Sung Valerie, Williams Katrina, Perlow Ella, Hu Yanhong J, Ahern Susannah, Said Joanne M, Karanatsios Bill, Hopper John L, McNeil John J, Donnan Leo, Goldfeld Sharon, Wake Melissa
Murdoch Children's Research Institute, Melbourne 3052, Australia.
Department of Paediatrics, The University of Melbourne, Melbourne 3052, Australia.
Children (Basel). 2021 Apr 7;8(4):285. doi: 10.3390/children8040285.
Health registries are critical to understanding, benchmarking and improving quality of care for specific diseases and conditions, but face hurdles including funding, bias towards clinical rather than population samples, lack of pre-morbid and outcomes data, and absent cross-registry harmonisation and coordination. Children are particularly under-represented in registry research. This paper lays out novel principles, methods and governance to integrate diverse registries within or alongside a planned children's mega-cohort to rapidly generate translatable evidence. GenV (Generation Victoria) will approach for recruitment parents of all newborns (estimated 150,000) over two years from mid-2021 in the state of Victoria (population 6.5 million), Australia. Its sample size and population denominator mean it will contain almost all children with uncommon or co-morbid conditions as they emerge over time. By design, it will include linked datasets, biosamples (including from pregnancy), phenotypes and participant-reported measures, all of which will span pre-morbid to long-term outcomes. We provide a vignette of a planned new registry for high-risk pregnancies to illustrate the possibilities. To our knowledge, this is the first paper to describe such a methodology designed prospectively to enhance both the clinical relevance of a large multipurpose cohort and the value and inclusivity of registries in a population.
健康登记对于了解、衡量和改善特定疾病和病症的护理质量至关重要，但面临诸多障碍，包括资金问题、偏向临床样本而非人群样本、缺乏病前和结局数据，以及缺乏跨登记处的协调统一。儿童在登记研究中的代表性尤其不足。本文提出了新的原则、方法和治理措施，以将各种登记处整合到一个计划中的儿童大型队列中或与之并行，从而迅速生成可转化的证据。“维多利亚一代”（GenV）将从2021年年中开始，在澳大利亚维多利亚州（人口650万）用两年时间招募所有新生儿（估计15万名）的父母。其样本量和总体分母意味着随着时间推移，它将涵盖几乎所有患有罕见或合并病症的儿童。从设计上看，它将包括关联数据集、生物样本（包括孕期样本）、表型和参与者报告的测量数据，所有这些都将涵盖病前到长期结局。我们提供了一个针对高危妊娠的计划新登记处的示例，以说明其可能性。据我们所知，这是第一篇描述这种前瞻性设计方法的论文，该方法既能增强大型多用途队列的临床相关性，又能提高登记处在人群中的价值和包容性。
