Evidence map›Paper›PMID 26720412›Full record

ArticlePloS one2015

A Scoring Tool to Identify East African HIV-1 Serodiscordant Partnerships with a High Likelihood of Pregnancy.

Renee Heffron, Craig R Cohen, Kenneth Ngure, Elizabeth Bukusi, Edwin Were, James Kiarie, Nelly Mugo, Connie Celum, Jared M Baeten, Partners PrEP Study, the Partners in Prevention HSV/HIV Transmission Study, and the Partners Demonstration Project Teams

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. A Risk Assessment Tool for Identifying Pregnant and Postpartum Women Who May Benefit From Preexposure Prophylaxis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2017
    Article
  4. Review
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

10 authors.

Renee HeffronDepartment of Global Health, University of Washington, Seattle, United States of America.
Craig R CohenDepartment of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, United States of America.
Kenneth NgureDepartment of Global Health, University of Washington, Seattle, United States of America.
Elizabeth BukusiDepartment of Global Health, University of Washington, Seattle, United States of America.
Edwin WereDepartment of Reproductive Health, Moi University, Eldoret, Kenya.
James KiarieDepartment of Obstetrics and Gynaecology, University of Nairobi, Nairobi, Kenya.
Nelly MugoDepartment of Global Health, University of Washington, Seattle, United States of America.
Connie CelumDepartment of Global Health, University of Washington, Seattle, United States of America.
Jared M BaetenDepartment of Global Health, University of Washington, Seattle, United States of America.
Partners PrEP Study, the Partners in Prevention HSV/HIV Transmission Study, and the Partners Demonstration Project Teams

Funding

Optimizing Antiretroviral-Based HIV Prevention for HIV Serodiscordant CouplesR01MH095507 · NIMH · UNIVERSITY OF WASHINGTON · PI BAETEN, JARED · 2011 to 2020
$6.1M
Antiretroviral periconception HIV prevention for HIV discordant couplesR00HD076679 · NICHD · UNIVERSITY OF WASHINGTON · PI HEFFRON, RENEE A. · 2015 to 2017
$742k
Antiretroviral periconception HIV prevention for HIV discordant couplesK99HD076679 · NICHD · UNIVERSITY OF WASHINGTON · PI HEFFRON, RENEE A. · 2013 to 2014
$208k
NICHD NIH HHS K99 HD076679NICHD NIH HHS K99HD076679NICHD NIH HHS R00 HD076679NICHD NIH HHS R00HD076679NIMH NIH HHS R01 MH095507NIMH NIH HHS R01MH095507
6 · The paper itself

Abstract

introductionHIV-1 prevention programs targeting HIV-1 serodiscordant couples need to identify couples that are likely to become pregnant to facilitate discussions about methods to minimize HIV-1 risk during pregnancy attempts (i.e. safer conception) or effective contraception when pregnancy is unintended. A clinical prediction tool could be used to identify HIV-1 serodiscordant couples with a high likelihood of pregnancy within one year.

methodsUsing standardized clinical prediction methods, we developed and validated a tool to identify heterosexual East African HIV-1 serodiscordant couples with an increased likelihood of becoming pregnant in the next year. Datasets were from three prospectively followed cohorts, including nearly 7,000 couples from Kenya and Uganda participating in HIV-1 prevention trials and delivery projects.

resultsThe final score encompassed the age of the woman, woman's number of children living, partnership duration, having had condomless sex in the past month, and non-use of an effective contraceptive. The area under the curve (AUC) for the probability of the score to correctly predict pregnancy was 0.74 (95% CI 0.72-0.76). Scores ≥ 7 predicted a pregnancy incidence of >17% per year and captured 78% of the pregnancies. Internal and external validation confirmed the predictive ability of the score. DISCUSSION: A pregnancy likelihood score encompassing basic demographic, clinical and behavioral factors defined African HIV-1 serodiscordant couples with high one-year pregnancy incidence rates. This tool could be used to engage African HIV-1 serodiscordant couples in counseling discussions about fertility intentions in order to offer services for safer conception or contraception that align with their reproductive goals.

Indexed as

AdultBlack PeopleContraceptionContraceptive AgentsContraceptive DevicesCounselingFamily CharacteristicsFemaleFertilityFertilizationHeterosexualityHIV-1HIV SeronegativityHIV SeropositivityHumansInfectious Disease Transmission, VerticalContraceptive Agents

Identifiers

PMID26720412
PMCPMC4703139

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Registered trials

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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.