摘要
目的 建立并验证第三类医疗器械经营许可检查结果预测模型,为科学、智慧监管提供参考。方法 回顾性分析广州市2018年6月至2022年12月申报第三类医疗器械经营许可的企业提交的申报材料,确定纳入标准和排除标准,在内部系统中提取申报材料中的相关信息及检查结果,对提取变量进行单因素分析、向前向后逐步回归分析和多因素Logistic回归分析,筛选与检查结果显著相关的变量,在此基础上构建预测模型,并应用受试者工作特征曲线(ROC)、校准曲线、Hosmer-Lemeshow拟合优度检验及决策曲线分析(DCA)评价预测模型。结果 共纳入企业182家,单因素分析筛选出6个预测变量,包括专业技术人员数量(因素A)、质量管理人员数量(因素B)、质量负责人学历(因素C)、经营场所面积(因素D)、仓库面积(因素E)、冷库容积(因素F);向前向后逐步回归分析结果显示,可得到最小赤池信息准则(AIC)值为219,且此时模型兼具优良的预测性能和低复杂度。选取因素A、因素C、因素F作为最终预测变量进行Logistic多因素回归分析,绘制列线图,构建预测模型。ROC曲线下面积(AUC)为0.73,模型区分度较好;HosmerLemeshow拟合优度检验结果显示,模型校准度较好(P=0.387)。DCA结果显示,成本-收益比大于0.5时,根据模型的预测结果进行检查的净收益显著高于对所有企业进行检查和全部都不检查。结论 因素A、因素C、因素F为企业现场检查通过与否的主要影响因素。所建立的列线图预测模型对第三类医疗器械经营许可检查结果有一定价值。
Objective To establish and verify the prediction model for the inspection results of the categoryⅢmedical device business license,and to provide a reference for scientific and intelligent supervision.Methods The application materials for categoryⅢmedical device business license submitted by enterprises in Guangzhou from June 2018 to December 2022 were retrospectively selected.The inclusion and exclusion criteria were determined,the relevant information and examination results from the application materials in the internal system were extracted,the univariate analysis,forward-backward stepwise regression analysis and multivariate Logistic regression analysis were conducted on the extracted variables,and variables significantly related to the examination results were screened.On this basis,a predictive model was constructed and evaluated by the receiver operating characteristic curve(ROC),calibration curve,Hosmer-Lemeshow goodness of fit test,and decision curve analysis(DCA).Results A total of 182 enterprises were included,and six predictive variables were selected through univariate analysis,including the number of professional and technical personnel(factor A),the number of quality management personnel(factor B),the education level of quality director(factor C),the area of business site(factor D),the area of warehouse(factor E),and the volume of cold storage(factor F).The forward-backward stepwise regression results showed that the minimum Akaike Information Criterion(AIC)value could be obtained as 216,the education level of the quality director and the volume of cold storage,at which point the model combined excellent predictive performance and low complexity.Three influencing factors(A,C,and F)were selected as the final predictive variables,and a multivariate Logistic regression analysis was performed to construct a prediction model by drawing a nomogram.The area under ROC curve(AUC)of the prediction model was 0.73 with good model discrimination.The result of the Hosmer-Lemeshow goodness of fit test showed
作者
何羡霞
侯珺
胡树文
姜志辉
HE Xianxia;HOU Jun;HU Shuwen;JIANG Zhihui(Guangzhou Center for Food and Drug Evaluation,Guangzhou,Guangdong,China 510140;General Hospital of Southern Theatre Command,Guangzhou,Guangdong,China 510010)
出处
《中国药业》
CAS
2024年第1期22-25,共4页
China Pharmaceuticals
基金
广东省重大科技专项[2013A022100035]
中国人民解放军南部战区总医院院内科技计划项目[2022NZA001]。
关键词
医疗器械企业
经营许可检查
预测模型
列线图
medical device enterprises
business license inspection
prediction model
nomogram
