Multinational Collaborative Evaluation of Corneal Confocal Microscopy as a Surrogate Endpoint for the Identification and Prediction of Diabetic Neuropathy in Type 1 Diabetes

 描述（由申请人提供）：周围神经弥漫性损伤（糖尿病性神经病变）在1型糖尿病中异常常见，但在晚期进展为麻烦且昂贵的足部感染、溃疡和截肢之前，缺乏客观的替代标志物来识别治疗可能最有效的早期亚临床阶段。与客观测量视网膜病变和肾病的疾病特异性替代标志物的能力相反，糖尿病神经病变替代标志物的缺乏严重阻碍了临床研究试验中特定干预措施的发展。我们代表5个独立的研究小组，共同创建了一个致力于开发早期糖尿病神经病变替代标志物的研究者联盟，我们专注于使用眼睛作为一个窗口，通过体内角膜共聚焦显微镜（CCM）的方法对支配角膜的小神经纤维进行非侵入性成像。我们已经证明，这些神经纤维末梢的变化发生在神经病变的发展早期，反映了其他周围神经的变化，通过侵入性皮肤活检评估，他们的测量是可行的和可重复的。作为一个跨国财团，我们在汇集多个队列的建议中受益，以在生物标志物开发中应用最有效的研究方法。首先，我们的目标是在分析516例1型和524例2型糖尿病受试者的现有汇总数据集时，确定可以识别糖尿病神经病变存在的CCM测量的确切水平。其次，我们建议在三年内重新检查至少70%的该队列，这将提供5至7年的随访数据，以确定哪种类型和水平的CCM测量可以预测未来神经病变的发作，以及基线时患有神经病变的患者的进展。最后，我们将评估节省时间和成本的自动图像分析软件的作用。由于数据汇集的大样本量，我们独特地获得了通过单独的推导和验证分析集来确认我们的目标的方法学能力。通过一个独特的和前所未有的多国汇总数据集的方法，糖尿病神经病变，这项工作将推导和验证特定的CCM参数阈值，用于识别神经病变，更重要的是，识别个人在未来的风险。这些结果将允许应用于神经病变风险分层的临床实践和干预试验。自动化图像分析的评价将影响这种替代生物标志物成功转化为临床实践的可能性-其中该程序可以与年度视网膜检查协调-以及干预试验。

 DESCRIPTION (provided by applicant): The diffuse injury to peripheral nerves (diabetic neuropathy) is exceptionally common in type 1 diabetes, but there is a lack of an objective surrogate marker to identify early subclinical stages when treatments might be most effective, prior to late-stage progression to troublesome and costly foot infection, ulceration, and limb amputation. In contrast to the ability to objectively measure disease-specific surrogate markers for retinopathy and nephropathy, this lack of a diabetic neuropathy surrogate marker has seriously impeded the development of specific interventions in clinical research trials. Representing 5 independent research groups that have together created a consortium of investigators dedicated to the development of a surrogate marker for early diabetic neuropathy, we have focused on using the eye as a window to non-invasively image by a method of in-vivo corneal confocal microscopy (CCM) the small nerve fibres that innervate the cornea. We have demonstrated that changes in these nerve fibre endings occur early in the development of neuropathy, reflect well the changes seen in other peripheral nerves by invasive skin biopsy evaluation, and that their measurement is feasible and reproducible. As a multinational consortium, we have the benefit in this proposal of pooling multiple cohorts to apply the most valid study methods in biomarker development. First, we aim to determine in the analysis of an existing pooled dataset of 516 type 1 and 524 type 2 diabetes subjects the exact levels of CCM measurement that can identify the presence of diabetic neuropathy. Secondly, we propose over three years to re- examine at least 70% of this cohort, which will provide 5- to 7-year follow-up data to determine which type and level of CCM measurement can predict the future onset of neuropathy, as well as its progression in those who had neuropathy at baseline. Finally, we will evaluate the role of time- and cost-saving automated image analysis software. By virtue of large sample size from data pooling, we are uniquely afforded the methodological power to confirm our objectives by way of separate derivation and validation analysis sets. Through a unique and unprecedented multinational pooled dataset approach for diabetic neuropathy, this work will derive and validate specific CCM parameter thresholds for the identification of neuropathy, and - more importantly - the identification of individuals at future risk. These results will permit application in clinical practice and intervention trials for neuropathy risk stratification. Evaluaion of automated image analysis will influence likelihood of successful knowledge translation of this surrogate biomarker into clinical practice - in which the procedure could be harmonized with annual retinal examinations - and into intervention trials.