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

To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precurso...

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Veröffentlicht in:PloS one 2014-06, Vol.9 (6), p.e101090
Hauptverfasser: Leslie, Hannah H, Karasek, Deborah A, Harris, Laura F, Chang, Emily, Abdulrahim, Naila, Maloba, May, Huchko, Megan J
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container_title PloS one
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creator Leslie, Hannah H
Karasek, Deborah A
Harris, Laura F
Chang, Emily
Abdulrahim, Naila
Maloba, May
Huchko, Megan J
description To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. 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. 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. 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. 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.
doi_str_mv 10.1371/journal.pone.0101090
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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. 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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24979709</pmid><doi>10.1371/journal.pone.0101090</doi><oa>free_for_read</oa></addata></record>
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subjects Acquired immune deficiency syndrome
AIDS
Antiretroviral drugs
Cancer
Cancer screening
Cervical cancer
Cervix
Confidence intervals
Contraception
Contraceptives, Oral, Hormonal - adverse effects
Data processing
Developing countries
Female
Gynecology
Health aspects
Health risk assessment
Health risks
HIV
HIV patients
HIV Seropositivity - complications
Human immunodeficiency virus
Human papillomavirus
Humans
Incidence
Kenya - epidemiology
LDCs
Maximum likelihood estimation
Medicine and health sciences
Methods
Models, Statistical
Obstetrics
Oral contraceptives
Parameter estimation
Physical Sciences
Precursors
Probabilistic methods
Public health
Research and Analysis Methods
Risk analysis
Risk factors
Statistical analysis
Uterine Cervical Neoplasms - epidemiology
Uterine Cervical Neoplasms - etiology
Viruses
Womens health
title 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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