Evidence map›Paper›PMID 28758145›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)2017

Cross-validation of optimized composites for preclinical Alzheimer's disease.

Michael C Donohue, Chung-Kai Sun, Rema Raman, Philip S Insel, Paul S Aisen, AN-ADNI, AIBL, J-ADNI

Abstract read
In one paragraph

Article in Alzheimer's & dementia (New York, N. Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Hypertension acts together with Aβ pathology in late-life to promote memory loss.The journal of prevention of Alzheimer's disease · 2026
    Article
  2. Article
  3. Development of language composites for enhanced sensitivity to multiple plasma biomarkers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  4. Article
  5. Article
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  7. Apolipoprotein E moderates the association between Non-medRxiv : the preprint server for health sciences · 2023
    Article
  8. Article
  9. Article
  10. Article
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  14. Article
  15. Identifying Sensitive Measures of Cognitive Decline at Different Clinical Stages of Alzheimer's Disease.Journal of the International Neuropsychological Society : JINS · 2021
    Article
  16. Article
  17. Measuring longitudinal cognition: Individual tests versus composites.Alzheimer's & dementia (Amsterdam, Netherlands) · 2019
    Article
  18. Article
  19. Article
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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

8 authors.

Michael C DonohueAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA.
Chung-Kai SunAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA.
Rema RamanAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA.
Philip S InselUniversity of Lund, Sweden.
Paul S AisenAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA.
AN-ADNI
AIBL
J-ADNI

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Estimating Long-Term Disease Trajectories from Short-Term DataR01AG049750 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI DONOHUE, MICHAEL C · 2016 to 2019
$1.6M
NIA NIH HHS R01 AG049750NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

introductionWe discuss optimization and validation of composite endpoints for pre-symptomatic Alzheimer's clinical trials. Optimized composites offer hope of substantial gains in statistical power or reduction in sample size. But there is tradeoff between optimization and face validity such that optimization should only be considered if there is a convincing rationale. As with statistically derived regions of interest in neuroimaging, validation on independent datasets is essential.

methodsUsing four datasets, we consider the optimized weighting of four components of a cognitive composite which includes measures of (1) global cognition, (2) semantic memory, (3) episodic memory, and (4) executive function. Weights are optimized to either discriminate amyloid positivity or maximize power to detect a treatment effect in an amyloid positive population. We apply repeated 5×3-fold cross-validation to quantify the out-of-sample performance of optimized composite endpoints.

resultsWe found the optimized weights varied greatly across the folds of the cross validation with either optimization method. Both optimization methods tend to down-weight the measures of global cognition and executive function. However when these optimized composites were applied to the validation sets, they did not provide consistent improvements in power. In fact, overall, the optimized composites performed worse than those without optimization. DISCUSSION: We find that component weight optimization does not yield valid improvements in sensitivity of this composite to detect treatment effects.

Indexed as

cognitive compositesendpoint validationpreclinical Alzheimer’s

Identifiers

PMID28758145
PMCPMC5527287

What OpenQuestion holds

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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.