Adjunct Associate Professor, of Biostatistics
Harvard T.H. Chan School of Public Health
Harvard School of Public Health
655 Huntington Ave
Boston MA 02115
My research focuses on the development and application of causal inference statistical methods for problems in HIV/AIDS research, with a special focus on the effects of highly active antiretroviral treatment, HAART. I have established strong productive interest in this area with important theoretical contributions in Statistica Neerlandica, the Scandinavian Journal of Statistics, the Annals of Statistics, Biometrics, and Biostatistics. I have a strong record in the application of novel causal inference methods to longitudinal observational studies of HIV-positive patients. For example, (1) I have analyzed the risk of cardiovascular outcomes associated with Abacavir use [Ribaudo et al., CID 2011]. For this project, we have applied Marginal Structural Models. (2) I have investigated the impact of age on the prognostic capacity of CD8+ T-cell activation during suppressive antiretroviral therapy [Lok et al., AIDS 2013, and Schnitzer et al., accepted by Biostatistics]. For this project, we have developed doubly robust, optimal estimators for a prediction model for the probability of an event occurring at or before a pre-specified point in time. (3) In collaboration with Kiragga and Yiannoutsos, I have estimated the CD4 count trajectory adjusting for dropout among HIV-positive patients receiving HAART in an East African HIV care center [Kiragga et al, JAIDS 2014]. Extra complication in this latter analysis was that dropout from this cohort depends on the survival status of the patients at the time of the first missed visit, as became apparent from data collected from patients after they dropped out of the study. (4) I have introduced “organic” direct and indirect effects, aiming to estimate how much of the effect of a treatment is mediated by a covariate that cannot be “set” to any specific value [Lok, submitted to Statistics in Medicine]. (5) I have developed a new class of Structural Nested Mean Models to evaluate the impact of timing of starting treatment following infection. I have applied this to investigate the impact of time between infection and HAART initiation on immune reconstitution in early-stage HIV-positive patients [Lok et al., Biometrics 2012]. (6) We have applied Inverse Probability of Censoring Weighting to investigate factors associated with remaining on initial randomized efavirenz-containing regimens [Smurzynski et al, AIDS 2013]. (7) I have evaluated the long-term CD4 count trajectory under HAART of HIV-positive patients in the US, additionally evaluating what the CD4 trajectory might have been had some patients not discontinued antiretroviral therapy when their CD4 counts increased to high levels (reflecting treatment management practices at the time) [Lok et al., AIDS 2010].
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(LOK, JUDITH JACQUELINE)
Mar 19, 2012 - Feb 29, 2016
Methods to find and model predictors of the causal effect of HAART
Role: Principal Investigator
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