Evidence map›Paper›PMID 42492033›Full record

SynthesisNeurology2026

Efficacy Measures Used in Alzheimer Disease Clinical Trials Between 2015 and 2025: A Systematic Review.

Can Li, Mengyuan Fu, Karina Berg, Joshua Wallach, Kexin Ling, Ran Wei, Luwen Shi, Joseph Ross, Xiaodong Guan

Abstract readSystematic Review
In one paragraph

Synthesis in Neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Can LiDepartment of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.ORCID 0000-0002-7605-326X
Mengyuan FuInternational Research Center for Medicinal Administration, Peking University, Beijing, China.ORCID 0000-0001-9703-8408
Karina BergCenter on Aging, Department of Medicine, University of Connecticut School of Medicine, Farmington, CT.ORCID 0009-0009-4767-7995
Joshua WallachDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.ORCID 0000-0002-2816-6905
Kexin LingDepartment of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.ORCID 0009-0007-0557-2154
Ran WeiDepartment of Pharmacy, Peking University First Hospital, Beijing, China.ORCID 0000-0002-0586-9560
Luwen ShiDepartment of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.ORCID 0000-0003-2683-6685
Joseph RossDepartment of Internal Medicine, Yale School of Medicine, New Haven, CT.ORCID 0000-0002-9218-3320
Xiaodong GuanDepartment of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.ORCID 0000-0002-1290-3827

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesRegulatory guidance has long emphasized clinically meaningful outcomes in Alzheimer disease (AD) drug trials. No contemporary review has examined the efficacy measures used for clinical trials of AD therapies. The objective of this study was to evaluate the clinical relevance and heterogeneity of efficacy measures used in phase II-IV AD drug trials over the past decade.

methodsWe systematically searched PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. All phase II-IV clinical trials of pharmacologic therapies in individuals with mild cognitive impairment due to AD or mild-to-moderate AD that were published, completed, or terminated between January 1, 2015, and November 15, 2025, or still ongoing as of November 15, 2025, were eligible for inclusion. We summarized the proportion of trials using clinical outcomes or biomarkers as primary or secondary efficacy measures, key clinical domains addressed, and the number of distinct measures using descriptive statistics. This study is registered with PROSPERO (CRD420251032087).

resultsAmong 238 included trials, 95.4% (227/238) used at least one clinical outcome and 73.5% (175/238) used at least one biomarker as efficacy measures. Cognitive abilities (87.0%, 207/238), global status (76.9%, 183/238), and functional ability (71.4%, 170/238) were the most frequently measured clinical domains, whereas patient (16.0%, 38/238) and caregiver (8.8%, 21/238) quality of life and significant disease-related life events (2.5%, 6/238) were less frequent. Only 21.8% (52/238) of trials adopted regulatory-recommended co-primary measures of cognition with either function or global status, whereas 8.4% (20/238) used biomarkers as the sole primary efficacy measure. We identified 318 distinct clinical outcome measures and 219 distinct biomarkers used across all trials, 6.9% (22/318) and 6.8% (15/219) of which were used in more than 5% of trials. DISCUSSION: Efficacy measures in AD drug trials primarily focused on cognition, global status, and functional outcomes, which are important indicators of AD progression. However, other clinical domains that may also be meaningful to patients and caregivers were far less frequently assessed, while biomarker use is widespread. Substantial heterogeneity in efficacy measure use limits comparability across trials and highlights the need for standardized, consensus-based, clinically meaningful core measure sets for AD drug trials.

Indexed as

Alzheimer DiseaseClinical Trials as TopicOutcome Assessment, Health CareBiomarkersCognitive DysfunctionHumansTreatment OutcomeBiomarkers

Identifiers

PMID42492033
PMCPMC13445500

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.