Departmaent of Biostatistics
Harvard Medical School
United States Virgin Islands
Dr. Rebecca Betensky’s current methodological research interests are in the areas of survival data, clinical trials, and biomarker studies, as motivated by problems that arise in studies of neurologic diseases and cancer. Within survival analysis, she is working on methods of inference in the presence of dependent truncation. She has developed methods for efficient subject and endpoint selection in Alzheimer’s disease clinical trials and for overcoming the placebo effect in chronic disease trials. She has recently examined the effects of subject compensation on statistical inference from clinical trials, and the reporting of follow-up time and its various meanings. Dr. Betensky’s current research also includes the development of statistical methods for biomarker identification in the presence of time varying endpoints with censoring and truncation and in the absence of a gold standard. She is extending these methods to handle very high dimensional biomarkers, such as gene expression arrays and imaging studies, for which standard methods break down.
Biomarker studies Alzheimer’s disease Very high dimensional biomarkers studies Statistical Methods for Analysis of Array CGH Data Signal processing for accurate detection of copy number variants in cancer Specialized Programs of Translational Research in Acute Stroke at the Partners
Singh K, Betensky RA, Wright A, Curhan GC, Bates DW, Waikar SS. A Concept-Wide Association Study of Clinical Notes to Discover New Predictors of Kidney Failure. Clin J Am Soc Nephrol. 2016 Dec 07; 11(12):2150-2158. PMID: 27927892.
Dhilla Albers A, Asafu-Adjei J, Delaney MK, Kelly KE, Gomez-Isla T, Blacker D, Johnson KA, Sperling RA, Hyman BT, Betensky RA, Hastings L, Albers MW. Episodic memory of odors stratifies Alzheimer biomarkers in normal elderly. Ann Neurol. 2016 Dec; 80(6):846-857. PMID: 27696605.
Emerson SC, Waikar SS, Fuentes C, Bonventre JV, Betensky RA. Biomarker validation with an imperfect reference: Issues and bounds. Stat Methods Med Res. 2017 Jan 01; 962280216689806. PMID: 28166709.
Asafu-Adjei J, Mahlet GT, Coull B, Balasubramanian R, Lev M, Schwamm L, Betensky R. Bayesian Variable Selection Methods for Matched Case-Control Studies. Int J Biostat. 2017 Jan 31; 13(1). PMID: 28157692.
Qian J, Wolters FJ, Beiser A, Haan M, Ikram MA, Karlawish J, Langbaum JB, Neuhaus JM, Reiman EM, Roberts JS, Seshadri S, Tariot PN, Woods BM, Betensky RA, Blacker D. APOE-related risk of mild cognitive impairment and dementia for prevention trials: An analysis of four cohorts. PLoS Med. 2017 Mar; 14(3):e1002254. PMID: 28323826.
Arbel-Ornath M, Hudry E, Boivin JR, Hashimoto T, Takeda S, Kuchibhotla KV, Hou S, Lattarulo CR, Belcher AM, Shakerdge N, Trujillo PB, Muzikansky A, Betensky RA, Hyman BT, Bacskai BJ. Soluble oligomeric amyloid-ß induces calcium dyshomeostasis that precedes synapse loss in the living mouse brain. Mol Neurodegener. 2017 Mar 21; 12(1):27. PMID: 28327181.
Hanseeuw BJ, Betensky RA, Schultz AP, Papp KV, Mormino EC, Sepulcre J, Bark JS, Cosio DM, LaPoint M, Chhatwal JP, Rentz DM, Sperling RA, Johnson KA. Fluorodeoxyglucose metabolism associated with tau-amyloid interaction predicts memory decline. Ann Neurol. 2017 Apr; 81(4):583-596. PMID: 28253546.
Qian J, Hyman BT, Betensky RA. Neurofibrillary Tangle Stage and the Rate of Progression of Alzheimer Symptoms: Modeling Using an Autopsy Cohort and Application to Clinical Trial Design. JAMA Neurol. 2017 May 01; 74(5):540-548. PMID: 28288263.
Dr. Betensky is Co-Course Director for HST 190: Introduction to Biostatistics and Epidemiology (January term course).
Dr. Betensky is instructor of BIO230: Statistical Inference I for Spring 2014.