中国公众对异种肾移植接受度的预测模型构建及验证

Construction and validation of a prediction model for public acceptance of kidney xenotransplantation in China

目的通过构建和验证基于异种移植调查问卷的预测模型,探讨中国公众对异种肾移植的态度。方法使用问卷星平台对中国公众进行方便抽样调查,分析公众对异种肾移植的接受度及影响因素。使用随机分配法将所有纳入的问卷(2280份)按7∶3分为训练集和验证集,构建预测模型并进行验证。结果共纳入2280份调查问卷,公众对于异种肾移植的接受度为71.3%。多因素分析结果显示性别、婚姻状况、居住地区、医保状况、宗教信仰、是否素食主义、异种肾移植知晓情况、是否肾移植等待者是公众能否接受异种肾移植的独立影响因素(均为P<0.05)。训练集预测模型的受试者工作特征(ROC)曲线下面积(AUC)为0.773,验证集预测模型的AUC为0.785,训练集和验证集校准曲线均提示预测模型有较好的预测价值,决策曲线分析(DCA)均提示模型预测效能较好。结论中国公众对于异种肾移植的接受度相对较高且存在较大提升空间。基于问卷调查所构建的预测模型预测效能较好,为今后的研究提供了参考依据。

Objective To explore the public attitude towards kidney xenotransplantation in China by constructing and validating the prediction model based on xenotransplantation questionnaire.Methods A convenient sampling survey was conducted among the public in China with the platform of Wenjuanxing to analyze public acceptance of kidney xenotransplantation and influencing factors.Using random distribution method,all included questionnaires(n=2280)were divided into the training and validation sets according to a ratio of 7:3.A prediction model was constructed and validated.Results A total of 2280 questionnaires were included.The public acceptance rate of xenotransplantation was 71.3%.Multivariate analysis showed that gender,marital status,resident area,medical insurance coverage,religious belief,vegetarianism,awareness of kidney xenotransplantation and whether on the waiting list for kidney transplantation were the independent influencing factors for public acceptance of kidney xenotransplantation(all P<0.05).The area under the curve(AUC)of receiver operating characteristic(ROC)of the prediction model in the training set was 0.773,and 0.785 in the validation set.The calibration curves in the training and validation sets indicated that the prediction models yielded good prediction value.Decision curve analysis(DCA)suggested that the prediction efficiency of the model was high.Conclusions In China,public acceptance of kidney xenotransplantation is relatively high,whereas it remains to be significantly enhanced.The prediction model based on questionnaire survey has favorable prediction efficiency,which provides reference for subsequent research.