2型糖尿病患者餐后血糖估算模型的构建与验证
目的:构建并验证适合亚洲2型糖尿病（T2DM）患者的餐后血糖（PBG）估算模型。方法:利用糖化血红蛋白（HbA 1c）和指尖空腹血糖（FBG）数据对PBG估算模型进行构建及验证。建模队列来自一项4期、跨国、随机、对照、26周治疗期的临床研究，比较低预混胰岛素和中预混胰岛素作为起始胰岛素在亚洲T2DM患者中的有效性及安全性，患者基线（胰岛素起始治疗前）及26周血糖数据被用于构建PBG估算模型。验证队列来自一项多中心、随机、实用性研究，比较基础胰岛素和中预混胰岛素作为起始胰岛素在接受口服降糖药治疗后血糖仍控制不佳的中国T2DM患者（HbA 1c≥7.5%）中的有效性及安全性，患者基线数据及用药24...
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| Published in | 中华糖尿病杂志 Vol. 13; no. 7; pp. 702 - 707 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中日友好医院内分泌科，北京 100029%礼来苏州制药有限公司，上海 200041%北京大学人民医院内分泌科 100044
27.07.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-5809 |
| DOI | 10.3760/cma.j.cn115791-20210224-00102 |
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| Abstract | 目的:构建并验证适合亚洲2型糖尿病（T2DM）患者的餐后血糖（PBG）估算模型。方法:利用糖化血红蛋白（HbA
1c）和指尖空腹血糖（FBG）数据对PBG估算模型进行构建及验证。建模队列来自一项4期、跨国、随机、对照、26周治疗期的临床研究，比较低预混胰岛素和中预混胰岛素作为起始胰岛素在亚洲T2DM患者中的有效性及安全性，患者基线（胰岛素起始治疗前）及26周血糖数据被用于构建PBG估算模型。验证队列来自一项多中心、随机、实用性研究，比较基础胰岛素和中预混胰岛素作为起始胰岛素在接受口服降糖药治疗后血糖仍控制不佳的中国T2DM患者（HbA
1c≥7.5%）中的有效性及安全性，患者基线数据及用药24周后的血糖数据被用于验证PBG估算模型。基于建模队列数据分布，使用包含两个自变量的线性回归模型构建PBG估算模型。采用由FBG、PBG和HbA
1c构成的数据组，估算每个选定模型估算因子的β回归系数和α截距。选择FBG和HbA
1c作为估算PBG的自变量。使用决定系数R
2评估拟合优度。为进行模型验证，使用该模型估算PBG，并与实测PBG进行比较。计算PBG估算值与实测值间个体差异的平均值及95%置信区间（CI），用于评价该模型估算的准确性，并计算均方根误差（RMSE）。
结果:建模队列研究和验证队列研究分别入组403例和814例T2DM患者。根据散点图中的数据分布，使用包含HbA
1c和FBG两个变量的线性回归模型构建PBG估算模型，PBG（单位mmol/L）=1.5×HbA
1c（单位%）+0.5×FBG（单位mmol/L）-4.1（R
2=0.57）。验证队列PBG估算值为（13.8±3.7）mmol/L，而实测值为（13.7±4.6）mmol/L，患者PBG估算值与实测值个体差异为（0.1±3.4）mmol/L，95%CI为-0.1~0.3，
P=0.525。估算模型的RMSE为3.40 mmol/L。
结论:接受口服降糖药或胰岛素治疗的T2DM患者可使用本模型通过HbA
1c和FBG合理可靠地估算PBG。 |
|---|---|
| AbstractList | 目的:构建并验证适合亚洲2型糖尿病（T2DM）患者的餐后血糖（PBG）估算模型。方法:利用糖化血红蛋白（HbA
1c）和指尖空腹血糖（FBG）数据对PBG估算模型进行构建及验证。建模队列来自一项4期、跨国、随机、对照、26周治疗期的临床研究，比较低预混胰岛素和中预混胰岛素作为起始胰岛素在亚洲T2DM患者中的有效性及安全性，患者基线（胰岛素起始治疗前）及26周血糖数据被用于构建PBG估算模型。验证队列来自一项多中心、随机、实用性研究，比较基础胰岛素和中预混胰岛素作为起始胰岛素在接受口服降糖药治疗后血糖仍控制不佳的中国T2DM患者（HbA
1c≥7.5%）中的有效性及安全性，患者基线数据及用药24周后的血糖数据被用于验证PBG估算模型。基于建模队列数据分布，使用包含两个自变量的线性回归模型构建PBG估算模型。采用由FBG、PBG和HbA
1c构成的数据组，估算每个选定模型估算因子的β回归系数和α截距。选择FBG和HbA
1c作为估算PBG的自变量。使用决定系数R
2评估拟合优度。为进行模型验证，使用该模型估算PBG，并与实测PBG进行比较。计算PBG估算值与实测值间个体差异的平均值及95%置信区间（CI），用于评价该模型估算的准确性，并计算均方根误差（RMSE）。
结果:建模队列研究和验证队列研究分别入组403例和814例T2DM患者。根据散点图中的数据分布，使用包含HbA
1c和FBG两个变量的线性回归模型构建PBG估算模型，PBG（单位mmol/L）=1.5×HbA
1c（单位%）+0.5×FBG（单位mmol/L）-4.1（R
2=0.57）。验证队列PBG估算值为（13.8±3.7）mmol/L，而实测值为（13.7±4.6）mmol/L，患者PBG估算值与实测值个体差异为（0.1±3.4）mmol/L，95%CI为-0.1~0.3，
P=0.525。估算模型的RMSE为3.40 mmol/L。
结论:接受口服降糖药或胰岛素治疗的T2DM患者可使用本模型通过HbA
1c和FBG合理可靠地估算PBG。 |
| Abstract_FL | Objective:To develop and validate a model for postprandial blood glucose (PBG) estimation in Asian patients with type 2 diabetes mellitus (T2DM).Methods:The estimation model for PBG was developed and validated based on glycated hemoglobin (HbA
1c) and finger-based fasting blood glucose (FBG). The training cohort was drawn from a phase 4, multinational, randomized, controlled, 26-week trial comparing the efficacy and safety of insulin lispro low-mixture and insulin lispro mid-mixture as an insulin starter in Asian T2DM patients. The glycemic data at baseline (before insulin initiation) and 26 weeks were used for developing the estimation model for PBG. The validation cohort was drawn from a multicenter, randomized, and pragmatic trial comparing the efficacy and safety of basal insulin analog and insulin analog mid-mixture as an insulin starter in Chinese T2DM patients with inadequate glycemic control (HbA
1c ≥7.5%) following oral antihyperglycemic medication (OAM) treatment. The glycemic data at baseline and 24 weeks were used for validating the estimation model. Based on the data distribution of the training cohort, a linear regression model including two variables was used to develop the estimation model. The β regression coefficient of each selected model predictor and α intercept were estimated using the datasets which consisted of FBG, PBG, and HbA
1c. FBG and HbA
1c were selected as independent variables for the estimation for PBG. The goodness of fit was assessed using the decisive factor R
2. For model validation, the PBG value was estimated using this model and compared with the real PBG. The mean of individual differences between estimated PBG and real PBG and the 95% confidence interval (CI) were calculated to evaluate the accuracy of the estimation model. Additionally, the root mean square error (RMSE) was calculated.
Results:The clinical trials for the training and validation cohorts enrolled, respectively, 403 and 814 patients with T2DM. Based on data distribution through scatter plot, a linear regression model including two variables, HbA
1c and FBG, was used for developing PBG estimation model: PBG (Unit: mmol/L) = 1.5×HbA
1c (Unit: %)+0.5×FBG (Unit: mmol/L)-4.1 (R
2=0.57). In the validation cohort, the estimated PBG was (13.8±3.7) mmol/L and the real PBG was (13.7±4.6) mmol/L with the individual differences between the estimated PBG and real PBG being (0.1±3.4) mmol/L, 95%CI being -0.1 to 0.3, and
P being 0.525. The RMSE for the estimation model was 3.40 mmol/L.
Conclusion:Patients with T2DM treated with OAM or insulin could estimate their PBG with HbA
1c and FBG using this estimation model with reasonable accuracy. |
| Author | 纪立农 杨文英 冯晨 马骁 张雪莲 |
| AuthorAffiliation | 中日友好医院内分泌科，北京 100029%礼来苏州制药有限公司，上海 200041%北京大学人民医院内分泌科 100044 |
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| Author_FL | Ma Xiao Zhang Xuelian Feng Chen Ji Linong Yang Wenying |
| Author_FL_xml | – sequence: 1 fullname: Zhang Xuelian – sequence: 2 fullname: Feng Chen – sequence: 3 fullname: Ma Xiao – sequence: 4 fullname: Ji Linong – sequence: 5 fullname: Yang Wenying |
| Author_xml | – sequence: 1 fullname: 张雪莲 – sequence: 2 fullname: 冯晨 – sequence: 3 fullname: 马骁 – sequence: 4 fullname: 纪立农 – sequence: 5 fullname: 杨文英 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| Keywords | 糖尿病，2型 餐后血糖 Diabetes mellitus, type 2 Estimation model 估算模型 Postprandial blood glucose |
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| PublicationTitle | 中华糖尿病杂志 |
| PublicationTitle_FL | Chinese Journal of Diabetes Mellitus |
| PublicationYear | 2021 |
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| Title | 2型糖尿病患者餐后血糖估算模型的构建与验证 |
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