395 research outputs found

    Adjusting the effect of integrating antiretroviral therapy and tuberculosis treatment on mortality for non-compliance : an instrumental variables analysis using a time-varying exposure.

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    Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.In South Africa and elsewhere, research has shown that the integration of antiretroviral therapy (ART) and tuberculosis (TB) treatment saves lives. The randomised controlled trials (RCTs) which provided this compelling evidence used intent-to-treat (ITT) strategy as part of their primary analysis. As much as ITT is protected against selection bias caused by both measured and unmeasured confounders, but it is capable of drawing results towards the null and underestimate the e ectiveness of treatment if there is too much non-compliance. To adjust for non-compliance, \as-treated"and \per-protocol"comparisons are commonly made. These contrast study participants according to their received treatment, regardless of the treatment arm to which they were assigned, or limit the analysis to participants who followed the protocol. Such analyses are generally biased because the subgroups which they compare often lack comparability. In view of the shortcomings of the \as-treated"and \per-protocol"analyses, our objective was to account for non-compliance by using instrumental variables (IV) analysis to estimate the e ect of ART initiation during TB treatment on mortality. Furthermore, to capture the full complexity of compliance behaviour outside the TB treatment duration, we developed a novel IV-methodology for a time-varying measure of compliance to ART. This is an important contribution to the IV literature since IV-methodology for the e ect of a time-varying exposure on a time-to-event endpoint is currently lacking. In RCTs, IV analysis enable us to make use of the comparability o ered by randomisation and thereby have the capability of adjusting for unmeasured and measured confounders; they have the further advantage of yielding results that are less sensitive to random measurement error in the exposure. In order to carry out IV analysis, one needs to identify a variable called an instrument, which needs to satisfy three important assumptions. To apply the IV methodology, we used data from Starting Antiretroviral Therapy at Three Points in Tuberculosis (SAPiT) trial which was conducted by the Centre for the AIDS Programme of Research in South Africa. This trial enrolled HIV and TB co-infected patients who were assigned to start ART either early or late during TB treatment or after TB treatment completion. The results from IV analysis demonstrate that survival bene t of fully integrating TB treatment and ART is even higher than what has been reported in the ITT analysis since non-compliance has been accounted for

    Analyzing two-stage experiments in the presence of interference

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    Two-stage randomization is a powerful design for estimating treatment effects in the presence of interference; that is, when one individual's treatment assignment affects another individual's outcomes. Our motivating example is a two-stage randomized trial evaluating an intervention to reduce student absenteeism in the School District of Philadelphia. In that experiment, households with multiple students were first assigned to treatment or control; then, in treated households, one student was randomly assigned to treatment. Using this example, we highlight key considerations for analyzing two-stage experiments in practice. Our first contribution is to address additional complexities that arise when household sizes vary; in this case, researchers must decide between assigning equal weight to households or equal weight to individuals. We propose unbiased estimators for a broad class of individual- and household-weighted estimands, with corresponding theoretical and estimated variances. Our second contribution is to connect two common approaches for analyzing two-stage designs: linear regression and randomization inference. We show that, with suitably chosen standard errors, these two approaches yield identical point and variance estimates, which is somewhat surprising given the complex randomization scheme. Finally, we explore options for incorporating covariates to improve precision. We confirm our analytic results via simulation studies and apply these methods to the attendance study, finding substantively meaningful spillover effects.Comment: Accepted for publication in the Journal of the American Statistical Associatio

    Assessing sensitivity of Early Head Start study findings to manipulated randomization threats

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    The Association Between Medication Adherence in Mental Illness and Substance Use Disorder Relapse in Patients with Dual Diagnosis

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    Objectives: The aims of the study were to (1) identify personal, social, and clinical history for patients with substance use disorder (SUD) and mental illness, (2) measure agreeance between patient self-report versus facility record history for mental illness, substance abuse, and psychotropic medication, (3) investigate the specific role of medication adherence and barriers to use for psychotropic medications upon SUD relapse, and (4) assess follow-up changes in mental illness severity and medication adherence in dual diagnosis patients enrolled in a substance abuse rehabilitation program. Methods: The pilot study utilized a mixed methodology. Inclusion criteria included male patients at least 18 years of age who were newly admitted at a 90-day residential rehabilitation program with a self-reported diagnosis of SUD, and either major depressive disorder (MDD), bipolar disorder, generalized anxiety disorder (GAD) or schizophrenia. Patients were evaluated within their first week of treatment and follow-up interviews were conducted at 1 and 2 months. Facility records were accessed to cross-reference patient reported data, using Cohen’s kappa coefficient to determine agreement. Patient demographic characteristics, substance abuse characteristics, health-related characteristics, and attitude towards medications stratified by adherence rates and relapse rates utilizing ANOVA and t-tests. Pearson’s correlation coefficient was utilized to analyze the relationship between medication adherence and SUD relapse. A multivariable logistic regression model was created to assess the impact of adherence on relapse frequency. Patient and clinical characteristics were stratified according to follow-up interviews completed utilizing ANOVA and t-tests. Lastly, changes in patients’ self reported adherence from interview to interview were analyzed using mean difference. SPSS Statistics (IBM Corp; Armonk, NY) was utilized for all analyses, with a two-tailed level of significance at 0.05. Results: The final sample consisted of 38 patients. The majority of patients were white (n=27, 71.1%), unemployed (n=32, 84.2%), and homeless (n=30, 78.9%). Heroin was the most common primary drug of use (n=19, 50%), followed by alcohol (n=12, 31.6%), and crack cocaine (n=4, 10.5%). The average length of substance use was 20.3 years. Half of the patients (n=19, 50%) had two or more mental illness diagnoses and the most common was the combination of MDD and GAD (n=9, 23.7%), followed by MDD alone (n=7, 18.4%), and bipolar disorder (n=6, 15.8%). Significant agreeance was found between patient self-reported data to facility records for primary substance of use (κ=0.753, p Conclusions: The study provided valuable insight into the relationship between psychotropic medication adherence and SUD relapse in patients with dual diagnosis which can be used by healthcare professionals and drug abuse rehabilitation programs

    A First Course in Causal Inference

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    I developed the lecture notes based on my ``Causal Inference'' course at the University of California Berkeley over the past seven years. Since half of the students were undergraduates, my lecture notes only require basic knowledge of probability theory, statistical inference, and linear and logistic regressions

    Links between stress, sleep, and inflammation : a translational perspective of resilience

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    Most individuals will experience one or more extremely traumatic events during their lifetime. For the most part, humans are resilient and have a tremendous capacity to bounce back from hardships; however, for a critical minority, trauma can result in debilitating symptoms, including posttraumatic stress disorder (PTSD). Historically, sleep disturbance and inflammation were viewed as symptoms or consequences of PTSD; however, recently there has been a shift towards conceptualizing sleep disturbance and inflammation as early indications of mental health issues to come. This thesis examined the inextricable link between stress, sleep, and inflammation, and how gaining a better understanding of these interconnected systems could be harnessed to develop enhanced treatments for populations with stress-related symptoms and disorders. Study I investigated the effect of standardized sleep therapy on posttraumatic stress symptoms, as well as the gene expression pathways that may mediate this effect in sleep disturbed military service members with PTSD (n =39) and controls without PTSD (n = 27). At baseline, participants diagnosed with insomnia and/or obstructive sleep apnea received a combination of 4 to 8 biweekly sessions of cognitive behavioral therapy for insomnia (CBT-I), and automatic positive airway pressure therapy. Results indicated that 22.6% of participants with PTSD had clinically meaningful posttraumatic stress symptom reduction following standardized sleep therapy. Posttraumatic stress symptoms were linked to increased expression of genes associated with immune response systems, which were downregulated with symptom reduction at follow-up. In order to investigate alternative interventions that may improve sleep quality and potentially provide additional benefits for stress-related disorders, Study II was a metaanalysis to determine the effect of mindfulness meditation on sleep quality outcomes in sleep disturbed adults with various mental and physical health conditions. To assess for relative efficacy, mindfulness meditation was compared to evidence-based sleep treatments (like CBT-I and medication) and time/attention-matched interventions to control for placebo effects, which were analyzed separately. The results indicated that mindfulness meditation had a similar effect on sleep quality compared to the evidence-based sleep treatments and was superior to the time/attention matched placebo controls. However, the strength of this evidence was low to moderate, so some doubt remains. Stress, Sleep, and Inflammation Once mindfulness meditation was established as a potential intervention to improve sleep quality, Study III investigated if sleep quality improvements, following a 4-week mindfulness-based integrative medicine program, were associated with reductions in posttraumatic stress, anxiety, depression, and postconcussion symptoms in sleep disturbed military service members with mild traumatic brain injury (n = 93). The secondary aim was to determine if sleep quality improvements were associated with decreases in protein levels of inflammation. Results indicated that sleep quality improvements, following the intervention, were linked to reductions in posttraumatic stress and other neurobehavioral symptoms, but not to inflammation. Moreover, 65.8% of participants with PTSD had clinically meaningful posttraumatic stress symptom reduction at follow-up. While we found some evidence that posttraumatic stress symptoms were reduced following the mindfulness-based integrative medicine program, this program required almost 30 treatment hours. This may be an excessive treatment duration when mindfulness meditation is used in populations with less severe symptoms. As such, Study IV investigated the effect of a brief 5-week (7.5-hour) mindfulness meditation program on perceived stress symptoms in moderately stressed healthcare professionals. Participants were randomized to the mindfulness-based self-care (MBSC) group (n = 43) or the life-as-usual control group (n = 35). Results indicated that the meditation group had larger reductions in perceived stress, and these reductions were maintained two months following the completion of the program. Taken together, the findings of these four studies led to some important conclusions regarding the link between stress, sleep, and inflammation. While mindfulness research is still in its infancy, these preliminary results suggest that mindfulness meditation is effective in improving sleep in adult populations with various mental and physical health conditions (Study II). Less intense mindfulness meditation programs (7.5 hours) may be beneficial to reduce perceived stress, which could potentially prevent the development of more severe mental health conditions (Study IV). While 22.6% of individuals with PTSD had reduced posttraumatic stress symptoms following standardized sleep therapy (Study I), 65.8% of individuals with PTSD had reduced posttraumatic stress symptoms following the mindfulness-based integrative medicine program (Study III). There was some evidence that a relationship exists between sleep quality improvements, decreases in gene expression levels of inflammation, and reductions in posttraumatic stress symptoms; although the direction of causality cannot be determined (Study I and III). Clinical implications and recommendations for future research will be discussed
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