Individualized optimization of the screening interval for diabetic retinopathy: a new model
Individualized optimization of the screening interval for diabetic retinopathy: a new model
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DOI：
10.1111/j.1755-3768.2010.01882.x
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发表时间：
2012-03-01
影响因子：
3.4
通讯作者：
Bek, Toke
中科院分区：
文献类型：
--
作者：
Mehlsen, Jesper;Erlandsen, Mogens;Bek, Toke
简介：糖尿病视网膜病变的筛查计划遵循指南，确保即使疾病进展迅速，也能检测到威胁视力的并发症。这意味着，疾病进展缓慢的患者将被推荐的检查更经常比need.Method：在以前定义的个人风险因素的基础上，多元Logistic回归被用来开发一个模型，用于个性化的确定糖尿病视网膜病变的筛查间隔，同时调整的事实，即在用于构建模型的数据集，筛查间隔作为一个时间依赖性的混杂因素。对2000年筛查的1372例患者进行了检验。结果：对于建议筛查间隔时间大于12个月的低危患者，可以建立一个计算最佳筛查间隔时间的模型。当达到需要治疗事件的概率设定为0.5%时，在模型验证中没有患者达到治疗终点，1型糖尿病患者的筛选间隔平均延长2.9倍，2型糖尿病患者延长1.2倍。该模型的预测强度取决于变量的数量included.Conclusions：它是可能的，以构建一个模型，用于优化检查间隔在筛选糖尿病视网膜病变的低风险患者。该模型可以通过识别未知或未测量的混杂因素，并通过在进行预测的基础上在检查之前和之后包括风险因素的知识来改进。
Introduction: Screening programmes for diabetic retinopathy follow guidelines that ensure that vision-threatening complications are detected even when the disease progression is fast. This implies that patients with slow disease progression will be recommended examinations more often than needed.Method: On the basis of previously defined individual risk factors, multiple logistic regression was used to develop a model for individualized determination of the screening interval in diabetic retinopathy, while adjusting for the fact that in the data set used to construct the model, the screening interval acted as a time-dependent confounder. The model was tested on 1372 patients screened during year 2000.Results: It was possible to construct a model for calculating the optimal screening interval in low-risk patients in whom the recommended screening interval was longer than 12 months. When the probability of reaching a treatment requiring event was set to 0.5%, none of the patients reached a treatment end-point in a validation of the model, and the screening interval was prolonged on average 2.9 times in patients with type 1 diabetes and 1.2 times in those with type 2 diabetes. The predictive strength of the model depended on the number of variables included.Conclusions: It is possible to construct a model for optimizing the examination interval during screening for diabetic retinopathy in low-risk patients. The model can potentially be improved by identifying unknown or unmeasured confounders and by including knowledge of risk factors before and after the examination on the basis of which the prediction is made.