A semi-automated pipeline for fulfillment of resource requests from a longitudinal Alzheimer's disease registry

Abstract

Objective Managing registries with continual data collection poses challenges, such as following reproducible research protocols and guaranteeing data accessibility. The University of Kansas (KU) Alzheimer’s Disease Center (ADC) maintains one such registry: Curated Clinical Cohort Phenotypes and Observations (C3PO). We created an automated and reproducible process by which investigators have access to C3PO data. Materials and Methods Data was input into Research Electronic Data Capture. Monthly, data part of the Uniform Data Set (UDS), that is data also collected at other ADCs, was uploaded to the National Alzheimer’s Coordinating Center (NACC). Quarterly, NACC cleaned, curated, and returned the UDS to the KU Data Management and Statistics (DMS) Core, where it was stored in C3PO with other quarterly curated site-specific data. Investigators seeking to utilize C3PO submitted a research proposal and requested variables via the publicly accessible and searchable data dictionary. The DMS Core used this variable list and an automated SAS program to create a subset of C3PO. Results C3PO contained 1913 variables stored in 15 datasets. From 2017 to 2018, 38 data requests were completed for several KU departments and other research institutions. Completing data requests became more efficient; C3PO subsets were produced in under 10 seconds. Discussion The data management strategy outlined above facilitated reproducible research practices, which is fundamental to the future of research as it allows replication and verification to occur. Conclusion We created a transparent, automated, and efficient process of extracting subsets of data from a registry where data was changing daily.

CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database

“…Handling of UDS data is described in our prior work. 20 For diagnostic consensus reporting, we mostly utilize UDS 3.0 data from the cognitive test and CDR visits. More detailed recruitment methods and protocols were reported under these papers.…”

CONSENSUS: A Shiny application of Dementia evaluation and reporting for the KU ADC Longitudinal Clinical Cohort Database.

“…These test scores and summary of the neuropsychological battery also follows NACC guidelines to satisfy the standard UDS 3.0 requirements, [12,15]. The number of variables listed for the ADC UDS requirements and the other dataset collection is further illustrated at Katelyn et al paper, [14]. For Consensus reporting, we mostly utilize UDS 3.0 data from the cognitive test and CDR visits.…”

CONSENSUS: A Shiny application of Dementia evaluation and reporting for the KU ADC Longitudinal Clinical Cohort Database.

“…The KU ADC Clinical Cohort is a longitudinal study involving the collection of annual clinical and neuropsychological assessments, for participants with and without dementia [12], [13]. Participants enrolled in the KU ADC Clinical Cohort study receive the required NACC UDS assessments, regulated by NACC guidelines [15], [16], along with several other KU speci c items collected for site speci c research questions and to aid with operational components of the study. These longitudinal questionnaires and instruments are captured during the participants' initial visit and subsequent follow-up visits, administered by highly trained research personnel, clinicians, and psychometrists.…”

“…A Neuropsychological test battery is also performed by a trained psychometrist following a standardized testing method [12], [13]. These test scores and summary of the neuropsychological battery also follows NACC guidelines to satisfy the standard UDS 3.0 requirements [12], [15]. The number of variables listed for the ADC UDS requirements and the other dataset collection is further illustrated at Katelyn et al paper [14].…”