Bo Zhang

Bo Zhang
Fred Hutchinson Cancer Research Center | Fred Hutch

PhD

About

36
Publications
2,030
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70
Citations

Publications

Publications (36)
Article
Objective To work towards automating Transcranial Doppler (TCD) imaging data in cerebral malaria (CM) patients. Methods Functional principal component analysis (FPCA) was used to identify important features of TCD data and quantify its variation explained by each feature. Cox regression was used to test the association between TCD measurements and...
Article
One central goal of design of observational studies is to embed non-experimental data into an approximate randomized controlled trial using statistical matching. Despite empirical researchers’ best intention and effort to create high-quality matched samples, residual imbalance due to observed covariates not being well matched often persists. Althou...
Article
Objective : To identify and quantify the predictors of intraoperative TEE use among patients undergoing cardiac valve or isolated coronary artery bypass graft (CABG) surgery. Design : Observational cohort study Setting : This study used Centers for Medicare and Medicaid Services (CMS) administrative claims dataset of beneficiaries undergoing valv...
Article
Full-text available
OBJECTIVE: Propose a theoretical framework for retinal biomarkers of Alzheimer's disease (AD). BACKGROUND: The retina and brain share important biological features that are relevant to AD. Developing retinal biomarkers of AD is a strategic priority but as yet none have been validated for clinical use. Part of the reason may be that fundamental infe...
Preprint
In an observational study, it is common to leverage known null effect to detect bias. One such strategy is to set aside a placebo sample -- a subset of data immune from the hypothesized cause-and-effect relationship. Existence of an effect in the placebo sample raises concern of unmeasured confounding bias while absence of it corroborates the causa...
Preprint
Full-text available
Many recent efforts center on assessing the ability of real-world evidence (RWE) generated from nonrandomized observational data to provide results that are compatible with those from randomized controlled trials (RCTs). One noticeable endeavor is the RCT DUPLICATE initiative (Franklin et al., 2020). To better reconcile findings from observational...
Research
Full-text available
This is a complete tutorial for R package match2C, available via CRAN.
Article
Full-text available
Background: Cerebral malaria is still a major cause of death in children in sub-Saharan Africa. Among survivors, debilitating neurological sequelae can leave children with permanent cognitive impairments and societal stigma, resulting in taxing repercussions for their families. This study investigated the effect of delay in presentation to medical...
Article
Importance: Intraoperative transesophageal echocardiography (TEE) is used frequently in cardiac valve and proximal aortic surgical procedures, but there is a lack of evidence associating TEE use with improved clinical outcomes. Objective: To test the association between intraoperative TEE use and clinical outcomes following cardiac valve or prox...
Preprint
Full-text available
We examine the role of textual data as study units when conducting causal inference by drawing parallels between human subjects and organized texts. %in human population research. We elaborate on key causal concepts and principles, and expose some ambiguity and sometimes fallacies. To facilitate better framing a causal query, we discuss two strateg...
Preprint
Randomized controlled trials (RCTs) are the gold standard for evaluating the causal effect of a treatment; however, they often have limited sample sizes and sometimes poor generalizability. On the other hand, non-randomized, observational data derived from large administrative databases have massive sample sizes and better generalizability, but the...
Article
Multivariate matching has two goals: (i) to construct treated and control groups that have similar distributions of observed covariates, and (ii) to produce matched pairs or sets that are homogeneous in a few key covariates. When there are only a few binary covariates, both goals may be achieved by matching exactly for these few covariates. Commonl...
Preprint
Full-text available
One central goal of design of observational studies is to embed non-experimental data into an approximate randomized controlled trial using statistical matching. Researchers then make the randomization assumption in their downstream, outcome analysis. For matched pair design, the randomization assumption states that the treatment assignment across...
Article
Instrumental variable methods are widely used in medical research to draw causal conclusions when the treatment and outcome are confounded by unmeasured confounding variables. One important feature of such studies is that the instrumental variable is often applied at the cluster level, e.g., hospitals' or physicians' preference for a certain treatm...
Preprint
Full-text available
Estimating dynamic treatment regimes (DTRs) from retrospective observational data is challenging as some degree of unmeasured confounding is often expected. In this work, we develop a framework of estimating properly defined "optimal" DTRs with a time-varying instrumental variable (IV) when unmeasured covariates confound the treatment and outcome,...
Article
Individualized treatment rules (ITRs) are considered a promising recipe to deliver better policy interventions. One key ingredient in optimal ITR estimation problems is to estimate the average treatment effect conditional on a subject’s covariate information, which is often challenging in observational studies due to the universal concern of unmeas...
Article
Background Coronary artery bypass graft (CABG) surgery is the most widely performed cardiac surgery in the US. Transesophageal echocardiography (TEE) is frequently used in a variety of cardiac surgeries, but its clinical benefit in isolated CABG surgery is unclear and guidelines remain indeterminate. This study aimed to compare clinical outcomes am...
Preprint
Full-text available
Subclassification and matching are often used to adjust for observed covariates in observational studies; however, they are largely restricted to relatively simple study designs with a binary treatment. One important exception is Lu et al. (2001), who considered optimal pair matching with a continuous treatment dose. In this article, we propose two...
Preprint
Full-text available
Social distancing is widely acknowledged as an effective public health policy combating the novel coronavirus. But extreme social distancing has costs and it is not clear how much social distancing is needed to achieve public health effects. In this article, we develop a design-based framework to make inference about the dose-response relationship...
Research Proposal
Full-text available
Social distancing is considered one of the most useful public health measures combating the novel coronavirus transmission. It is of great interest to understand the ``dose-response" relationship between the level of social distancing and its effect on public health related outcomes, in particular the COVID-19-related death toll. Since late April a...
Article
We conducted a matched observational study to investigate the causal relationship between second‐hand smoke and blood lead levels in children. Our first analysis that assumes no unmeasured confounding suggests evidence of a detrimental effect of second‐hand smoke. However, unmeasured confounding is a concern in our study as in other observational s...
Preprint
Full-text available
Instrumental variable methods are widely used in medical and social science research to draw causal conclusions when the treatment and outcome are confounded by unmeasured confounding variables. One important feature of such studies is that the instrumental variable is often applied at the cluster level, e.g., hospitals' or physicians' preference f...
Article
Link to the paper: https://journals.lww.com/epidem/Citation/9000/Number_of_Healthcare_Workers_Who_Have_Died_of.98394.aspx
Preprint
Full-text available
Background: Coronary artery bypass graft (CABG) surgery is the most widely performed adult cardiac surgery in the US. Transesophageal echocardiography (TEE) is an ultrasound-based cardiac imaging modality used in CABG surgery for hemodynamic monitoring and management of complications related to cardiopulmonary bypass. However, there are no comparat...
Preprint
Full-text available
We construct matched groups of U.S. counties that had high levels of social distancing vs. low levels of social distancing during the week of March 16-22 but similar levels of demographic, socioeconomic and disease transmission confounding variables, and examine the difference between the counties’ fever rates two and three weeks later. Our approac...
Preprint
Full-text available
The novel coronavirus disease (COVID-19) is a highly contagious respiratory disease that was first detected in Wuhan, China in December 2019, and has since spread around the globe, claiming more than 69,000 lives by the time this protocol is written. It has been widely acknowledged that the most effective public policy to mitigate the pandemic is \...
Article
Background: Cerebral malaria (CM) remains a leading cause of mortality and morbidity in children in sub-Saharan Africa. Recent studies using brain magnetic resonance imaging have revealed increased brain volume as a major predictor of death. Similar morphometric predictors of morbidity at discharge are lacking. The aim of this study was to investi...
Article
It is common to compare individualized treatment rules based on the value function, which is the expected potential outcome under the treatment rule. Although the value function is not point-identified when there is unmeasured confounding, it still defines a partial order among the treatment rules under Rosenbaum’s sensitivity analysis model. We fi...
Preprint
Full-text available
It is common to compare individualized treatment rules based on the value function, which is the expected potential outcome under the treatment rule. Although the value function is not point-identified when there is unmeasured confounding, it still defines a partial order among the treatment rules under Rosenbaum's sensitivity analysis model. We fi...
Preprint
Full-text available
Individualized treatment rules (ITRs) are considered a promising recipe to deliver better policy interventions. One key ingredient in optimal ITR estimation problems is to estimate average treatment effect conditional on a subject's covariate information, which is often challenging in observational studies due to the universal concern of unmeasured...
Preprint
Full-text available
Instrumental variables (IV) are extensively used to estimate treatment effects in the presence of unmeasured confounding; however, weak IVs are often encountered in empirical studies and may cause problems. Many studies have considered building a stronger IV from the original, possibly weak, IV in the design stage of a matched study at the cost of...
Preprint
Full-text available
When drawing causal inference from observational data, there is always concern about unmeasured confounding. One way to tackle this is to conduct a sensitivity analysis. One widely-used sensitivity analysis framework hypothesizes the existence of a scalar unmeasured confounder U and asks how the causal conclusion would change were U measured and in...
Preprint
Full-text available
Matched observational studies are commonly used to study treatment effects in non-randomized data. After matching for observed confounders, there could remain bias from unobserved confounders. A standard way to address this problem is to do a sensitivity analysis. A sensitivity analysis asks how sensitive the result is to a hypothesized unmeasured...
Conference Paper
Accurate gene tree-species tree reconciliation is fundamental to understanding evolutionary processes across species. However, within eukaryotes, the most popular algorithms consider only a restricted set of evolutionary events, typically modeling only duplications and losses or only coalescences. Recent work has unified duplications, losses, and c...

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