Evidence map›Paper›PMID 32042214›Full record

ArticleJournal of the American Statistical Association2017

Quantifying an Adherence Path-Specific Effect of Antiretroviral Therapy in the Nigeria PEPFAR Program.

Caleb H Miles, Ilya Shpitser, Phyllis Kanki, Seema Meloni, Eric J Tchetgen Tchetgen

Abstract read
In one paragraph

Article in Journal of the American Statistical Association, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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.

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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Identification in Causal Models With Hidden Variables.Journal de la Societe francaise de statistique (2009) · 2020
    Article
  8. Article
  9. Article
  10. Identification of Personalized Effects Associated With Causal Pathways.Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence · 2018
    Article
  11. Estimation of Personalized Effects Associated With Causal Pathways.Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence · 2018
    Article
  12. Fair Inference on Outcomes.Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence · 2018
    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

5 authors.

Caleb H MilesPostdoctoral Fellow, Division of Biostatistics, University of California, Berkeley, Berkeley, CA 94720-7358.
Ilya ShpitserAssistant Professor, Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218-2608.
Phyllis KankiResearch Associate, Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115.
Seema MeloniResearch Associate, Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115.
Eric J Tchetgen TchetgenProfessor, Departments of Biostatistics and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115.

Funding

Identification and Inference for Longitudinal Causal Mediation Analysis in HIVR01AI104459 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI SHPITSER, ILYA, VANDERWEELE, TYLER · 2013 to 2017
$2.0M
NIAID NIH HHS R01 AI104459
6 · The paper itself

Abstract

Since the early 2000s, evidence has accumulated for a significant differential effect of first-line antiretroviral therapy (ART) regimens on human immunodeficiency virus (HIV) viral load suppression. This finding was replicated in our data from the Harvard President's Emergency Plan for AIDS Relief (PEPFAR) program in Nigeria. Investigators were interested in finding the source of these differences, i.e., understanding the mechanisms through which one regimen outperforms another, particularly via adherence. This question can be naturally formulated via mediation analysis with adherence playing the role of a mediator. Existing mediation analysis results, however, have relied on an assumption of no exposure-induced confounding of the intermediate variable, and generally require an assumption of no unmeasured confounding for nonparametric identification. Both assumptions are violated by the presence of drug toxicity. In this paper, we relax these assumptions and show that certain path-specific effects remain identified under weaker conditions. We focus on the path-specific effect solely mediated by adherence and not by toxicity and propose an estimator for this effect. We illustrate with simulations and present results from a study applying the methodology to the Harvard PEPFAR data. Supplementary materials are available online.

Indexed as

Human immunodeficiency virusMediationNonparametric identificationUnobserved confounding

Identifiers

PMID32042214
PMCPMC7009790

What OpenQuestion holds

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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.