Evidence map›Paper›PMID 35765300›Full record

ArticleThe annals of applied statistics2022

BAGEL: A BAYESIAN GRAPHICAL MODEL FOR INFERRING DRUG EFFECT LONGITUDINALLY ON DEPRESSION IN PEOPLE WITH HIV.

Yuliang Li, Yang Ni, Leah H Rubin, Amanda B Spence, Yanxun Xu

Open access · greenAbstract read
In one paragraph

Article in The annals of applied statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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

5 authors at 3 institutions in 1 country.

Yuliang LiDepartment of Applied Mathematics and Statistics, Johns Hopkins University.
Yang NiDepartment of Statistics, Texas A&M University.
Leah H RubinDepartments of Neurology and Psychiatry, Johns Hopkins University School of Medicine.
Amanda B SpenceDepartment of Medicine, Georgetown University.
Yanxun XuDepartment of Applied Mathematics and Statistics, Johns Hopkins University.
Johns Hopkins University · USGeorgetown University · USTexas A&M University · US

Funding

Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
Clinical Research Sites for the MACS/WIHS Combined Cohort Study (MACS/WIHS-CCS) - Baltimore/Wash DC Center - Admin Supplement: Vision and dual sensory loss in HIV-infected older adultsU01HL146201 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TODD T BROWN, Joseph B. Margolick · 2019 to 2026
$33.7M
NHLBI NIH HHS U01 HL146201NIAID NIH HHS P30 AI094189
6 · The paper itself

Abstract

Access and adherence to antiretroviral therapy (ART) has transformed the face of HIV infection from a fatal to a chronic disease. However, ART is also known for its side effects. Studies have reported that ART is associated with depressive symptomatology. Large-scale HIV clinical databases with individuals' longitudinal depression records, ART medications, and clinical characteristics offer researchers unprecedented opportunities to study the effects of ART drugs on depression over time. We develop BAGEL, a Bayesian graphical model to investigate longitudinal effects of ART drugs on a range of depressive symptoms while adjusting for participants' demographic, behavior, and clinical characteristics, and taking into account the heterogeneous population through a Bayesian nonparametric prior. We evaluate BAGEL through simulation studies. Application to a dataset from the Women's Interagency HIV Study yields interpretable and clinically useful results. BAGEL not only can improve our understanding of ART drugs effects on disparate depression symptoms, but also has clinical utility in guiding informed and effective treatment selection to facilitate precision medicine in HIV.

Indexed as

Bayesian nonparametricsDepressionGraphical modelLongitudinal cohort studyPrecision medicine

Identifiers

PMID35765300
PMCPMC9236217
OpenAlexW3039828472

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.