Evidence map›Paper›PMID 32740471›Full record

ArticleEpidemiology (Cambridge, Mass.)2020

Defining and Identifying Per-protocol Effects in Randomized Trials.

Jacqueline E Rudolph, Ashley I Naimi, Daniel J Westreich, Edward H Kennedy, Enrique F Schisterman

Open access · greenAbstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Review
  5. 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 at 4 institutions in 1 country.

Jacqueline E RudolphFrom the Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA.
Ashley I NaimiFrom the Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA.
Daniel J WestreichDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Edward H KennedyDepartment of Statistics, Carnegie Mellon University, Pittsburgh, PA.
Enrique F SchistermanEpidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland.
University of Pittsburgh · USCarnegie Mellon University · USEunice Kennedy Shriver National Institute of Child Health and Human Development · USUniversity of North Carolina at Chapel Hill · US

Funding

Informing national guidelines on diet patterns that promote healthy pregnancy outcomesR01HD102313 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BODNAR, LISA M, NAIMI, ASHLEY ISAAC · 2020 to 2024
$3.0M
Estimating the Effect of Low-Dose Aspirin on Fetal Loss in a Trial with Non-ComplianceR01HD093602 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI NAIMI, ASHLEY ISAAC · 2018 to 2021
$1.2M
NICHD NIH HHS R01 HD093602NICHD NIH HHS R01 HD102313
6 · The paper itself

Abstract

In trials with noncompliance to assigned treatment, researchers might be interested in estimating a per-protocol effect-a comparison of two counterfactual outcomes defined by treatment assignment and (often time-varying) compliance with a well-defined treatment protocol. Here, we provide a general counterfactual definition of a per-protocol effect and discuss examples of per-protocol effects that are of either substantive or methodologic interest. In doing so, we seek to make more concrete what per-protocol effects are and highlight that one can estimate per-protocol effects that are more than just a comparison of always taking treatment in two distinct treatment arms. We then discuss one set of identifiability conditions that allow for identification of a causal per-protocol effect, highlighting some potential violations of those conditions that might arise when estimating per-protocol effects.

Indexed as

Clinical ProtocolsRandomized Controlled Trials as TopicCausalityHumansPatient ComplianceTreatment Outcome

Identifiers

PMID32740471
PMCPMC7400733
OpenAlexW3046119562

What OpenQuestion 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 OpenQuestion graph.