Introduction
HIV-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.
Methods
Using
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.
Results
The
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.
Below: Pregnancy incidence rates by score among women in the A)
Partners PrEP Study B) Partners in Prevention HSV/HIV Transmission Study at
Kenyan and Ugandan sites and C) Partners Demonstration Project.
Full article at: http://goo.gl/uBRQFe
By:
Renee Heffron, Kenneth Ngure, Elizabeth Bukusi, Nelly Mugo,
Connie Celum, Jared M. Baeten
Department of Global Health,
University of Washington, Seattle, United States of America
Renee Heffron, Connie Celum, Jared M. Baeten
Department of Epidemiology,
University of Washington, Seattle, United States of America
Connie Celum, Jared M. Baeten
Department of Medicine,
University of Washington, Seattle, United States of America
Craig R. Cohen
Department of Obstetrics,
Gynecology & Reproductive Sciences, University of California San Francisco,
San Francisco, United States of America
Kenneth Ngure
Jomo Kenyatta University of
Agriculture and Technology, Nairobi, Kenya
Elizabeth Bukusi
Microbiology Research, Kenya
Medical Research Institute, Nairobi, Kenya
Nelly Mugo
Center for Clinical Research,
Kenya Medical Research Institute, Nairobi, Kenya
Nelly Mugo
Department of Obstetrics &
Gynecology, Kenya Medical Research Institute, Nairobi, Kenya
Edwin Were
Department of Reproductive
Health, Moi University, Eldoret, Kenya
James Kiarie
Department of Obstetrics and
Gynaecology, University of Nairobi, Nairobi, Kenya
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