Exploring C-peptide loss in type 1 diabetes using growth curve analysis.
Exploring C-peptide loss in type 1 diabetes using growth curve analysis.
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DOI：
10.1371/journal.pone.0199635
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Cole TJ
中科院分区：
文献类型：
--
作者：
Besser REJ;Ludvigsson J;Hindmarsh PC;Cole TJ
1型糖尿病(T1D)的C-肽(CP)丢失具有很高的变异性，其影响因素尚不清楚。我们对确诊后长达6年的T1D患者的Cp值进行了建模，将系列数据处理为诊断后随时间变化的生长曲线。其目的是用简单的术语总结个体患者CP丢失的模式(即生长曲线形状)，并确定预测个体这种模式的基线特征。1976-2011年间，442例T1D患者在确诊后3、9、18、30、48和72个月接受了120分钟的混合餐耐量试验，计算曲线下面积(AUC)CP(n=1537)。使用新的锡塔尔混合效应生长曲线模型(平移和旋转叠加)对数据进行分析。它符合平均AUC增长曲线，但也允许曲线的平均水平和下降速度在不同的人之间变化，以最好地符合个别患者的曲线。这些曲线调整定义了各个曲线形状。平方根(√)AUC量表提供了最好的匹配。个体的平均跌倒水平和跌倒速度呈正态分布，且彼此之间不相关。诊断时的年龄和3个月时的√AUC值强烈地预测了患者特定的平均水平，而诊断时较年轻的年龄(p<；0.0001)和3个月的MMTT120分钟Cp值(p=0.002)预测了患者特定的下降率。SITAR生长曲线分析是评估1型糖尿病患者CP丢失的有用工具，解释了患者在平均水平和下降速度方面的差异。快速CP丢失的定义可以基于跌倒分布率的分位数，从而更好地了解决定CP丢失的因素，并将患者分层纳入靶向治疗。
C-peptide (CP) loss in type 1 diabetes (T1D) is highly variable, and factors influencing it are poorly understood. We modelled CP values in T1D patients from diagnosis for up to 6 years, treating the serial data as growth curves plotted against time since diagnosis. The aims were to summarise the pattern of CP loss (i.e. growth curve shape) in individual patients in simple terms, and to identify baseline characteristics that predict this pattern in individuals. Between 1976 and 2011, 442 T1D patients initially aged <18y underwent 120-minute mixed meal tolerance tests (MMTT) to calculate area under the curve (AUC) CP, at 3, 9, 18, 30, 48 and 72 months after diagnosis (n = 1537). The data were analysed using the novel SITAR mixed effects growth curve model (SuperImposition by Translation And Rotation). It fits a mean AUC growth curve, but also allows the curve’s mean level and rate of fall to vary between individuals so as to best fit the individual patient curves. These curve adjustments define individual curve shape. The square root (√) AUC scale provided the best fit. The mean levels and rates of fall for individuals were normally distributed and uncorrelated with each other. Age at diagnosis and √AUC at 3 months strongly predicted the patient-specific mean levels, while younger age at diagnosis (p<0.0001) and the 120-minute CP value of the 3-month MMTT (p = 0.002) predicted the patient-specific rates of fall. SITAR growth curve analysis is a useful tool to assess CP loss in type 1 diabetes, explaining patient differences in terms of their mean level and rate of fall. A definition of rapid CP loss could be based on a quantile of the rate of fall distribution, allowing better understanding of factors determining CP loss and stratification of patients into targeted therapies.
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影响因子：
8.2
作者：
KNIP, M;ILONEN, J;AKERBLOM, HK
通讯作者：
AKERBLOM, HK
影响因子：
7.7
作者：
Cole TJ;Donaldson MD;Ben-Shlomo Y
通讯作者：
Ben-Shlomo Y
影响因子：
1.7
作者：
Cole TJ;Pan H;Butler GE
通讯作者：
Butler GE
DOI：
10.1136/archdischild-2012-303536
发表时间：
2014-01
期刊：
Archives of disease in childhood. Fetal and neonatal edition
影响因子：
--
作者：
Cole TJ;Statnikov Y;Santhakumaran S;Pan H;Modi N;Neonatal Data Analysis Unit and the Preterm Growth Investigator Group
通讯作者：
Neonatal Data Analysis Unit and the Preterm Growth Investigator Group
影响因子：
3.7
作者：
Lachin, John M.;McGee, Paula L.;Skyler, Jay
通讯作者：
Skyler, Jay