Evidence map›Paper›PMID 33276738›Full record

Trial reportBMC infectious diseases2020

Factors and HCV treatment outcomes associated with smoking among people who inject drugs on opioid agonist treatment: secondary analysis of the PREVAIL randomized clinical trial.

Irene Pericot-Valverde, Moonseong Heo, Matthew J Akiyama, Brianna L Norton, Linda Agyemang, Jiajing Niu, Alain H Litwin

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01857245 (Intensive Models of HCV Care for Injection Drug Users), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

NCT01857245 nacompletednot on this map

Intensive Models of HCV Care for Injection Drug Users

TypeinterventionalSponsorPrisma Health-UpstateRan2013 to 2017Enrolled150ConditionsHepatitis C, Medication AdherenceArmsIntensive Models (mDOT and CGT) of HCV Care
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

7 authors.

Irene Pericot-ValverdeSchool of Health Research, Clemson University, Clemson, SC, USA.
Moonseong HeoDepartment of Public Health Sciences, College of Behavioral, Social, and Health Sciences, Clemson University, Clemson, SC, USA.
Matthew J AkiyamaAlbert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY, USA.
Brianna L NortonAlbert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY, USA.
Linda AgyemangAlbert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY, USA.
Jiajing NiuSchool of Mathematical and Statistical Sciences, College of Science, Clemson University, Clemson, SC, USA.
Alain H LitwinSchool of Health Research, Clemson University, Clemson, SC, USA. alain.litwin@prismahealth.org.

Funding

Intensive Models of HCV Care for Injection Drug UsersR01DA034086 · NIDA · CLEMSON UNIVERSITY · PI LITWIN, ALAIN HARRIS · 2012 to 2016
$3.7M
Advance Care Coordination and Enhanced Linkage and Retention Among Transitional Re-Entrants LivingR00DA043011 · NIDA · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI AKIYAMA, MATTHEW · 2020 to 2022
$747k
NIDA NIH HHS R00 DA043011NIDA NIH HHS R01 DA034086NIDA NIH HHS R01DA034086
6 · The paper itself

Abstract

backgroundCigarette smoking has emerged as a leading cause of mortality among people with hepatitis C virus (HCV). People who inject drugs (PWID) represent the largest group of adults infected with HCV in the US. However, cigarette smoking remains virtually unexplored among this population. This study aimed at (1) determining prevalence and correlates of cigarette smoking among HCV-infected PWID enrolled in opiate agonist treatment programs; (2) exploring the association of smoking with HCV treatment outcomes including adherence, treatment completion and sustained virologic response (SVR); and 3) exploring whether cigarette smoking decreased after HCV treatment.

methodsParticipants were 150 HCV-infected PWID enrolled in a randomized clinical trial primarily designed to test three intensive models of HCV care. Assessments included sociodemographics, presence of chronic health and psychiatric comorbidities, prior and current drug use, quality of life, and HCV treatment outcomes.

resultsThe majority of the patients (84%) were current cigarette smokers at baseline. There was a high prevalence of psychiatric and medical comorbidities in the overall sample of PWID. Alcohol and cocaine use were identified as correlates of cigarette smoking. Smoking status did not influence HCV treatment outcomes including adherence, treatment completion and SVR. HCV treatment was not associated with decreased cigarette smoking.

conclusionsThe present study showed high prevalence of cigarette smoking among this population as well as identified correlates of smoking, namely alcohol and cocaine use. Cigarette smoking was not associated with HCV treatment outcomes. Given the detrimental effects that cigarette smoking and other co-occurring, substance use behaviors have on HCV-infected individuals' health, it is imperative that clinicians treating HCV also target smoking, especially among PWID. The high prevalence of cigarette smoking among PWID will contribute to growing morbidity and mortality among this population even if cured of HCV. Tailored smoking cessation interventions for PWID along with HCV treatment may need to be put into clinical practice.

trial registrationNCT01857245 . Registered May 20, 2013.

Indexed as

AdultAgedAnalgesics, OpioidAntiviral AgentsCigarette SmokingFemaleFollow-Up StudiesHepacivirusHepatitis CHumansLongitudinal StudiesMaleMiddle AgedPrevalenceQuality of LifeRisk FactorsAnalgesics, OpioidAntiviral AgentsRNA, ViralDAAHCVPWIDSmokingSVR

Identifiers

PMID33276738
PMCPMC7718688

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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.