Evidence map›Paper›PMID 27578113›Full record

ArticleJournal of clinical lipidology

Patterns and predictors of medication adherence to lipid-lowering therapy in children aged 8 to 20 years.

Nina R Joyce, Gregory A Wellenius, Charles B Eaton, Amal N Trivedi, Justin P Zachariah

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Journal of clinical lipidology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04458766 (The Use of Mobile Health Technology and Behavioral Economics to Encourage Adherence to Statins in Adolescents With Familial Hypercholesterolemia), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 18% 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.

NCT04458766 nacompletednot on this map

The Use of Mobile Health Technology and Behavioral Economics to Encourage Adherence to Statins in Adolescents With Familial Hypercholesterolemia

TypeinterventionalSponsorBoston Children's HospitalRan2021 to 2024Enrolled11ConditionsFamilial Hypercholesterolemia, Adherence, MedicationArmsMonetary incentives
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 17 citations in OpenAlex.

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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 2 institutions in 1 country.

Nina R JoyceDepartment of Epidemiology, Brown University School of Public Health, Providence, RI, USA; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA. Electronic address: Joyce@hcp.harvard.med.edu.
Gregory A WelleniusDepartment of Epidemiology, Brown University School of Public Health, Providence, RI, USA.
Charles B EatonDepartment of Epidemiology, Brown University School of Public Health, Providence, RI, USA.
Amal N TrivediDepartment of Health Services, Policy and Practice, Brown University, Providence, RI, USA.
Justin P ZachariahDepartment of Cardiology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Lillie Frank Abercrombie Section of Pediatric Cardiology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
Brown University · USHarvard University · US

Funding

Health Policy Training Program: Promoting Outcomes, Quality, Equity and Diffusion of AdvancesT32MH019733 · NIMH · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Benjamin Le Cook, Haiden A Huskamp · 1993 to 2026
$7.0M
Develop Patient Centered Outcomes Scholars for Comparative Effectiveness ResearchK12HS022998 · AHRQ · BROWN UNIVERSITY · PI TRIKALINOS, THOMAS · 2014 to 2018
$3.4M
Vascular Remodeling in Overweight and Obese AdolescentsK23HL111335 · NHLBI · BOSTON CHILDREN'S HOSPITAL · PI ZACHARIAH, JUSTIN P.V. · 2012 to 2017
$708k
AHRQ HHS K12 HS022998NHLBI NIH HHS K23 HL111335NIMH NIH HHS T32 MH019733
6 · The paper itself

Abstract

backgroundThe American Academy of Pediatrics recommends lipid-lowering therapy (LLT) for children at high risk of cardiovascular disease. However, the use of LLT in children is rare, and rates of nonadherence are unknown.

objectiveTo identify patterns of use and predictors of nonadherence to LLT in children aged 8 to 20 years and the subgroup with dyslipidemia.

methodsCommercially insured patients with a new dispensing for an LLT were included. Nonadherence was defined as a gap of >90 days between the last dispensing plus the medication days supply and the next dispensing or censoring. Descriptive statistics characterize the patterns of LLT adherence and class-specific drug switching. Kaplan-Meier curves and multivariable Cox proportional hazard models identified time to, and predictors of, nonadherence for the cohort and the dyslipidemia subgroup.

resultsOf the 8710 patients meeting inclusion criteria, 87% were nonadherent. Statins were the most common index prescription, and patients with an index statin dispensing were more likely to have multiple comorbidities and other prescription drug use. In multivariable analyses, nonadherence was inversely associated with dyslipidemia (hazard ratio [HR] = 0.61, 95% confidence interval [CI] = 0.57-0.65), chronic kidney disease (HR = 0.69, 95% CI = 0.54-0.88), higher outpatient (HR = 0.87, 95% CI = 0.77-0.98), and inpatient (HR = 0.83, 95% CI = 0.70-0.97) use. When limited to patients with dyslipidemia, nonadherence was related to age (HR = 1.21, 95% CI = 1.07-1.38) and obesity (HR = 1.23, 95% CI = 1.02-1.49).

conclusionsDespite recommendations to begin continuous treatment early for high-risk children, nonadherence to LLT is frequent in this population, with modestly higher adherence in children with dyslipidemia.

Indexed as

Drug MonitoringAdolescentChildDatabases, FactualDyslipidemiasFemaleHumansHypolipidemic AgentsInsurance, HealthMaleYoung AdultHypolipidemic AgentsDyslipidemiaMedication adherencePediatricsPharmacoepidemiology

Identifiers

PMID27578113
PMCPMC5226262
OpenAlexW2293944828

What OpenQuestion holds

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Registered trials

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.