Non-curative Resection Of Endoscopic Submucosal Dissection In Patients With Early Gastric Cancer

Purpose: Although endoscopic submucosal dissection(ESD)has gradually replaced surgical removal as the standard treatment for early gastric cancer(EGC),there are nearly 30% patients who have received non-curative resection(NCR)of ESD that may still need to undergo additive gastrectomy.Therefore,the prediction of NCR prior to ESD procedure will undoubtedly facilitate the improvement of the prognosis and quality of life for EGC patients.Inflammation indices that reflect the inflammation response of human body including neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),systemic inflammation response index(SIRI),and systemic immune-inflammation index(SII),has been shown to have great potential in predicting the overall survival(OS)of gastric cancer patients.This study aims to investigate and compare the predictive validity of NCR between inflammation indices including SII,PLR,NLR,and SIRI in EGC patients.Methods: We retrospectively reviewed and analyzed the clinicopathological data of EGC patients who underwent ESD in the affiliated hospital of Qingdao University between 2013 and 2021.Preoperative SII,PLR,NLR,and SIRI value was calculated.The relationship between SII and clinicopathologic features was investigated.Receiver operating characteristic(ROC)curves and the area under the curve(AUC)were used to compare the predictive values of NCR between SII and other inflammation indices.Youden index was utilized to calculate the optimal cut-off value of SII、SIRI、PLR、NLR.Patients were then divided into low SII group and high SII group.The correlation between SII and other clinicopathological features were investigated using the χ2 test.Patients were also subdivided into CR group and NCR group to compare the difference in clinicopathological characteristics between them using χ2 test.The features with statistical difference were further included in the multivariate analysis.Binary Logistic Analysis was used to identify independent risk factors for NCR in the multivariate analysis.The independent risk factors were then used to construct a nomogram as a predictive model for NCR.Internal verification,including a ROC curve and calibration,was used to assess the predictive accuracy of the nomogram.Results: The optimal cut-off value of SII、SIRI、PLR、NLR were 414.87、0.45、140、and 1.21,respectively.SII was associated with larger tumor size,submucosal invasion,larger hospital expenses,a higher e Cura grade,and a greater risk of NCR.ROC analysis revealed that the AUC of SII greater than PLR、NLR、SIRI,indicating that SII was a better predictor of NCR post ESD than PLR,SIRI,and NLR.Comparing to CR patients,NCR patients were more susceptible to have higher SII,SIRI,PLR,NLR value,lesions located on the upper 1/3 of the stomach,tumors>3 cm,larger hospital expenses,poorly differentiated carcinoma,ulceration and submucosal invasion.Multivariate analysis indicated that SII(OR=2.707,P=0.001)、PLR(OR=2.302,P=0.024)、 NLR(OR=3.169,P=0.035)、 SIRI(OR=3.787,P=0.004),tumors larger than 3cm(OR=2.055,P<0.001),upper stomach tumors(OR=16.393,P<0.001),poorly differentiated type(OR=29.754,P<0.001),ulceration(OR=4.814,P=0.001),and submucosal invasion(OR=51.017,P<0.001)were independent risk factors for NCR.SII,pathology,tumor size,ulceration,location of the tumor were then utilized to construct a nomogram for the prediction of NCR.Validation of this nomogram included evaluation of discrimination and calibration.We applied the concordance index(C-index)and calibration curve to assess the accuracy and discriminative ability of the nomogram.The AUC was used to evaluate the predictive efficacy for NCR of the model.AUC was calculated by running the predictive model through a ROC curve.The AUC or C-index of0.5 indicates that the model has no predictive effect,while the AUC or C-index of 1.0 indicates that there is perfect concordance between the actual results and those predicted by the model.Calibration was carried out using the bootstrap method,which consisted of 1000 bootstrap sample corrections.A calibration curve generated using the bootstrap method for internal validation demonstrated great consistency between the deviation correction prediction and the ideal interface line.The concordance index of this nomogram was 0.942,indicating satisfying accuracy and discriminative ability of the model.AUC of the ROC curve that was performed to predict NCR was 0.858,suggesting that in comparing with single inflammation indices including SII,PLR,and NLR,the nomogram model based could be considered a more effective tool for the prediction of NCR.Conclusion:1.SII was a better predictive factor of NCR than SIRI,NLR,PLR for EGC patients undergoing ESD.SII was associated with larger tumor size,submucosal invasion,larger hospital expenses,a higher e Cura grade,and a greater risk of NCR.2.SII,PLR,NLR,SIRI,tumors larger than 3cm,upper stomach tumors,poorly differentiated type,ulceration,and submucosal invasion were independent risk factors of NCR for EGC patients after ESD.3.The nomogram constructed by 5 preoperative risk factors of NCR,after thorough validation on both accuracy and discriminative ability,showed great potency in predicting NCR,hence could be used as a convenient,reliable predictive model of NCR after ESD procedure.