Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada.
Departments of Pediatrics and Clinical Genetics, Amsterdam University Medical Centres, Amsterdam, the Netherlands.
Dev Med Child Neurol. 2019 Oct;61(10):1208-1213. doi: 10.1111/dmcn.14180. Epub 2019 Mar 14.
To create a classification system for severe, rare, and progressive genetic conditions for use in research reporting.
A modified Delphi consensus technique was used to create and reach agreement on a new system of condition categories. Interrater reliability was tested via two rounds of an online survey whereby physicians classified a subset of conditions using our novel system. Overall percentage agreement and agreement above chance were calculated using Fleiss' kappa (κ).
Eleven physicians completed the first Delphi, with an overall agreement of 76.4%, the κ value was 0.57 (95% confidence interval 0.51-0.63), indicating moderate agreement (0.41-0.60) above chance. Based on the first survey several categories were described in more detail. The second survey confirmed a classification system with 12 categories, with an overall percentage agreement among the participants of 82.6%. The overall mean κ value was 0.71 (95% confidence interval 0.65-0.77), indicating substantial agreement (0.61-0.80).
Our new system was useful in categorizing a broad range of rare childhood diseases and may be applicable to other rare disease studies; further validation in larger cohorts is required.
This novel 12-category classification system can be used in research reporting in rare and progressive genetic conditions.
创建一个用于研究报告的严重、罕见和进行性遗传疾病分类系统。
采用改良的 Delphi 共识技术创建并达成新的疾病类别系统的共识。通过两轮在线调查测试了观察者间的可靠性，医生使用我们的新系统对一组条件进行分类。使用 Fleiss' kappa（κ）计算总体百分比一致性和一致性超过机会的一致性。
11 名医生完成了第一次 Delphi，总体一致性为 76.4%，κ 值为 0.57（95%置信区间为 0.51-0.63），表明存在中度一致性（0.41-0.60）超过机会。根据第一次调查，对几个类别进行了更详细的描述。第二次调查确认了一个包含 12 个类别的分类系统，参与者的总体百分比一致性为 82.6%。总体平均κ值为 0.71（95%置信区间为 0.65-0.77），表明存在高度一致性（0.61-0.80）。
我们的新系统可用于对广泛的罕见儿童疾病进行分类，可能适用于其他罕见疾病研究；需要在更大的队列中进一步验证。
这个新的 12 类别分类系统可用于罕见和进行性遗传疾病的研究报告。
