Evidence map›Paper›PMID 38701142›Full record

ArticleJournal of Alzheimer's disease : JAD2024

Associations Between Neuroinflammation-Related Conditions and Alzheimer's Disease: A Study of US Insurance Claims Data.

Jing Xu, Yao Chen, Yi Shi, Anna Sun, Yuedi Yang, Malaz Boustani, Jing Su, Pengyue Zhang

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Jing XuDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
Yao ChenDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
Yi ShiDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
Anna SunDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
Yuedi YangDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
Malaz BoustaniIndiana University Center for Health Innovation and Implementation Science, School of Medicine, Indianapolis, IN, USA.
Jing SuDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
Pengyue ZhangDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.

Funding

Revealing Health Trajectories of Chronic Kidney Disease for Precision MedicineR01LM013771 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI SU, JING, ZHANG, PENGYUE · 2022 to 2025
$1.7M
NLM NIH HHS R01 LM013771
6 · The paper itself

Abstract

Background: Early detection of Alzheimer's disease (AD) is a key component for the success of the recently approved lecanemab and aducanumab. Patients with neuroinflammation-related conditions are associated with a higher risk for developing AD. Objective: Investigate the incidence of AD among patients with neuroinflammation-related conditions including epilepsy, hemorrhage stroke, multiple sclerosis (MS), and traumatic brain injury (TBI). Methods: We used Optum's de-identified Clinformatics Data Mart Database (CDM). We derived covariate-matched cohorts including patients with neuroinflammation-related conditions and controls without the corresponding condition. The matched cohorts were: 1) patients with epilepsy and controls (N = 67,825 matched pairs); 2) patients with hemorrhage stroke and controls (N = 81,510 matched pairs); 3) patients with MS and controls (N = 9,853 matched pairs); and 4) patients TBI and controls (N = 104,637 matched pairs). We used the Cox model to investigate the associations between neuroinflammation-related conditions and AD. Results: We identified that epilepsy, hemorrhage stroke, and TBI were associated with increased risks of AD in both males and females (hazard ratios [HRs]≥1.74, p < 0.001), as well as in gender- and race-conscious subpopulations (HRs≥1.64, p < 0.001). We identified that MS was associated with increased risks of AD in both males and females (HRs≥1.47, p≤0.004), while gender- and race-conscious subgroup analysis shown mixed associations. Conclusions: Patients with epilepsy, hemorrhage stroke, MS, and/or TBI are associated with a higher risk of developing AD. More attention on cognitive status should be given to older patients with these conditions.

Indexed as

Alzheimer DiseaseEpilepsyAdultAgedAged, 80 and overBrain Injuries, TraumaticCohort StudiesDatabases, FactualFemaleHemorrhagic StrokeHumansIncidenceInsurance Claim ReviewMaleMiddle AgedMultiple SclerosisAlzheimer’s diseaseepilepsyhemorrhagic strokemultiple sclerosisneuroinflammatory diseasetraumatic brain injury

Identifiers

PMID38701142
PMCPMC11228456

What OpenQuestion holds

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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.