摘要目的:探讨控制营养状态(CONUT)评分对非肌层浸润性膀胱癌(NMIBC)患者治疗后肿瘤复发的预测价值，并建立列线图模型评价其预测效果。方法:回顾性分析2017年1月至2020年1月在本院收治的164例NMIBC患者的临床资料，通过受试者工作特征(ROC)曲线确定CONUT评分的最佳截断值。根据CONUT评分将患者分成高CONUT评分组(73例)和低CONUT评分(71例)。采用Kaplan-Meier曲线和Cox比例风险回归模型评估CONUT评分对NMIBC患者无复发生存(RFS)的预测价值。基于多变量Cox分析认定的显著变量，构建预测NMIBC患者RFS的列线图模型。采用C指数和校准曲线评价列线图模型对肿瘤复发的预测能力。结果:CONUT评分预测NMIBC患者的RFS最佳截断值确定为2分[曲线下面积(AUC)＝0.704，95% CI: 0.626～0.782]。高CONUT评分组的多发肿瘤数量、淋巴血管侵犯(LVI)高于低CONUT评分组，而血清白蛋白、外周血淋巴细胞计数及血清总胆固醇低于低CONUT评分组(均 P<0.05)。随访期间共有77例(47.0%)患者观察到局部肿瘤复发，Kaplan-Meier生存曲线结果显示，术前高CONUT评分与NMIBC患者的不良RFS之间存在显著相关性。低CONUT评分组与高CONUT评分组患者的3年RFS分别为60.3%和34.9%，差异有统计学意义( χ2＝16.219, P<0.001)。肿瘤最大径、病理学分级、T分期、LVI以及CONUT评分均是NMIBC患者的RFS影响因素(均 P<0.05)。多变量Cox回归分析结果显示肿瘤最大径≥3 cm 、LVI与CONUT评分≥2分是NMIBC患者的RFS独立预测因素(均 P<0.05)。列线图模型预测患者RFS的C指数为0.711 (95% CI: 0.649～0.823)，其中预测1、3和5年RFS的AUC分别为0.748、0.720和0.695。校准曲线结果显示列线图模型预测的1、3和5年的RFS与理想预测之间无明显偏差。 结论:CONUT评分可作为预测NMIBC治疗后肿瘤复发的有效工具，基于CONUT评分的列线图模型有望实现对患者的个体化风险分层，帮助临床医生做出早期干预。

abstractsObjective:To investigate the predictive value of controlling nutritional status (CONUT)score for the recurrence of non-muscle invasive bladder cancer (NMIBC) patients, and establish a nomogram model based on CONUT score to evaluate its predictive performance.Methods:The clinical data of 164 NMIBC patients admitted to our hospital from January 2017 to January 2020 were analyzed retrospectively, and the optimal cutoff value of CONUT score was determined by the receiver operation characteristics (ROC) curve. According to CONUT score, the patients were divided into high CONUT score group (73 cases) and low CONUT score group (71 cases).Kaplan-Meier curve and Cox proportional hazard regression model were used to evaluate the predictive value of CONUT score for recurrence-free survival (RFS) of NMIBC patients. Based on the significant variables identified by the multivariate Cox analysis, an nomogram model was developed and C-index and calibration curves were used to evaluate its predictive performance for tumor recurrence.Results:The best cut-off value of CONUT score for predicting RFS in NMIBC patients was determined to be 2 points (AUC=0.704, 95% CI: 0.626-0.782). The number of multiple tumors, lymphatic vascular invasion(LVI) in high CONUT score group were higher than those in low CONUT score group, serum albumin, peripheral blood lymphocyte count and serum total cholesterol were lower than those in low CONUT score group(all P<0.05). Local tumor recurrence was observed in 77 patients (47.0%) during follow-up, Kaplan-Meier survival curve results showed a significant association between high preoperative CONUT score and poor RFS in patients with NMIBC. The 3-year RFS of patients with low CONUT score group and high CONUT score group were 60.3% and 34.9%, respectively, and the difference was statistically significant ( χ2=16.219, P<0.001). Tumor maximum diameter, pathological grade, T stage, LVI and CONUT score were all influencing factors of RFS in NMIBC patients (all P<0.05). Multivariate Cox regression analysis showed that maximum tumor diameter≥3 cm and LVI and CONUT score≥2 were independent predictors of RFS in NMIBC patients (all P<0.05). The nematic model predicted a C index of 0.711 (95% CI: 0.649-0.823) for the patient′s RFS, with an AUC of 0.748, 0.720, and 0.695 for 1-year, 3-year, and 5-year RFS, respectively. The calibration curve shows no significant deviation between the 1-year, 3-year, and 5-year RFS predicted by the nomogram model and the ideal forecast. Conclusions:CONUT score was an effective tool to predict NMIBC recurrence after initial treatment, and its nomogram model might provide an individualized risk stratification for NMIBC patients and help clinicians make early intervention.