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.
cervical cancer precursors hormonal contraceptives, HIV-positive women cervical intraepithelial neoplasia, causal inference contraceptive cervical cancer, semi-parametric estimation epidemiology, DMPA cervical dysplasia risk, hormonal contraception cervical cancer HIV, causal modeling obstetrics gynecology, injectable contraceptive cervical neoplasia, HIV contraception cancer interaction
PMID 24979709 24979709 DOI 10.1371/journal.pone.0101090 10.1371/journal.pone.0101090
Cite this article
Leslie, H. H., Karasek, D. A., Harris, L. F., Chang, E., Abdulrahim, N., Maloba, M., & Huchko, M. 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), e101090. https://doi.org/10.1371/journal.pone.0101090
Leslie HH, Karasek DA, Harris LF, Chang E, Abdulrahim N, Maloba M, et al. Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods. PLoS One. 2014;9(6):e101090. doi:10.1371/journal.pone.0101090
Leslie, Hannah H., et al. "Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods." PloS one, vol. 9, no. 6, 2014, pp. e101090.
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