Rebecca A Betensky
Rebecca Betensky
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Chair of the Department of Biostatistics
Professor of Biostatistics
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Professional overview
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Prior to NYU, Dr. Betensky was Professor of Biostatistics at the Harvard T.H. Chan School of Public Health. She was director of the Harvard Catalyst (Clinical and Translational Science Award) Biostatistics Program; director of the Data and Statistics Core for the Massachusetts Alzheimer’s Disease Research Center; and director of the Biostatistics Neurology Core at Massachusetts General Hospital. Previously, she was the Biostatistics Program Leader for the Dana-Farber/Harvard Cancer Center.
Dr. Betensky’s research focuses on methods for the analysis of censored and truncated outcomes and covariates, which frequently arise from the subsampling of cohort studies. She has a long-time interest in clinical trials, and has written on the evaluation of biomarkers and the use and interpretation of p-values. She has collaborated extensively in studies in neurologic diseases, and serves as statistical editor for Annals of Neurology.
Dr. Betensky was awarded, and directed for 15 years, an NIH T32 training program in neurostatistics and neuroepidemiology for pre- and post-doctoral students in biostatistics and epidemiology and for clinician-scientists. She previously directed Harvard’s Biostatistics programs to promote and support diversity at all levels in the field of quantitative public health. She was also a member of the BMRD Study Section for review of NIH statistical methodology grants; on committees for the Institute of Medicine; and a co-chair of the technical advisory committee for the scientific registry of transplant recipients.
Dr. Betensky an elected Fellow of the American Statistical Association and of the International Statistical Institute, and is a past recipient of the Spiegelman Award from the American Public Health Association. She currently serves as a member of the Board of Scientific Counselors for Clinical Science and Epidemiology at the National Cancer Institute.
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Education
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AB, Mathematics, Harvard University, Cambridge, MAPhD, Statistics, Stanford University, Stanford, CA
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Areas of research and study
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BiologyBiostatisticsNeuroepidemiologyNeurologyNeurostatisticsTranslational science
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Publications
Publications
Neuronal calcineurin transcriptional targets parallel changes observed in Alzheimer disease brain
Failed retrieving data.Permutation tests for general dependent truncation
Failed retrieving data.PET staging of amyloidosis using striatum
Failed retrieving data.Polygenic pleiotropy and potential causal relationships between educational attainment, neurobiological profile, and positive psychotic symptoms
Failed retrieving data.Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI
Failed retrieving data.rBPI21 (opebacan) promotes rapid trilineage hematopoietic recovery in a murine model of high-dose total body irradiation
AbstractJanec, K. J., Yuan, H., Norton, J. E., Kelner, R. H., Hirt, C. K., Betensky, R., & Guinan, E. C. (n.d.).Publication year
2018Journal title
American Journal of HematologyVolume
93Issue
8Page(s)
1002-1013AbstractThe complexity of providing adequate care after radiation exposure has drawn increasing attention. While most therapeutic development has focused on improving survival at lethal radiation doses, acute hematopoietic syndrome (AHS) occurs at substantially lower exposures. Thus, it is likely that a large proportion of such a radiation-exposed population will manifest AHS of variable degree and that the medical and socioeconomic costs of AHS will accrue. Here, we examined the potential of rBPI21 (opebacan), used without supportive care, to accelerate hematopoietic recovery after radiation where expected survival was substantial (42%-75%) at 30 days. rBPI21 administration was associated with accelerated recovery of hematopoietic precursors and normal marrow cellularity, with increases in megakaryocyte numbers particularly marked. This translated into attaining normal trilineage peripheral blood counts 2-3 weeks earlier than controls. Elevations of hematopoietic growth factors observed in plasma and the marrow microenvironment suggest the mechanism is likely multifactorial and not confined to known endotoxin-neutralizing and cytokine downmodulating activities of rBPI21. These observations deserve further exploration in radiation models and other settings where inadequate hematopoiesis is a prominent feature. These experiments also model the potential of therapeutics to limit the allocation of scarce resources after catastrophic exposures as an endpoint independent of lethality mitigation.Reader response : Systematic review and statistical analysis of the integrity of 33 randomized controlled trials
Betensky, R., & Chiou, S. H. (n.d.).Publication year
2018Journal title
NeurologyVolume
90Issue
12Page(s)
578Tau induces blood vessel abnormalities and angiogenesis-related gene expression in P301L transgenic mice and human Alzheimer's disease
Failed retrieving data.The prognostic value of histopathologic lesions in native kidney biopsy specimens : Results from the Boston kidney biopsy cohort study
Failed retrieving data.Threshold regression to accommodate a censored covariate
AbstractQian, J., Chiou, S. H., Maye, J. E., Atem, F., Johnson, K. A., & Betensky, R. (n.d.).Publication year
2018Journal title
BiometricsVolume
74Issue
4Page(s)
1261-1270AbstractIn several common study designs, regression modeling is complicated by the presence of censored covariates. Examples of such covariates include maternal age of onset of dementia that may be right censored in an Alzheimer's amyloid imaging study of healthy subjects, metabolite measurements that are subject to limit of detection censoring in a case-control study of cardiovascular disease, and progressive biomarkers whose baseline values are of interest, but are measured post-baseline in longitudinal neuropsychological studies of Alzheimer's disease. We propose threshold regression approaches for linear regression models with a covariate that is subject to random censoring. Threshold regression methods allow for immediate testing of the significance of the effect of a censored covariate. In addition, they provide for unbiased estimation of the regression coefficient of the censored covariate. We derive the asymptotic properties of the resulting estimators under mild regularity conditions. Simulations demonstrate that the proposed estimators have good finite-sample performance, and often offer improved efficiency over existing methods. We also derive a principled method for selection of the threshold. We illustrate the approach in application to an Alzheimer's disease study that investigated brain amyloid levels in older individuals, as measured through positron emission tomography scans, as a function of maternal age of dementia onset, with adjustment for other covariates. We have developed an R package, censCov, for implementation of our method, available at CRAN.Time-to-event data with time-varying biomarkers measured only at study entry, with applications to Alzheimer's disease
AbstractBetensky, R. (n.d.).Publication year
2018Journal title
Statistics in MedicineVolume
37Issue
6Page(s)
914-932AbstractRelating time-varying biomarkers of Alzheimer's disease to time-to-event using a Cox model is complicated by the fact that Alzheimer's disease biomarkers are sparsely collected, typically only at study entry; this is problematic since Cox regression with time-varying covariates requires observation of the covariate process at all failure times. The analysis might be simplified by using study entry as the time origin and treating the time-varying covariate measured at study entry as a fixed baseline covariate. In this paper, we first derive conditions under which using an incorrect time origin of study entry results in consistent estimation of regression parameters when the time-varying covariate is continuous and fully observed. We then derive conditions under which treating the time-varying covariate as fixed at study entry results in consistent estimation. We provide methods for estimating the regression parameter when a functional form can be assumed for the time-varying biomarker, which is measured only at study entry. We demonstrate our analytical results in a simulation study and apply our methods to data from the Rush Religious Orders Study and Memory and Aging Project and data from the Alzheimer's Disease Neuroimaging Initiative.APOE-related risk of mild cognitive impairment and dementia for prevention trials : An analysis of four cohorts
Failed retrieving data.Association of cancer and Alzheimer's disease risk in a national cohort of veterans
Failed retrieving data.Bayesian Variable Selection Methods for Matched Case-Control Studies
AbstractAsafu-Adjei, J., Mahlet, G. T., Coull, B., Balasubramanian, R., Lev, M., Schwamm, L., & Betensky, R. (n.d.).Publication year
2017Journal title
International Journal of BiostatisticsVolume
13Issue
1AbstractMatched case-control designs are currently used in many biomedical applications. To ensure high efficiency and statistical power in identifying features that best discriminate cases from controls, it is important to account for the use of matched designs. However, in the setting of high dimensional data, few variable selection methods account for matching. Bayesian approaches to variable selection have several advantages, including the fact that such approaches visit a wider range of model subsets. In this paper, we propose a variable selection method to account for case-control matching in a Bayesian context and apply it using simulation studies, a matched brain imaging study conducted at Massachusetts General Hospital, and a matched cardiovascular biomarker study conducted by the High Risk Plaque Initiative.Cognitive resilience in clinical and preclinical Alzheimer’s disease : the Association of Amyloid and Tau Burden on cognitive performance
Failed retrieving data.Correlation among baseline variables yields non-uniformity of p-values
Failed retrieving data.Fluorodeoxyglucose metabolism associated with tau-amyloid interaction predicts memory decline
Failed retrieving data.Is this significant?
Failed retrieving data.Linear regression with a randomly censored covariate : application to an Alzheimer's study
Failed retrieving data.Neurofibrillary tangle stage and the rate of progression of Alzheimer symptoms : Modeling using an autopsy cohort and application to clinical trial design
Failed retrieving data.Soluble oligomeric amyloid-β induces calcium dyshomeostasis that precedes synapse loss in the living mouse brain
Failed retrieving data.A concept-wide association study of clinical notes to discover new predictors of kidney failure
Failed retrieving data.Comparison of urine output among patients treated with more intensive versus less intensive RRT : Results from the acute renal failure trial network study
Failed retrieving data.Decreased hippocampal metabolism in high-amyloid mild cognitive impairment
AbstractHanseeuw, B. J., Schultz, A. P., Betensky, R., Sperling, R. A., & Johnson, K. A. (n.d.).Publication year
2016Journal title
Alzheimer's and DementiaVolume
12Issue
12Page(s)
1288-1296AbstractIntroduction Hippocampal volume (HV), cortical metabolism, and thickness are decreased in mild cognitive impairment (MCI). Hippocampal metabolism (HM) studies comparing MCI and clinically normal (CN) elderly gave inconsistent results. As hippocampus is a key region in Alzheimer's disease, we hypothesized that HM is specifically decreased in high-amyloid MCI. Methods Overall, 250 CN and 45 MCI underwent three-dimensional magnetic resonance imaging, fludeoxyglucose-positron emission tomography, and fluorodeoxyglucose-positron emission tomography (PET), and Pittsburgh Compound B (PiB) PET. We investigated the interaction between clinical and amyloid status on HM, HV, cortical metabolism, and thickness using linear models, covarying age, gender, and education. Analyses were conducted with and without correction for multiple comparisons and for partial volume effects. Results Volume-adjusted HM was decreased in high-amyloid MCI but close to normal in low-amyloid MCI and in high-amyloid CN. Both MCI groups had hippocampal atrophy, although less severe in low-amyloid MCI. High-amyloid CN and high-amyloid MCI had cortical hypometabolism. Discussion HM is decreased when both cognitive impairment and amyloid are present.Episodic memory of odors stratifies Alzheimer biomarkers in normal elderly
Failed retrieving data.