Hippocampal Atrophy on Magnetic Resonance Imaging as a Surrogate Marker for Clinical Benefit and Neurodegeneration in Early Symptomatic Alzheimer’s Disease: Synthesis of Evidence from Observational and Interventional Trials
Bibliographic record
Abstract
Amyloid-plaque reduction is currently the only recognized surrogate outcome for Alzheimer’s disease (AD) trials, allowing accelerated approval of plaque-clearing amyloid antibodies. However, plaque reduction does not facilitate the development of new non-plaque-clearing treatments. The hippocampus is among the first brain regions affected by AD pathology, exhibiting synaptic dysfunction and neurodegeneration that manifests as hippocampal atrophy and memory decline. We evaluated hippocampal volume (HV) as a potential surrogate outcome that can predict clinical benefit in disease-modification trials. Using published data from observational and interventional studies that examined both cognition and HV on volumetric magnetic resonance imaging (vMRI), we evaluated the cross-sectional correlations of HV to cognitive performance, the longitudinal correlations of HV atrophy to cognitive decline, HV sensitivity to drug effects, and the correlations between drug effects on HV atrophy and cognitive decline. We also examined the magnitude of HV protection that corresponds to meaningful clinical benefit. Analyses from 30 observational studies encompassing 13,187 individuals (2633 cognitively normal; 10,554 early AD) showed significant cross-sectional correlations between baseline HV and cognition, and longitudinal correlations between HV atrophy and cognitive decline over ≥ 1 year. The relationship of HV–cognitive drug effects was examined at the group level in nine placebo-controlled trials of five antiamyloid agents that evaluated HV in early AD trials of at least 18 months’ duration. These trials included four amyloid antibodies (aducanumab, lecanemab, donanemab, and gantenerumab) and one oral anti-oligomer agent (valiltramiprosate). Individual-level HV–cognition relationships were examined in two valiltramiprosate studies, one of which included diffusion tensor imaging (DTI) providing microstructural correlates of HV drug effects and helping distinguish neuroprotection from brain edema. Across these anti-amyloid drug trials (total N ~10,000), there was a linear relationship between drug effects on slowing of cognitive decline and slowing of HV atrophy. Two anti-oligomer trials (valiltramiprosate) reported significant subject-level correlations between drug effects on HV and cognition over 18–24 months ( r = −0.40 to −0.44, p < 0.005, N = 50/69), with significant correlations of drug effects on brain microstructure (decreased mean diffusivity) with both HV and cognitive benefits, supporting reduced neurodegeneration. The minimal HV preservation at the mild cognitive impairment (MCI) stage that is associated with clinical benefit is estimated to be ≥ 40 mm 3 or ≥ 10% of atrophy in the placebo arm over 18 months. Our findings demonstrate that hippocampal atrophy is an early indicator of cognitive decline in AD, linked to amyloid and tau-related neurodegeneration. HV on standardized vMRI is sensitive to anti-amyloid treatments, demonstrating strong correlations between slowed hippocampal atrophy and slowed cognitive decline. Data from over 23,000 subjects over three decades support HV as a surrogate marker for predicting clinical benefit in early symptomatic AD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.058 | 0.109 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".