Evidence map›Paper›PMID 27766318›Full record

ArticleContemporary clinical trials communications2016

Intra-Cluster Correlation Estimates for HIV-related Outcomes from Care and Treatment Clinics in Dar es Salaam, Tanzania.

Dale Barnhart, Ellen Hertzmark, Enju Liu, Ester Mungure, Aisa N Muya, David Sando, Guerino Chalamilla, Nzovu Ulenga, Till Bärnighausen, Wafaie Fawzi and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in Contemporary clinical trials communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03688217 (The Philani Mobile Video Intervention for Exclusive Breastfeeding), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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.

NCT03688217 nacompletednot on this mapstarted 2018, after this paper: background citation

The Philani Mobile Video Intervention for Exclusive Breastfeeding (MOVIE) Study: a Cluster-randomized Controlled Trial of a Mobile Video Entertainment-education Intervention to Promote Exclusive Breastfeeding in South Africa

TypeinterventionalSponsorCharles G. ProberRan2018 to 2020Enrolled1,504ConditionsExclusive Breastfeeding, Infant Feeding PracticesArmsPhilani Intervention Model+MOVIE (PIM+M), Philani Intervention Model (PIM)
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

11 authors.

Dale BarnhartDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA.
Ellen HertzmarkDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA.
Enju LiuDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA.
Ester MungureDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA.
Aisa N MuyaManagement and Development of Health, Mwai Kibaki Road, Dar es Salaam, Tanzania.
David SandoDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA; Management and Development of Health, Mwai Kibaki Road, Dar es Salaam, Tanzania.
Guerino ChalamillaManagement and Development of Health, Mwai Kibaki Road, Dar es Salaam, Tanzania.
Nzovu UlengaDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA; Management and Development of Health, Mwai Kibaki Road, Dar es Salaam, Tanzania.
Till BärnighausenDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA; Wellcome Trust Africa Centre for Population Health, A2074 Road, Mtubatuba, KwaZulu-Natal 3935, South Africa.
Wafaie FawziDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA.
Donna SpiegelmanDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, Massachusetts 02115, USA.

Funding

IMPLEMENTATION OF PROGRAMS FOR THE PREVENTION, CARE AND TREATMENT OF HIV/AIDS IN U2GPS001966 · PS · HARVARD SCHOOL OF PUBLIC HEALTH · PI FAWZI, WAFAIE W · 2010 to 2015
$13.0M
Comprehensive Translational Science Analytics Tools for the Global Health AgendaDP1ES025459 · NIEHS · YALE UNIVERSITY · PI SPIEGELMAN, DONNA L · 2014 to 2018
$4.1M
New Methods for the design and evaluation of large HIV prevention interventionsR01AI112339 · NIAID · YALE UNIVERSITY · PI SPIEGELMAN, DONNA L · 2014 to 2017
$2.7M
NCHHSTP CDC HHS U2G PS001966NIAID NIH HHS R01 AI112339NIEHS NIH HHS DP1 ES025459
6 · The paper itself

Abstract

introductionResearchers planning cluster-randomized controlled trials (cRCTs) require estimates of the intra-cluster correlation coefficient (ICC) from previous studies for sample size calculations. This paper fills a persistent gap in the literature by providing estimates of ICCs for many key HIV-related clinical outcomes.

methodsData from HIV-positive patients from 47 HIV care and treatment clinics in Dar es Salaam, Tanzania were used to calculate ICCs by site of enrollment or site of ART initiation for various clinical outcomes using cross-sectional and longitudinal data. ICCs were estimated using linear mixed models where either clinic of enrollment or clinic of ART initiation served as the random effect.

resultsICCs ranged from 0 to 0.0706 (95% CI: 0.0447, 0.1098). For most outcomes, the ICCs were large enough to meaningfully affect sample size calculations. For binary outcomes, the ICCs for event prevalence at baseline tended to be larger than the ICCs for later cumulative incidences. For continuous outcomes, the ICCs for baseline values tended to be larger than the ICCs for the change in values from baseline.

conclusionThe ICCs for HIV-related outcomes cannot be ignored when calculating sample sizes for future cluster-randomized trials. The differences between ICCs calculated from baseline data alone and ICCs calculated using longitudinal data demonstrate the importance of selecting an ICC that reflects a study's intended design and duration for sample size calculations. While not generalizable to all contexts, these estimates provide guidance for future researchers seeking to design adequately powered cRCTs in Sub-Saharan African HIV treatment and care clinics.

Indexed as

Cluster Randomized ControlledHIV InfectionsIntra-cluster Correlation CoefficientMulticenter StudiesSample Size

Identifiers

PMID27766318
PMCPMC5066589

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.