Which MCI Patients Should be Included in Prodromal Alzheimer Disease Clinical Trials?

Abstract

Background: Prodromal Alzheimer's disease (AD) clinical trials enroll patients with Mild Cognitive Impairment (MCI) meeting biomarker criteria, but specific enrollment criteria vary among trials. Methods: We used data from AD Neuroimaging Initiative (ADNI) MCI participants to assess AD biomarker eligibility, variation in trial outcome measures, and statistical power. Results: Most (65%) participants meet eligibility criteria based on low cerebrospinal fluid (CSF) amyloid beta (Aβ). Relative to trials enrolling exclusively based on low CSF Aβ, trials including participants with a high ratio of phosphorylated tau (p-Tau) to Aβ would include an additional 15% of participants. Fewer (34-62%) participants met criteria for Aβ and tau. Differences in clinical and demographic characteristics of modeled trial samples were minimal. Those with low Aβ and high tau showed the greatest change over time on outcome measures. Conclusions: Eligibility rates for prodromal trials vary depending on the specific biomarker criteria, though differences in demographics and the variation associated with outcome measures are minimal. Broadening inclusion criteria beyond amyloid alone may facilitate recruitment but include patients showing slower progression over time. Biomarker criteria selection should be

Anterolateral entorhinal cortex thickness as a new biomarker for early detection of Alzheimer's disease

“…Given positive results, we motivate future research by asking the secondary question whether differential associations between CSF amyloid levels and aLEC/pMEC CTs provides explanatory power for primary analysis results. Based on prior work, 36‐39 Model 4 considers the ratio between p‐tau and amyloid beta (Aß) binarized at the threshold 0.1 as predictor for CT in aLEC and pMEC subregions. All models are outlined in Table 1.…”

Anterolateral entorhinal cortex thickness as a new biomarker for early detection of Alzheimer’s disease

“…Given positive results, we motivate future research by asking the secondary question whether differential associations between CSF amyloid levels and aLEC/pMEC CTs provides explanatory power for primary analysis results. Based on prior work 36–39 , Model 4 considers the ratio between p-tau and Aß binarized at the threshold 0.1 as predictor for CT in aLEC and pMEC subregions. All models are outlined in Supplementary Table 1 .…”

“…Given positive results, we motivate future research by asking the secondary question whether differential associations between CSF amyloid levels and aLEC/pMEC CTs provides explanatory power for primary analysis results. Based on prior work [36][37][38][39] , Model 4 considers the ratio between p-tau and Aß binarized at the threshold 0.1 as . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.…”

“…We look at the longitudinal progressions of aLEC and pMEC thicknesses as a function of the binary threshold given by the ratio of phosphorylated tau-181 (p-tau) to amyloid beta (Aß) being greater than 0.1 [36][37][38][39] . These CSF data are available for a smaller 238 subject (70 healthy; 119 MCI; 49 AD) subset of the data used in the primary analyses.…”

Digital biomarker‐based individualized prognosis for people at risk of dementia

“…To identify the size of the dataset necessary for obtaining a clinically relevant analysis, we used the information available from NC and MCI participants in our previous study 20 . Using Clinical Dementia Rating scale sum of boxes (CDR‐SB) as an outcome at 40 months, a minimum of 200 individuals per class was needed to demonstrate difference in the longitudinal disease progression, that is, stability over time or significant changes toward dementia, in keeping with the recent literature 28 . To assess real‐world performance, the NMI models were trained on the entire Study A dataset and then evaluated on data derived from Study B and compared to actual diagnoses, asking whether NMI can predict their later diagnoses.…”