Evidence map›Paper›PMID 32204991›Full record

Observational studyAnnals of epidemiology2020

Cholesterol-lowering effect of statin therapy in a clinical HIV cohort: an application of double propensity score adjustment.

Matthew E Levy, Yan Ma, Manya Magnus, Naji Younes, Amanda D Castel, DC Cohort Executive Committee

Open access · greenAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Annals of epidemiology, 2020. 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, top 97% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Observational
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

6 authors at 2 institutions in 1 country.

Matthew E LevyDepartment of Epidemiology, Milken Institute School of Public Health at the George Washington University, Washington, DC. Electronic address: mattelevy@gwu.edu.
Yan MaDepartment of Biostatistics and Bioinformatics, Milken Institute School of Public Health at the George Washington University, Washington, DC.
Manya MagnusDepartment of Epidemiology, Milken Institute School of Public Health at the George Washington University, Washington, DC.
Naji YounesDepartment of Biostatistics and Bioinformatics, Milken Institute School of Public Health at the George Washington University, Washington, DC.
Amanda D CastelDepartment of Epidemiology, Milken Institute School of Public Health at the George Washington University, Washington, DC.
DC Cohort Executive Committee
George Washington University · USMilken Institute · US

Funding

Terry Beirn CPCRA Clinical Trials UnitUM1AI069503 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI KAN, VIRGINIA · 2012 to 2020
$38.5M
The DC Cohort: A Longitudinal Population-Based Cohort Study of People Living with HIV in Washington, DCR24AI152598 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI Amanda Derryck Castel, Marinella Temprosa · 2020 to 2026
$37.9M
CPCRA Clinical Trials UnitU01AI069503 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI GORDIN, FRED M · 2007 to 2011
$33.9M
SWG 2: Cure Research Scientific Working GroupP30AI117970 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI Italo Mocchetti · 2015 to 2026
$29.6M
Data Driven Methods for Missing Data Imputation in Surgical Disparities ResearchR01MD013901 · NIMHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MA, YAN · 2019 to 2022
$996k
NIAID NIH HHS P30 AI117970NIAID NIH HHS R24 AI152598NIAID NIH HHS U01 AI069503NIAID NIH HHS UM1 AI069503NIMHD NIH HHS R01 MD013901
6 · The paper itself

Abstract

purposePropensity score matching (PSM) is often used to estimate the average treatment effect among the treated (ATT) using observational data. We demonstrate how the use of "double propensity score adjustment" can reduce residual confounding and avoid bias due to incomplete matching compared with traditional PSM methods.

methodsThe DC Cohort is an observational clinical HIV cohort in Washington, DC. We compared the mean percent change in non-high-density lipoprotein cholesterol (non-HDL-C) concentration after 3-12 months between participants treated and participants not treated with statin therapy between 2011 and 2018. We conducted traditional PSM procedures (optimal, nearest neighbor, and nearest neighbor caliper matching) and double propensity score adjustment.

resultsAmong 202 treated and 1252 untreated participants, the ATT was -14.5% (95% CI: -18.4, -10.6) after optimal matching (202 matched pairs; 15/22 covariates balanced), -14.9% (-18.9, -11.0) after nearest neighbor matching (202 matched pairs; 17/22 covariates balanced), and -12.0% (-16.5, -7.5) after nearest neighbor caliper matching (153 matched pairs; 21/22 covariates balanced). After double propensity score adjustment, the ATT was -13.0% (-16.0, -10.1).

conclusionsIn PSM analyses, double propensity score adjustment is a readily accessible alternative approach for estimating ATTs when sufficient covariate balance between treatment groups cannot be achieved without excluding treated participants.

Indexed as

Anticholesteremic AgentsCholesterolDistrict of ColumbiaFemaleHIV InfectionsHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMalePropensity ScoreAnticholesteremic AgentsCholesterolHydroxymethylglutaryl-CoA Reductase InhibitorsCausalityCholesterolConfounding factors (epidemiology)HIVHydroxymethylglutaryl-CoA reductase inhibitorsMatched-pair analysisObservational studyPropensity scoreResearch design

Identifiers

PMID32204991
PMCPMC7190432
OpenAlexW3009520687

What Socratic 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 Socratic graph.