Evidence map›Paper›PMID 29971228›Full record

ArticleFrontiers in public health2018

Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies.

Joanne Ryan, Peter Fransquet, Jo Wrigglesworth, Paul Lacaze

Abstract read
In one paragraph

Article in Frontiers in public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–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

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Encoding Discordance in the Alzheimer's Disease A/T/N Framework.medRxiv : the preprint server for health sciences · 2026
    Article
  5. Dementia etiology classification using NULISA plasma biomarkers and machine learning.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
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  15. Adaptive Subtype and Stage Inference for Alzheimer's Disease.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2024
    Article
  16. Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  17. Review
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  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

4 authors.

Joanne RyanDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Peter FransquetDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Jo WrigglesworthDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Paul LacazeDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and can only be made definitively post-mortem with histopathological confirmation. These inherent difficulties combined with the overlap of some symptoms and even neuropathological features, present a challenging problem for research in the field. This has likely hampered progress in epidemiological studies of risk factors and preventative interventions, as well as genetic and biomarker research. Resource limitations in large epidemiologically studies mean that limited diagnostic criteria are often used, which can result in phenotypically heterogeneous disease states being grouped together, potentially resulting in misclassification bias. When biomarkers are identified for etiologically heterogeneous diseases, they will have low specificity for any utility in clinical practice, even if their sensitivity is high. We highlight several challenges in in the field which must be addressed for the success of future genetic and biomarker studies, and may be key to the development of the most effective treatments. As a step toward achieving this goal, defining the dementia as a biological construct based on the presence of specific pathological features, rather than clinical symptoms, will enable more precise predictive models. It has the potential to lead to the discovery of novel genetic variants, as well as the identification of individuals at heightened risk of the disease, even prior to the appearance of clinical symptoms.

Indexed as

Alzheimer's diseasebiomarkersclinical symptomsdementiadiagnosisheterogeneitypathophysiology

Identifiers

PMID29971228
PMCPMC6018385

What OpenQuestion holds

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Registered trials

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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.