Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.
Abstract
OBJECTIVE: To demonstrate the application of causal inference methods to observational
data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric
estimation. BACKGROUND: Human immunodeficiency virus (HIV)-positive women are at increased
risk for cervical cancer and its treatable precursors. Determining whether potential
risk factors such as hormonal contraception are true causes is critical for informing
public health strategies as longevity increases among HIV-positive women in developing
countries. METHODS: We developed a causal model of the factors related to combined
oral contraceptive (COC) use and cervical intraepithelial neoplasia 2 or greater (CIN2+)
and modified the model to fit the observed data, drawn from women in a cervical cancer
screening program at HIV clinics in Kenya. Assumptions required for substantiation
of a causal relationship were assessed. We estimated the population-level association
using semi-parametric methods: g-computation, inverse probability of treatment weighting,
and targeted maximum likelihood estimation. RESULTS: We identified 2 plausible causal
paths from COC use to CIN2+: via HPV infection and via increased disease progression.
Study data enabled estimation of the latter only with strong assumptions of no unmeasured
confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7%) were diagnosed
with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9%)
increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance
of this association was sensitive to method of estimation and exposure misclassification.
CONCLUSION: Use of causal modeling enabled clear representation of the causal relationship
of interest and the assumptions required to estimate that relationship from the observed
data. Semi-parametric estimation methods provided flexibility and reduced reliance
on correct model form. Although selected results suggest an increased prevalence of
CIN2+ associated with COC, evidence is insufficient to conclude causality. Priority
areas for future studies to better satisfy causal criteria are identified.
Type
Journal articleSubject
Contraceptives, Oral, HormonalFemale
HIV Seropositivity
Humans
Incidence
Kenya
Models, Statistical
Uterine Cervical Neoplasms
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https://hdl.handle.net/10161/12717Published Version (Please cite this version)
10.1371/journal.pone.0101090Publication Info
Leslie, Hannah H; Karasek, Deborah A; Harris, Laura F; Chang, Emily; Abdulrahim, Naila;
Maloba, May; & Huchko, Megan J (2014). Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application
of a causal model and semi-parametric estimation methods. PLoS One, 9(6). pp. e101090. 10.1371/journal.pone.0101090. Retrieved from https://hdl.handle.net/10161/12717.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Megan Justine Huchko
Associate Professor of Obstetrics and Gynecology
Megan Huchko, MD, MPH, holds a dual appointment as an Associate Professor in the Department
of Obstetrics & Gynecology and the Duke Global Health Institute. Dr. Huchko was an
undergraduate at Duke before moving to New York City to complete medical school at
the Albert Einstein College of Medicine, and residency training at Columbia Presbyterian
Medical Center. She completed her fellowship in Repr

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