ArticleBiometrics2014
Modeling the impact of hepatitis C viral clearance on end-stage liver disease in an HIV co-infected cohort with targeted maximum likelihood estimation.
Article in Biometrics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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.
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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
16 citing papers in PubMed, 25 citations in OpenAlex.
- Guidelines and Best Practices for the Use of Targeted Maximum Likelihood and Machine Learning When Estimating Causal Effects of Exposures on Time-To-Event Outcomes.Statistics in medicine · 2025Article
- A Bayesian latent class approach to causal inference with longitudinal data.Statistical methods in medical research · 2025Article
- Longitudinal plasmode algorithms to evaluate statistical methods in realistic scenarios: an illustration applied to occupational epidemiology.BMC medical research methodology · 2023Article
- Considering Questions Before Methods in Dementia Research With Competing Events and Causal Goals.American journal of epidemiology · 2023Article
- Estimation of the Average Causal Effect in Longitudinal Data With Time-Varying Exposures: The Challenge of Nonpositivity and the Impact of Model Flexibility.American journal of epidemiology · 2022Article
- MULTIPLY ROBUST ESTIMATORS OF CAUSAL EFFECTS FOR SURVIVAL OUTCOMES.Scandinavian journal of statistics, theory and applications · 2022Article
- Parametric g-formula implementations for causal survival analyses.Biometrics · 2021Article
- A causal framework for classical statistical estimands in failure-time settings with competing events.Statistics in medicine · 2020Article
- Using longitudinal targeted maximum likelihood estimation in complex settings with dynamic interventions.Statistics in medicine · 2019Article
- Double Robust Efficient Estimators of Longitudinal Treatment Effects: Comparative Performance in Simulations and a Case Study.The international journal of biostatistics · 2019Article
- Inverse probability weighted estimation of risk under representative interventions in observational studies.Journal of the American Statistical Association · 2019Article
- Methods for time-varying exposure related problems in pharmacoepidemiology: An overview.Pharmacoepidemiology and drug safety · 2018Review
- Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?International journal of epidemiology · 2016Article
- Evaluating the Impact of a HIV Low-Risk Express Care Task-Shifting Program: A Case Study of the Targeted Learning Roadmap.Epidemiologic methods · 2016Article
- Doubly Robust and Efficient Estimation of Marginal Structural Models for the Hazard Function.The international journal of biostatistics · 2016Article
- Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models.Journal of causal inference · 2014Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
Despite modern effective HIV treatment, hepatitis C virus (HCV) co-infection is associated with a high risk of progression to end-stage liver disease (ESLD) which has emerged as the primary cause of death in this population. Clinical interest lies in determining the impact of clearance of HCV on risk for ESLD. In this case study, we examine whether HCV clearance affects risk of ESLD using data from the multicenter Canadian Co-infection Cohort Study. Complications in this survival analysis arise from the time-dependent nature of the data, the presence of baseline confounders, loss to follow-up, and confounders that change over time, all of which can obscure the causal effect of interest. Additional challenges included non-censoring variable missingness and event sparsity. In order to efficiently estimate the ESLD-free survival probabilities under a specific history of HCV clearance, we demonstrate the double-robust and semiparametric efficient method of Targeted Maximum Likelihood Estimation (TMLE). Marginal structural models (MSM) can be used to model the effect of viral clearance (expressed as a hazard ratio) on ESLD-free survival and we demonstrate a way to estimate the parameters of a logistic model for the hazard function with TMLE. We show the theoretical derivation of the efficient influence curves for the parameters of two different MSMs and how they can be used to produce variance approximations for parameter estimates. Finally, the data analysis evaluating the impact of HCV on ESLD was undertaken using multiple imputations to account for the non-monotone missing data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.