Browsing by Author "Galvin, James E."

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    Avoid or Embrace? Practice Effects in Alzheimer’s Disease Prevention Trials
    (Frontiers Media, 2022-06-16) Aschenbrenner, Andrew J.; Hassenstab, Jason; Wang, Guoqiao; Li, Yan; Xiong, Chengjie; McDade, Eric; Clifford, David B.; Salloway, Stephen; Farlow, Martin; Yaari, Roy; Cheng, Eden Y. J.; Holdridge, Karen C.; Mummery, Catherine J.; Masters, Colin L.; Hsiung, Ging-Yuek; Surti, Ghulam; Day, Gregory S.; Weintraub, Sandra; Honig, Lawrence S.; Galvin, James E.; Ringman, John M.; Brooks, William S.; Fox, Nick C.; Snyder, Peter J.; Suzuki, Kazushi; Shimada, Hiroyuki; Gräber, Susanne; Bateman, Randall J.; Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU); Neurology, School of Medicine
    Demonstrating a slowing in the rate of cognitive decline is a common outcome measure in clinical trials in Alzheimer's disease (AD). Selection of cognitive endpoints typically includes modeling candidate outcome measures in the many, richly phenotyped observational cohort studies available. An important part of choosing cognitive endpoints is a consideration of improvements in performance due to repeated cognitive testing (termed "practice effects"). As primary and secondary AD prevention trials are comprised predominantly of cognitively unimpaired participants, practice effects may be substantial and may have considerable impact on detecting cognitive change. The extent to which practice effects in AD prevention trials are similar to those from observational studies and how these potential differences impact trials is unknown. In the current study, we analyzed data from the recently completed DIAN-TU-001 clinical trial (TU) and the associated DIAN-Observational (OBS) study. Results indicated that asymptomatic mutation carriers in the TU exhibited persistent practice effects on several key outcomes spanning the entire trial duration. Critically, these practice related improvements were larger on certain tests in the TU relative to matched participants from the OBS study. Our results suggest that the magnitude of practice effects may not be captured by modeling potential endpoints in observational studies where assessments are typically less frequent and drug expectancy effects are absent. Using alternate instrument forms (represented in our study by computerized tasks) may partly mitigate practice effects in clinical trials but incorporating practice effects as outcomes may also be viable. Thus, investigators must carefully consider practice effects (either by minimizing them or modeling them directly) when designing cognitive endpoint AD prevention trials by utilizing trial data with similar assessment frequencies.
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    Digital detection of dementia (D3): a study protocol for a pragmatic cluster-randomized trial examining the application of patient-reported outcomes and passive clinical decision support systems
    (MDPI, 2022-10-11) Kleiman, Michael J.; Plewes, Abbi D.; Owora, Arthur; Grout, Randall W.; Dexter, Paul Richard; Fowler, Nicole R.; Galvin, James E.; Ben Miled, Zina; Boustani, Malaz; Medicine, School of Medicine
    Background: Early detection of Alzheimer's disease and related dementias (ADRD) in a primary care setting is challenging due to time constraints and stigma. The implementation of scalable, sustainable, and patient-driven processes may improve early detection of ADRD; however, there are competing approaches; information may be obtained either directly from a patient (e.g., through a questionnaire) or passively using electronic health record (EHR) data. In this study, we aim to identify the benefit of a combined approach using a pragmatic cluster-randomized clinical trial. Methods: We have developed a Passive Digital Marker (PDM), based on machine learning algorithms applied to EHR data, and paired it with a patient-reported outcome (the Quick Dementia Rating Scale or QDRS) to rapidly share an identified risk of impairment to a patient's physician. Clinics in both south Florida and Indiana will be randomly assigned to one of three study arms: 1200 patients in each of the two populations will be administered either the PDM, the PDM with the QDRS, or neither, for a total of 7200 patients across all clinics and populations. Both incidence of ADRD diagnosis and acceptance into ADRD diagnostic work-up regimens is hypothesized to increase when patients are administered both the PDM and QDRS. Physicians performing the work-up regimens will be blind to the study arm of the patient. Discussion: This study aims to test the accuracy and effectiveness of the two scalable approaches (PDM and QDRS) for the early detection of ADRD among older adults attending primary care practices. The data obtained in this study may lead to national early detection and management program for ADRD as an efficient and beneficial method of reducing the current and future burden of ADRD, as well as improving the annual rate of newly documented ADRD in primary care practices.