ArticleInternational journal of epidemiology2021
G-computation for policy-relevant effects of interventions on time-to-event outcomes.
Article in International journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Pooled Multinomial Logistic Regression for Parametric G-computation in the Presence of Competing Events.Epidemiology (Cambridge, Mass.) · 2026Article
- Impact of interventions to prevent asbestos-related respiratory disease in an exposed worker registry using a simplified G-computation.American journal of epidemiology · 2026Article
- Responding to the increase in substance use, HIV, HCV, and overdose in New England (RISE-NE): Protocol for a prospective cohort study.PloS one · 2026Article
- A hypothetical intervention analysis for the effects of healthy dietary patterns on reducing major chronic diseases and mortality associated with air pollutant mixtures.BMC medicine · 2025Article
- Enhancing confidence in complex health technology assessments by using real-world evidence: highlighting existing strategies for effective drug evaluation.BMC medical research methodology · 2025Review
- Residential Segregation and Lung Cancer Risk in African American Adults.JAMA network open · 2025Article
- Study assessing the effectiveness of overdose prevention centers through research (SAFER): an overview of the study protocol.Harm reduction journal · 2025Article
- Hypothetical Behavioral Interventions for Mitigating the Cardiovascular Effects of Long-Term Fine Particulate Matter Exposure: Analyses From 2 Prospective Cohorts.Journal of the American Heart Association · 2025Article
- Effects of an Intervention on Black Family Incomes on Self-Rated Health and Obesity in Black and White Adolescents and Young Adults.American journal of epidemiology · 2024Article
- Simulating the impact of greenspace exposure on metabolic biomarkers in a diverse population living in San Diego, California: A g-computation application.Environmental epidemiology (Philadelphia, Pa.) · 2024Article
- Semiparametric g-computation for survival outcomes with time-fixed exposures: An illustration.Annals of epidemiology · 2024Article
- Bias due to coarsening of time intervals in the inference for the effectiveness of colorectal cancer screening.International journal of epidemiology · 2024Article
- The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach.BMC medical research methodology · 2024Article
- Immortal Time Bias With Time-Varying Exposures in Environmental Epidemiology: A Case Study in Lung Cancer Survival.American journal of epidemiology · 2023Article
- Long-term causal effects of far-right terrorism in New Zealand.PNAS nexus · 2023Article
- Article
- Potential benefits of joint hypothetical interventions on diet, lead, and cadmium on mortality in US adults.Environmental health : a global access science source · 2022Article
- Population intervention effects in observational studies to emulate target trial results: reconciling the effects of improved sanitation on child growth.International journal of epidemiology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
Abstract
backgroundParametric 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.
methodsWe 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.
resultsWe 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.
conclusionsAs 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.
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Registered trials
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