在尿路结石患者中预测草酸钙结石列线图的建立与应用  

Establishment and application of the nomogram for predicting calcium oxalate stones in patients with urinary calculus

作　　者：谢茂春 曹明德 戴英波 延敏博[1] 王晋华 张豪 吴振杰 Xie Maochun;Cao Mingde;Dai Yingbo;Yan Minbo;Wang Jinhua;Zhang hao;Wu Zhenjie(Department of Urology,The Fifth Affiliated Hospital of Sun Yat-Sen University,Zhuhai 519000,China;Department of Orthopaedics,The Fifth Affiliated Hospital of Sun Yat-Sen University,Zhuhai 519000,China)

机构地区：[1]中山大学附属第五医院泌尿外科,珠海519000 [2]中山大学附属第五医院创伤与关节外科,珠海519000

出　　处：《中华腔镜泌尿外科杂志（电子版）》2022年第1期53-59,共7页Chinese Journal of Endourology(Electronic Edition)

摘　　要：目的建立和应用个性化的列线图模型,探讨列线图预测尿路结石患者中草酸钙结石的准确性及可行性。方法回顾性分析2017年1月1日至2018年12月31日在中山大学附属第五医院接受手术治疗的298例泌尿系结石患者资料,以7∶3的比例随机分为建模组和验证组,基于建模组采用最小绝对值收敛和选择算子回归(Lasso)模型及多变量Logistic回归分析选择草酸钙结石的最佳预测特征,根据最佳预测特征以列线图的形式构建预测模型。通过C指数、校准曲线和决策曲线分别评估列线图的辨别力、校准和临床实用性,并基于验证组对外部验证进行评估。结果在LASSO模型中选择的最佳预测特征包括结石位置、甘油三酯(TG)和尿比重(SG)。将以上最佳预测特征和性别、年龄一起建立列线图模型后,建模组和验证组的C指数分别为0.706、0.603,表明模型具有良好的辨别能力。校准曲线中标准曲线与预测校准曲线贴合良好,提示校正效果良好。决策曲线分析表明,在草酸钙结石可能性阈值为31%时使用该列线图可以在临床上获益。结论本研究建立的列线图预测模型可有效预测草酸钙结石,有助于筛选和早期识别草酸钙尿路结石的高危患者,对泌尿科医师进行临床治疗决策可能有一定的指导意义。Objective To develop an individualized nomogram model and explore the feasibility and veracity of nomogram to predict calcium oxalate stones in patients with urinary calculus.Methods Clinical data of 298 patients with urinary calculus who underwent surgery in the Fifth Affiliated Hospital of Sun Yat-sen University from January 1,2017 to December 31,2018 were retrospectively analyzed.The patients were randomly divided into a development group and a validation group by 7∶3 ratio.The least absolute shrinkage and selection operator regression(LASSO)model and multivariable logistic regression analysis were used to select the best prediction characteristics of calcium oxalate stones based on the development group,and a prediction model was constructed in the form of a nomogram according to the best prediction characteristics.Discrimination,calibration,and clinical usefulness of the nomogram were assessed respectively using the C-index,calibration plot,and decision curve analysis,and external validation was assessed based on the validation group.Results The best predictive features selected in the LASSO model include stone location,triglycerides(TG),and urine specific gravity(SG).After the gender,age and the best predictive characteristics were used to establish a nomogram model,the C indexes of the development group and the validation group were 0.706 and 0.603,respectively,indicating that the model had good discrimination ability.The standard curve in the calibration curve fit well with the predicted calibration curve,which indicates good calibration.Decision curve analysis showed that the calcium oxalate stones nomogram was clinically useful when intervention was decided at the calcium oxalate stones possibility threshold of 31%.Conclusion A nomogram prediction model for the prediction of calcium oxalate stones was established.This model is helpful in screening and early identifying patients who are at high risk of calcium oxalate urinary stones,and is significant to help urologists make clinical treatment decision

关 键 词：尿路结石 草酸钙结石 列线图 预测与验证 

分 类 号：R691.4[医药卫生—泌尿科学]