DEGREE (if applicable) A.B. Ph.D.

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1 OMB No /0002 (Rev. 08/12 Approved Through 8/31/2015) NAME: Rebecca Betensky BIOGRAPHICAL SKETCH Provide the following information for the Senior/key personnel and other significant contributors. Follow this format for each person. DO NOT EXCEED FIVE PAGES. era COMMONS USER NAME (credential, e.g., agency login): RBETENSKY POSITION TITLE: Professor of Biostatistics EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.) INSTITUTION AND LOCATION DEGREE (if applicable) Completion Date MM/YYYY FIELD OF STUDY Harvard University, Cambridge, MA Stanford University, Stanford, CA A.B. Ph.D. 06/87 09/92 Mathematics Statistics A. Personal Statement Dr. Betensky has served as Director of BERD for the Harvard Catalyst (Clinical and Translational Science Award) since In this capacity, she directs Catalyst s biostatistics and bioinformatics consulting service, along with its extensive educational programs for junior and senior level statisticians, epidemiologists, bioinformaticians and for clinical/translational investigators. The focus of her research is the development of statistical methods for the analysis of censored and truncated data. It is often motivated by problems that arise in her collaborative clinical/translational research using observational cohorts in Alzheimer s disease and other disease settings. She is currently working on the problem of dependent truncation, which is pervasive across application areas, and although a tractable problem, has not been solved in a satisfactory manner in the literature. She is also motivated by a wide breadth of problems that arise from Catalyst consultations: e.g., missing continuation endpoints due to early death, censored covariates in regression models, and biomarker validation in the absence of a gold standard. Additionally, she has published on statistical foundations and principles for clinical audiences. She has served as PI of the Data and Statistics Core of the Massachusetts Alzheimer s Disease Research Center (ADRC) since She is PI of a T32 training grant from NINDS (Training in Neurostatistics and Neuroepidemiology), which trains pre- and post-doctoral students and physician scientists in neuro-focused methods research, she teaches and advises PhD students and post-doctoral fellows in Biostatistics, and she serves as a statistical mentor for a K12 training grant in Neuro-oncology and the Catalyst KL2 program. 1. Betensky RA. Is this significant? Ann Neurol Mar;81(3): PubMed PMID: Matsouaka RA, Singhal AB, Betensky RA. An optimal Wilcoxon-Mann-Whitney test of mortality and a continuous outcome. Stat Methods Med Res PMCID: PMC Atem FD, Qian J, Maye JE, Johnson KA, Betensky, RA. Linear Regression with a Randomly Censored Covariate: Application to an Alzheimer s Study. Journal of the Royal Statistical Society, Series C 2017; 66(2): PMCID: PMC Emerson SC, Waikar SS, Fuentes C, Bonventre JV, Betensky RA. Biomarker validation with an imperfect reference: Issues and bounds. Stat Methods Med Res PubMed PMID: B. Positions and Honor Positions and Employment Postdoctoral Scholar, Department of Health Research and Policy, Division of Epidemiology, Stanford University, Stanford, CA Assistant Professor, Departments of Preventive Medicine and Statistics, Northwestern University, Chicago, IL Assistant Professor, Department of Biostatistics, Harvard School of Public Health, Boston, MA Assistant Biostatistician, Massachusetts General Hospital, Boston, MA Associate Professor, Department of Biostatistics, Harvard School of Public Health, Boston, MA Associate Biostatistician, Massachusetts General Hospital, Boston, MA

2 Director of Statistics, Harvard NeuroDiscovery Center, Boston, MA Co-Leader Biostatistics Program, Dana-Farber/Harvard Cancer Center, Boston, MA Leader Biostatistics Program, Dana-Farber/Harvard Cancer Center, Boston, MA Biostatistician, Massachusetts General Hospital, Boston, MA Professor, Department of Biostatistics, Harvard School of Public Health, Boston, MA Member, Affiliated Faculty, Harvard-MIT Division of Health Sciences and Technology (HST) Director, Data and Statistics Core, Alzheimer s Disease Research Center, Massachusetts General Hospital, Boston, MA Director, Harvard Catalyst Biostatistics Program, Harvard University, Boston, MA Visiting Scholar, Department of Statistics and Operations Research, Tel Aviv University (Fall Semester) Other Experience and Professional Memberships Associate Editor: Biostatistics ( ), Biometrics ( ), Statistics in Medicine ( ), Lifetime Data Analysis ( ), Neuro-Oncology ( ) Permanent Member, Biostatistical Methods and Research Design (BMRD) Study Section Permanent Member, Cancer Biomarkers Study Section (CBSS) Statistical Consultant, New England Journal of Medicine Member, Institute of Medicine Committee on Cognitive Behavioral Therapy for Traumatic Brain Injury Member, Institute of Medicine Committee on Health Effects of Agent Orange Statistical Editor, Annals of Neurology Co-Chair: Technical Advisory Committee for the Scientific Registry of Transplant Recipients Member, Board of Scientific Counselors for Clinical Sciences and Epidemiology, National Cancer Institute Honors 1987 A.B. Harvard University, cum laude in Mathematics 1996 Schering-Plough Junior Faculty Award 1998 FIRST Award 2003 Fellow of the American Statistical Association 2005 Mortimer Spiegelman Award for outstanding contributions to health statistics from the American Public Health Association 2007 Elected Member, International Statistical Institute 2016 Keynote Speaker, Annual Joint Biostatistics Symposium, co-sponsored by The Ohio State University, Case Western Reserve University and Cleveland Clinic Foundation 2017 Director s Award for Educational Contributions to the Harvard/MIT HST program C. Contributions to Science Dr. Betensky has published over 224 papers in statistical and medical journals. She has served as the senior author on many of the methods papers and the leading statistician on many of the collaborative papers. ( ). 1. Methods for analyzing truncated survival data: Dr. Betensky has developed methods for testing for goodness of fit of a truncation distribution and for dependent truncation, and for estimation of various types of doubly truncated data. It is often motivated by problems that arise in her collaborative clinical/translational research using observational cohorts in Alzheimer s disease and other disease settings. a. Betensky RA and Mandel M. Recognizing the problem of delayed entry in time-to-event studies: Better late than never for clinical neuroscientists. Ann.of Neurol (6): PMID b. Qian J, Betensky RA. Assumptions regarding right censoring in the presence of left truncation. Stat Probab Lett Apr 1;87: PMCID: PMC c. Austin MD, Betensky RA. Eliminating bias due to censoring in Kendall's tau estimators for quasiindependence of truncation and failure. Comput Stat Data Anal May 14;73: PMC d. Austin MD, Simon DK, Betensky RA. Computationally simple estimation and improved efficiency for special cases of double truncation. Lifetime Data Anal. 2014: 20: PMCID: PMC Design and analysis of clinical trials: Dr. Betensky has developed methods for design and analysis of sequential trials for efficacy and futility and adaptive designs for reestimation of nuisance parameters and overcoming placebo effects. She demonstrated an approach for derivation of an optimal design using existing data sources. She examined the measure of follow-up in reports of clinical trials.

3 a. 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 Mar 13. PubMed PMID: b.betensky RA. (2015) Measures of follow-up in time-to-event studies: Why provide them and what should they be? Clinical Trials. 12(4): PMCID: PMC c. Mi MY, Betensky RA. An analysis of adaptive design variations on the sequential parallel comparison design for clinical trials. Clin Trials Apr;10(2): PMCID: PMC d. Macklin EA, Blacker D, Hyman BT, Betensky RA. Improved design of prodromal Alzheimer's disease trials through cohort enrichment and surrogate endpoints. J Alzheimers Dis Jan 1;36(3): PMCID: PMC Statistical methods for design and analysis of brain tumor studies: Dr. Betensky developed several novel methods for the analysis of brain tumor studies. These addressed design features, such as matched sets of patients with short, standard and long term survival, misclassification due to incomplete pathological examination, and loss of power due to unrecognized heterogeneity. a. Betensky RA, Szymonifka J, Lee EQ, Nutt CL, Batchelor TT. Computationally simple analysis of matched, outcome-based studies of ordinal disease states. Stat Med (17): PMCID:PMC b. Betensky RA, Louis DN, Cairncross JG. Tests of association under misclassification: application to histological sampling in oncology. Stat Med.2007 Nov 20;26(26): PubMed PMID: c. Betensky RA, Louis DN, Cairncross JG. Analysis of a molecular genetic neuro-oncology study with partially biased selection. Biostatistics Apr;4(2): PubMed PMID: d. Betensky RA, Louis DN, Cairncross JG. Influence of unrecognized molecular heterogeneity on randomized clinical trials. J Clin Oncol May15;20(10): PubMed PMID: Statistical methods for class and biomarker discovery: Dr. Betensky has developed novel methods for latent class modeling of high dimensional genetic and imaging markers. She has investigated the problem of variable selection in high dimensional settings. a. Balasubramanian, Raji, E. Andres Houseman, Brent A. Coull, Michael H. Lev, Lee H. Schwamm, and Betensky, RA. "Variable importance in matched case control studies in settings of high dimensional data." Journal of the Royal Statistical Society: Series C (Applied Statistics) 63, no. 4 (2014): b. Qian J, Payabvash S, Kemmling A, Lev MH, Schwamm LH, Betensky RA. Variable selection and prediction using a nested, matched case-control study: Application to hospital acquired pneumonia in stroke patients. Biometrics Mar;70(1): PMCID: PMC c. 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 Jan 31. doi: /ijb PubMed PMID: d. Houseman EA, Coull BA, Betensky RA. Feature-specific penalized latent class analysis for genomic data. Biometrics Dec;62(4): PubMed PMID: Statistical methods and analyses of multiple sclerosis and Alzheimer s disease studies: Dr. Betensky has developed novel methods for improved analysis of multiple sclerosis and Alzheimer s disease studies, including Markov transition modeling of relapsing-remitting MS disability status and latent class modeling of amyloid measurements from different PET platforms. a. Mandel M, Mercier F, Eckert B, Chin P, Betensky RA. Estimating time to disease progression comparing transition models and survival methods--an analysis of multiple sclerosis data. Biometrics Mar;69(1): PMCID: PMC b. Mormino EC, Betensky RA, Hedden T, Schultz AP, Ward A, Huijbers W, Rentz DM, Johnson KA, Sperling RA; For the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle Flagship Study of Aging, and the Harvard Aging Brain Study. Amyloid and APOE4 interact to influence short-term decline in preclinical Alzheimer disease. Neurology. 2014: 71: PMCID:PMC c. Johnson KA, Schultz A, Betensky RA, Becker JA, Sepulcre J, Rentz D, Mormino E, Chhatwal J, Amariglio R, Papp K, Marshall G, Albers M, Mauro S, Pepin L, Alverio J, Judge K, Philiossaint M, Shoup T, Yokell D, Dickerson B, Gomez-Isla T, Hyman B, Vasdev N, Sperling R. Tau positron emission tomographic imaging in aging and early Alzheimer disease. Ann Neurol :110-9 PMC d. Serrano-Pozo A, Qian J, Monsell SE, Betensky RA, Hyman BT. APOEε2 is associated with milder clinical and pathological Alzheimer's disease. Ann Neurol (6): PMCID: D. Research Support Ongoing

4 No Award Number (Betensky) 07/01/09-6/30/17 Harvard NeuroDiscovery Center Translational Neurology Core The goal of this project is to promote research in neurodegenerative diseases with the mission of fostering novel collaborations between scientists at the Harvard Medical School-affiliated labs. ROLE: Director R01NS (Betensky) 07/01/16-06/30/20 Statistical methods for censored and dependently truncated data The goals of this project are to develop and evaluate robust and powerful statistical tests and methods for dependently truncated censored survival data, such as often arise in neurological disease studies. ROLE: PI T36GM (Betensky) 09/01/13-04/30/18 Pipelines into Biostatistics: Training in Quantitative Public Health The goal of the T36 is to provide training in quantitative Public Health to undergraduates from underrepresented backgrounds. ROLE: Co-Investigator UL1TR (Nadler) 05/19/08-04/30/18 /NCRR Harvard Clinical and Translational Science Center (Biostatistics Node/HSPH) The major goal of this project is to provide statistical support to Harvard clinical and translational researchers. ROLE: Leader of Biostatistics Program P50AG (Hyman) 05/15/04-03/31/19 /NIA Massachusetts Alzheimer's Disease Research Center ADRC's Database Management & Statistics Core (aka Core C). The major goal of this project is to provide statistical support for clinical studies. ROLE: Director P01AG (Sperling) 07/15/10-03/31/20 /NIA Impact of Amyloid on the Aging Brain The overall goals of the Program Project application are to elucidate the biological and clinical significance of amyloid deposition in clinically normal older individuals and to determine age-related functional and cognitive change in the absence of amyloid. ROLE: Statistician R01AG (Greenberg) 09/30/10 02/29/20 /NIA Vascular Dysfunction in Cerebral Amyloid Angiopathy The major goal of this project is to analyze the effect of cerebral amyloid angiopathy on microvascular function, white matter diseaese, and cognitive impairment. ROLE: Statistician R01CA (Batchelor) 09/30/07-03/31/18 /NCI Angiogenesis-targeting therapy for glioblastoma The major goal of this project is to apply imaging and biomarker methods to patients with newly diagnosed glioblastoma. ROLE: Statistician 5P01AG (Blacker) 07/01/15-03/31/20

5 Impact of Amyloid and Tau on the Aging Brain: The Harvard Aging Brain Study Core D The overall goals of the Program Project application are to elucidate the biological and clinical significance of amyloid deposition in clinically normal older individuals and to determine age-related functional and cognitive change in the absence of amyloid. ROLE: Statistician R01HL (Balasubramanian) 03/15/15-02/28/19 Statistical methods for large-scale, prospective, epidemiologic studies The goal of this project is to develop new methods for high dimensional matched survival outcomes by extending and combining existing methods. ROLE: Consortium PI R21AG (Qian) 08/01/16-05/31/18 Treatment of Randomly Censored Covariates in Alzheimer s Disease Studies The goal of this project is to develop new statistical methods for treatment of randomly censored covariates in Alzheimer s Disease studies. These studies will enhance the understanding of the relationship between parental age of onset dementia and amyloid-beta levels in older, cognitively normal offspring, and strengthen the findings of how brain pathology changes during the course of the disease. ROLE: Consortium PI 5U01AG (Koenig) 07/01/16-06/30/17 Lipophilic vs. Hydrophilic Statin Exposure and Post-Mortem Neuropathology The goal of this project is to leverage the strengths of the NACC dataset to examine the neuropathological effects of lipophilic vs. hydrophilic statins in individuals across the spectrum of cerebrovascular and neurodegenerative disease. ROLE: Statistician Completed R01DK (Waikar) 09/01/12-06/30/16 Biomarkers of kidney pathology The aims of the study are to identify novel biomarkers that identify histopathologic lesions and predict prognosis in patients undergoing kidney biopsy for acute and chronic kidney diseases. ROLE: Consortium PI R03CA (Betensky) 04/11/12-03/31/15 Signal processing for accurate detection of copy number variants in cancer The aim of this study is to translate methods from traditional signal processing into the problem in genomics of copy number variant detection. ROLE: PI

DEGREE (if applicable)

DEGREE (if applicable) NAME: Joseph Jasper Locascio OMB No. 0925-0001 and 0925-0002 (Rev. 11/16 Approved Through 10/31/2018) BIOGRAPHICAL SKETCH Provide the following information for the Senior/key personnel and other significant