Evidence map›Paper›PMID 32501812›Full record

Trial reportEpidemiology (Cambridge, Mass.)2020

The Effect of Prenatal Treatments on Offspring Events in the Presence of Competing Events: An Application to a Randomized Trial of Fertility Therapies.

Yu-Han Chiu, Mats J Stensrud, Issa J Dahabreh, Paolo Rinaudo, Michael P Diamond, John Hsu, Sonia Hernández-Díaz, Miguel A Hernán

Open access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report 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 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 41 citations in OpenAlex.

  1. Trial
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  7. Causal Approaches to Disease Progression Analyses.Epidemiology (Cambridge, Mass.) · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Yu-Han ChiuFrom the Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Mats J StensrudFrom the Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Issa J DahabrehFrom the Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Paolo RinaudoCenter for Reproductive Health, University of California, San Francisco, CA.
Michael P DiamondDepartment of Obstetrics & Gynecology, Medical College of Georgia, Augusta University, Augusta, GA.
John HsuMongan Institute, Massachusetts General Hospital, Boston, MA.
Sonia Hernández-DíazFrom the Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Miguel A HernánFrom the Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Harvard University · USAugusta University · USBrown University · USInstitute for Reproductive Health · US

Funding

Long-term Impact of Fertility Treatment StudyR01HD088393 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI HERNAN, MIGUEL, HERNANDEZ-DIAZ, SONIA · 2017 to 2022
$2.9M
The Training Program in Reproductive, Perinatal, and Pediatric Life Course EpidemiologyT32HD104612 · NICHD · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Sonia Hernandez-Diaz, Henning Tiemeier · 2021 to 2026
$2.2M
NICHD NIH HHS R01 HD088393NICHD NIH HHS T32 HD104612
6 · The paper itself

Abstract

When studying the effect of a prenatal treatment on events in the offspring, failure to produce a live birth is a competing event for events in the offspring. A common approach to handle this competing event is reporting both the treatment-specific probabilities of live births and of the event of interest among live births. However, when the treatment affects the competing event, the latter probability cannot be interpreted as the causal effect among live births. Here we provide guidance for researchers interested in the effects of prenatal treatments on events in the offspring in the presence of the competing event "no live birth." We review the total effect of treatment on a composite event and the total effect of treatment on the event of interest. These causal effects are helpful for decision making but are agnostic about the pathways through which treatment affects the event of interest. Therefore, based on recent work, we also review three causal effects that explicitly consider the pathways through which treatment may affect the event of interest in the presence of competing events: the direct effect of treatment on the event of interest under an intervention to eliminate the competing event, the separable direct and indirect effects of treatment on the event of interest, and the effect of treatment in the principal stratum of those who would have had a live birth irrespective of treatment choice. As an illustrative example, we use a randomized trial of fertility treatments and risk of neonatal complications.

Indexed as

FertilityLive BirthPrenatal CareFemaleHumansInfant, NewbornPregnancyTreatment Outcome

Identifiers

PMID32501812
PMCPMC7755108
OpenAlexW3033081440

What OpenQuestion holds

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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.