Year: 2020
Type: article
Abstract: BACKGROUND: Parametric g-computation is an analytic technique that can be used to estimate the effects of exposures, treatments and interventions; it relies on a different set of assumptions than more commonly used inverse probability weighted estimators. Whereas prior work has demonstrated implementations for binary exposures and continuous outcomes, use of parametric g-computation has been limited due to difficulty in implementation in more typical complex scenarios. METHODS: We provide an easy-to-implement algorithm for parametric g-computation in the setting of a dynamic baseline intervention of a baseline exposure and a time-to-event outcome. To demonstrate the use of our algorithm, we apply it to estimate the effects of interventions to reduce area deprivation on the cumulative incidence of sexually transmitted infections (STIs: gonorrhea, chlamydia or trichomoniasis) among women living with HIV in the Women's Interagency HIV Study. RESULTS: We found that reducing area deprivation by a maximum of 1 tertile for all women would lead to a 2.7% [95% confidence interval (CI): 0.1%, 4.3%] reduction in 4-year STI incidence, and reducing deprivation by a maximum of 2 tertiles would lead to a 4.3% (95% CI: 1.9%, 6.4%) reduction. CONCLUSIONS: As analytic methods such as parametric g-computation become more accessible, epidemiologists will be able to estimate policy-relevant effects of interventions to better inform clinical and public health practice and policy.
DOI: 10.1093/ije/dyaa156
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
Funders: Northwestern University, Georgia Clinical and Translational Science Alliance, National Institutes of Health, University of California, San Francisco, Center for AIDS Research, University of Alabama at Birmingham, National Institute on Alcohol Abuse and Alcoholism, National Institute on Aging, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Institute on Drug Abuse, National Human Genome Research Institute, National Cancer Institute, National Institute on Deafness and Other Communication Disorders, National Institute of Nursing Research, National Institute of Allergy and Infectious Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, National Institute of Dental and Craniofacial Research, National Center for Advancing Translational Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Center for AIDS Research, University of North Carolina at Chapel Hill
Awards: G1130671811, G12089860, G1329112180, G1400602301, G1655989834, G1830603148, G183157880, G1913134163, G192128497, G2127051194, G234276190, From patients to policy: innovative epidemiology for implementation science, G248584506, G2688758764, G2755707676, G2759654445, G2782268947, G2837030827, G311558797, G319781266, G3242306066, G3630727822, G3648831043, G3671922257, G3869857964, G418714284, G43444534, G4391827178, G4535678174, G483408255, G4942913453, G5078796989, G5147848267, G521591464, G5660189159, G5721902458, G5747858550, G5863844756, G5900455136, G6396423216, G693265041, G6990385686, G7096550276, G7152846654, G775892330, G7807729167, G7824296413, G8148537207, G8653535977, G9000003786, G9000010044, G9000025681, G9000030772, G9000037749, G9000039899, G9000050451, G9000066220, G9000080293, G9000088144, G9000093720, G9000102070, G9000132212, UNC MACS/WIHS Combined Cohort Study Clinical Research Site, Surviving the HIV Epidemic (S/HE) in metropolitan Washington DC - Advancing knowledge through cohort studies, Clinical Research Sites for the MACS/WIHS Combined Cohort Study (MACS/WIHS-CCS) - Baltimore/Wash DC Center, Clinical Research Sites for the MACS/WIHS Combined Cohort Study (MACS/WIHS-CCS), UAB Center for AIDS Research (CFAR)
OpenAlex ID: W3096496153