Causal models and their application to estimate the effect of Chronic Hepatitis B treatment

Causal models and their application to estimate the effect of Chronic Hepatitis B treatment

Βουρλή Γεωργία (EL)

born_digital_thesis

Διδακτορική Διατριβή (EL)

Doctoral Dissertation (EN)

2015

Classic statistical analysis methods examine whether observed relationships are due to chance and provide us with inference concerning non-circumstantial associations between variables, that may however be non-causally interpreted. Unfortunately, it has been shown that in the context of a longitudinal observational study, when a covariate affected by past exposure is both a predictor of the future exposure and the outcome, i.e there exists time-dependent confounding, standard analysis approaches for the estimation of the exposure’s effect, may produce biased estimates. The g-methods are a class of methods introduced to estimate causal effects. The most recent of them is the Inverse Probability of Treatment Weighting (IPTW), which is applied to estimate the parameters of the Marginal Structural Models (MSMs). The aim of this thesis was to assess the performance of the MSMs in situations often met in longitudinal observational studies with survival endpoints. Following an exact simulation method, we explored two classes of scenarios: a) missed visits, which resembles clinical cohort studies; b) missing confounder’s values that corresponds to interval cohort studies. In the first class, data were analyzed initially without any correction and subsequently using either weights’ truncation or normalization. In the second class, data were analyzed either filling-in the missing values with the Last Observation Carried Forward (LOCF), or after imputing them by Multiple Imputation (MI) or accounting for missingness through additional weighting with the Inverse Probability of Missingness (IPMW). Furthermore, we analysed data from the HEPNET.Greece study for viral hepatitis B, in order to evaluate the effect of treatment and the treatment type (Interferon (IFN) +/- Nucleos(t)ide (NA) vs. NA) to the occurrence of a clinical event in CHB patients. Results of this thesis suggest that data from observational studies can provide us with useful inference, given that they are analyzed appropriately. Even in the presence of problems related to missing confounding data or irregular observational plans that are often met in observational studies, sophisticated approaches to account for potential bias can be incorporated into the MSM. (EN)

Greek

Σχολή Επιστημών Υγείας » Τμήμα Ιατρικής » Τομέας Κοινωνικής Ιατρικής - Ψυχιατρικής και Νευρολογίας

Βιβλιοθήκη και Κέντρο Πληροφόρησης » Βιβλιοθήκη Επιστημών Υγείας

https://creativecommons.org/licenses/by-nc/4.0/

University of Athens

Pergamos Digital Library

Doctoral Dissertation