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Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.

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Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.pdf
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Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.pdf
1.0 Mb
Date
2014
Authors
Leslie, Hannah H
Karasek, Deborah A
Harris, Laura F
Chang, Emily
Abdulrahim, Naila
Maloba, May
Huchko, Megan J
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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 article
Subject
Contraceptives, Oral, Hormonal
Female
HIV Seropositivity
Humans
Incidence
Kenya
Models, Statistical
Uterine Cervical Neoplasms
Permalink
https://hdl.handle.net/10161/12717
Published Version (Please cite this version)
10.1371/journal.pone.0101090
Publication 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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Scholars@Duke

Huchko

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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