News
Faculty Awarded Grants
Professor J. Jack Lee will serve as the Core Director for The University of Texas MD Anderson Cancer Center SPORE in Melanoma, Core 3 Biostatistics and Bioinformatics. The goal is to provide comprehensive service to guide experiment design to optimize quantitative data analysis, while maintaining statistical justification and results interpretation through sound experimental design principles tailored to each project. This will include data analyses and contributions to the interpretation of results via written reports and interactions with investigators.
Professor Jeffrey Morris is the Core Director for MD Anderson Cancer Center SPORE in Gastrointestinal Cancer, Core 2 Biostatistics and Bioinformatics. This effort will provide modeling, simulations and data analysis to enable the specific aims of related Cores by developing and adapting innovative statistical and bioinformatics methods pertinent to translational cancer studies. This will include generating related reports and facilitating project investigators in publishing results.
Assistant Professor Nabihah Tayob received an R01 grant to support her research, “Biomarker Screening Algorithms for the Improved Early Detection of Hepatocellular Carcinoma.”
Professor Xuelin Huang received grant funding as Co-director of the Biostatistics/Bioinformatics Core for The University of Texas MD Anderson Cancer Center SPORE 2P50CA100632-16 (NIH/NCI), in coordination with PI Hagop Kantarjian, for the proposed research goal of discovering/enhancing new therapies through a better understanding of the causal pathophysiologies in leukemia and the identification of actionable targets.
Professor Liang Li was awarded two R01 grants from NCI to support the following research: “Estimating the Cost Trajectories and Projecting the Cost of Cancer Care in the United States: Methodology and Application" and “Dynamic Prediction of Renal Failure Using Longitudinal Prognostic Information Among Patients with Chronic Kidney Disease and Kidney Transplant.”
Assistant Professor Christine Peterson has received grant funding from the National Science Foundation for her proposed research, “Collaborative research: Bayesian network estimation across multiple sample groups and data types.”
Assistant Professor Min Jin Ha has been awarded an NIH R21 grant for her proposed research, “Proteomic-based integrated subject-specific networks in cancer.”
Assistant Professor Suyu Liu has received a grant award from the American Cancer Society for her proposed research, “Bayesian adaptive designs for early phase clinical trials of immunotherapy.”
MD ANDERSON BIOSTATISTICS AT JSM 2019
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at JSM 2019 in Denver, Colorado, USA, July 27-August 1, 2019.
JSM Contributed Papers
Ken Hess, et al: Evaluating the Psychometric Properties of the Immunotherapy Module of the MD Anderson Symptom Inventory (MDASIImmunotherapy). Suyu Liu (presenter), Heather Lin, Xuemei Wang, et al: The Use of BOIN Design in Practice: What We Have Learned. Jing Ning, Xuelin Huang, et al: A Flexible and Robust Method for Assessing Conditional Association and Conditional Concordance. Jing Ning, et al: Semiparametric Isotonic Regression Analysis for Risk Assessment Under Two-Phase Sampling Designs. Jing Ning, Yu Shen, et al: Semiparametric Model for Bivariate Survival Data Subject to Biased Sampling. Jian Wang (presenter), Jing Ning, and Sanjay Shete: Mediation Analysis with a Censored Mediator in a Casencontrol Study. Peng Wei: Estimation of Mediation Effect for High-Dimensional Omics Mediators with Application to the Framingham Heart Study. Peng Wei, et al: Statistical Methods for Leveraging Public Controls in a Two-Stage Epigenome-Wide Association Study. Sanjay Shete, et al: Detecting Hierarchical Geographical Clusters of Disease Using Heterogeneity Patterns of Varying Incidence Intensity. Sanjay Shete, et al: Detecting Hierarchical Geographical Clusters of Disease Using Heterogeneity Patterns of Varying Incidence Intensity. Sanjay Shete, et al: Estimating Bidirectional Mediation Effects with Application to the Relationship Between Obesity and Diabetes.
JSM Posters
Research Stat Analyst Shiva Dibaj, et al: Exact Inference for Analyzing Contingency Tables in Finite Populations. Senior Stat Analyst Bryan Fellman (presenter), Suyu Liu, et al: Use Restricted Mean Survival Time for the Design Phase of Studies in Power Calculations for Time-to-Event Endpoints.
MD ANDERSON BIOSTATISTICS AT ENAR 2019 SPRING MEETING
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at ENAR 2019 in Philadelphia, Pennsylvania, USA, March 24-27, 2019.
ENAR Invited Sessions
Liang Li (speaker): Dynamic Prediction of Competing Risk Events using Landmark Sub-Distribution Hazard Model with Multivariate Longitudinal Biomarkers. Jeffrey S. Morris (speaker), Hojin Yang, Michelle Miranda, etc.: Bayesian Regression Models for Big Spatially or Longitudinally Correlated Functional Data. Peter F. Thall, etc.: Bayesian Variable Selection for a Semi-Competing Risks Model with Three Hazard Functions. Ying Yuan (speaker): A Bayesian Adaptive Design for Biosimilar Clinical Trials Using Calibrated Power Prior.
ENAR Contributed Sessions
Jing Ning, Yu Shen, etc.: Regression Analysis of Combined Incident and Prevalent Cohort. Hai Shu (presenter), Peng Wei, etc.: High-Dimensional Decomposition-Based Canonical Correlation Analysis. Jack Lee, etc.: BayesESS: An R package and a Web-based Application for Quantifying the Impact of Parametric Priors in Bayesian Analysis. Jeffrey S. Morris, etc.: Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data. Ying Yuan, etc.: A Continuous Reassessment Method for Pediatric Phase I Clinical Trials. Jing Ning, etc.: Quantifying the Evidence of Selective Publishing in Network Meta-Analysis: An EM Algorithm-Based Approach. Suyu Liu, Peter Thall and Ying Yuan, etc.: Group Sequential Enrichment Designs Based on Adaptive Regression of Response and Survival Time on High Dimensional Covariates. Hojin Yang (speaker), Jeffrey S. Morris, etc.: Regression Analyses of Distributions using Quantile Functional Regression. Liangliang Zhang (speaker): Bayesian Variable Selection in Regression with Compositional Covariates
ENAR Posters
Yushu Shi (presenter), Liangliang Zhang, Kim-Anh Do, Robert Jenq and Christine Peterson: A Bayesian Approach for Flexible Clustering of Microbiome Data. Research Statistical Analyst Dawen Sui (presenter) and Mary Elizabeth Edgerton: Body Mass Index and Breast Cancer Survival: A Censored Quantile Regression Analysis. Fang Xia (presenter), Jing Ning, Liang Li, Xuelin Huang, etc.: A Signature Enrichment Design with Bayesian Adaptive Randomization for Cancer Clinical Trials. Yanhong Zhou (presenter), J. Jack Lee and Ying Yuan: Utility-based Seamless Phase I/II Trial Design to Identify the Optimal Biological Dose for Targeted and Immune Therapies.
OTHER NEWS AND HONORS
Huang appointed to Endowed Position
Xueline Huang, Ph.D., was appointed to the endowed position of the Dr. Mien-Chie Hung and Mrs. Kinglan Hung Professorship, effective October 1, 2019. This professorship was established in 2019, and Dr. Huang was nominated for "Developing innovative statistical methods of survival analysis and clinical trial design, for making important statistical contributions to fruitful collaborative cancer research, and for using statistical approaches to deliver better therapy to patients, and to influence national public health policy."
Shete Named Betty B. Marcus Chair in Cancer Prevention
Sanjay Shete, Ph.D., was appointment to the Betty B. Marcus Chair in Cancer Prevention, effective August 1, 2019. The Betty B. Marcus Chair in Cancer Prevention was established in 1994 by Mrs. Marcus, who was a philanthropist, arts patron, and former journalist. She also was the widow of the late Edward S. Marcus, board chairman of Neiman Marcus and nephew of Neiman Marcus store co-founder Carrie Marcus Neiman.
Morris Receives MD Anderson 2018-19 Distinguished Faculty Mentor Award
Jeffrey Morris, Ph.D., was selected for the 2018 MD Anderson Distinguished Faculty Mentor Award, which he received April 11. Recipients of this prestigious award, created in 2010, are nominated by no less than three separate faculty members whom they mentor within the institution.
Urbauer Joins MD Anderson Wall of Science Honorees
Diana Urbauer, Principal Statistical Analyst, and her former teammate Mark Munsell had their pictures hung on the MD Anderson Wall of Science, along with Dr. Michael Frumovitz’s team, for their role in the development and design of a pivotal Phase III trial to determine the non-inferiority of Stryker’s PINPOINT Endoscopic Fluorescence Imaging System, as compared to the current imaging system for detecting sentinel lymph nodes in women with cervical or endometrial cancer. The new technology was found to be far superior, and as a result of their collective efforts, the device received FDA approval for use in detecting sentinel lymph nodes in the patient population. The Wall of Science recognizes excellent work done by MD Anderson faculty and teams, displaying high-impact journal articles that are selected on a quarterly basis.
Ning Invited to Speak by Royal Statistical Society
Jing Ning, Ph.D. was honored with an invitation to present at the Royal Statistical Society in September. There, she will present on the topic of the semiparametric model for bivariate survival data subject to biased sampling.
Thall Invited to Speak at the OncoStat Annual Meeting and as Keynote at Annual Meeting of International Society for Clinical Biostatistics
Peter Thall, Ph.D., presented the invited half day short course, “Dysfunctional Conventions in Medical Statistics: Some Practical Alternatives,” at the OncoStat Annual meeting in Hartford, Connecticut, April 26-28, 2019. He also will present the Keynote Address at the annual meeting of the International Society for Clinical Biostatistics in Leuven, Belgium, July 14-18, 2019.
Biostatistics Student Awarded JSM 2019 Risk Analysis Section Student Paper Award, Runner UP
Wen Li, a current Ph.D. student at The University of Texas School of Public Health (supervised by Jing Ning, Ph.D.) is the recipient of the JSM 2019 Risk Analysis Section student paper award, runner up, for a paper titled: Semiparametric for Risk Assessment Under Two-phase Sampling.
Biostatistics Student Awarded JSM 2019 Section on Bayesian Statistical Science Student Award
Rice University student Yusha Liu (supervised by Jeffrey Morris, Ph.D.) won the Joint Statistical Meetings (JSM) 2019 Section on Bayesian Statistical Science (SBSS) student award for her paper on Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data.
Lee a Keynote Speaker at BAYES 2018 Cambridge: Bayesian Biostatistics Workshop
Professor J. Jack Lee, Kenedy Foundation Chair in Cancer Research, was a keynote speaker at the Bayesian Biostatistics Workshop, held June 20-22 in Cambridge, UK. The workshop was a satellite event of the 2018 International Society for Bayesian Analysis (ISBA) World Meeting.
Ning Awarded Sabin Fellowship
Associate Professor Jing Ning was named a recipient of MD Anderson's Andrew Sabin Fellowship for the category of population and quantitative sciences.
Morris Featured in MD Anderson's Cancer Frontline: Using integromics to better understand and treat colorectal cancer
Professor Jeffrey S. Morris describes some of the collaborative work he is undertaking with members of the Colorectal Cancer Subtyping Consortium and MD Anderson's Colorectal Cancer Moon Shot.
MD Anderson Biostatistics at the ENAR 2019 Spring Meeting
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at ENAR 2019 in Philadelphia, Pennsylvania, USA, March 24-27, 2019.
ENAR Invited Sessions
Liang Li (speaker): Dynamic Prediction of Competing Risk Events using Landmark Sub-Distribution Hazard Model with Multivariate Longitudinal Biomarkers. Jeffrey S. Morris (speaker), Hojin Yang, Michelle Miranda, etc.: Bayesian Regression Models for Big Spatially or Longitudinally Correlated Functional Data. Peter F. Thall, etc.: Bayesian Variable Selection for a Semi-Competing Risks Model with Three Hazard Functions. Ying Yuan (speaker): A Bayesian Adaptive Design for Biosimilar Clinical Trials Using Calibrated Power Prior.
ENAR Contributed Sessions
Jing Ning, Yu Shen, etc.: Regression Analysis of Combined Incident and Prevalent Cohort. Hai Shu (presenter), Peng Wei, etc.: High-Dimensional Decomposition-Based Canonical Correlation Analysis. Jack Lee, etc.: BayesESS: An R package and a Web-based Application for Quantifying the Impact of Parametric Priors in Bayesian Analysis. Jeffrey S. Morris, etc.: Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data. Ying Yuan, etc.: A Continuous Reassessment Method for Pediatric Phase I Clinical Trials. Jing Ning, etc.: Quantifying the Evidence of Selective Publishing in Network Meta-Analysis: An EM Algorithm-Based Approach. Suyu Liu, Peter Thall and Ying Yuan, etc.: Group Sequential Enrichment Designs Based on Adaptive Regression of Response and Survival Time on High Dimensional Covariates. Hojin Yang (speaker), Jeffrey S. Morris, etc.: Regression Analyses of Distributions using Quantile Functional Regression. Liangliang Zhang (speaker): Bayesian Variable Selection in Regression with Compositional Covariates
ENAR Posters
Yushu Shi (presenter), Liangliang Zhang, Kim-Anh Do, Robert Jenq and Christine Peterson: A Bayesian Approach for Flexible Clustering of Microbiome Data. Research Statistical Analyst Dawen Sui (presenter) and Mary Elizabeth Edgerton: Body Mass Index and Breast Cancer Survival: A Censored Quantile Regression Analysis. Fang Xia (presenter), Jing Ning, Liang Li, Xuelin Huang, etc.: A Signature Enrichment Design with Bayesian Adaptive Randomization for Cancer Clinical Trials. Yanhong Zhou (presenter), J. Jack Lee and Ying Yuan: Utility-based Seamless Phase I/II Trial Design to Identify the Optimal Biological Dose for Targeted and Immune Therapies.
Professor Jeffrey Morris is the Core Director for MD Anderson Cancer Center SPORE in Gastrointestinal Cancer, Core 2 Biostatistics and Bioinformatics. This effort will provide modeling, simulations and data analysis to enable the specific aims of related Cores by developing and adapting innovative statistical and bioinformatics methods pertinent to translational cancer studies. This will include generating related reports and facilitating project investigators in publishing results. [ST1]
[ST1]New…edit and then upload and add to newsletter. Morris likely to change.
Two biostatistics faculty are Fellows of the Society for Clinical Trials
Professors Peter F. Thall (2014) and J. Jack Lee (2017) are Fellows of the Society for Clinical Trials. This fellowship honors society members who have made significant contributions to the advancement of clinical trials and to the society.
10 biostatistics faculty are ASA fellows
Ten of the department's faculty members have attained the prestigious honor of being named a Fellow in the American Statistical Association: Donald A. Berry (1986), Kim-Anh Do (2006), Yu Shen (2007), J. Jack Lee (2008), Jeffrey S. Morris (2011), Sanjay Shete (2012), Peter F. Thall (2015), Kenneth R. Hess (2017), Xuelin Huang (2017), and Ying Yuan (2017).
Open Positions
Faculty Position
Assistant, Associate, or Full Professor
Join the team that is once again number one in cancer care at The University of Texas MD Anderson Cancer Center, Department of Biostatistics. Ranked by U.S. News and World Report’s annual “Best Hospitals” survey, the institution has held the top two positions since the start of the list. From Nobel-level collaborations to programs that dramatically accelerate the conversion of scientific discovery into clinical realities, your work will help make cancer history.
Exceptional candidates are sought for multiple tenured/tenure-track faculty positions at the Assistant, Associate, or full Professor level. Applicants should demonstrate prowess in interdisciplinary, collaborative scientific research. The department will consider those developing methodologies with application to biomedical research in various areas, with particular interest in early detection and cancer screening, clinical trial design, imaging, and computer-intensive methodology—including machine learning, and integrative analyses of multiplatform high-dimensional data, such as genomic, proteomic, and microbiome analysis. A Ph.D. in statistics, biostatistics, or a related field is required.
The department has 19 faculty members, 37 masters and doctoral-level research analysts, and 10 postdoctoral fellows. Faculty members are actively involved in collaborative and methodological research in diverse areas such as clinical trial design, cancer screening and early detection, bioinformatics, genomic pathway analysis, network analysis, and integrative modeling of multiple types of complex data. This includes high-dimensional omic data, functional data analysis, Bayesian methodology, longitudinal and survival analysis, statistical genetics, population health research, and behavioral/social statistics.
Our faculty collaborate with world-class cancer scientists, such as Dr. James Allison—the 2018 Nobel Prize winner for medicine—in all cancer areas and research levels. Opportunities to support large-scale studies and programs include the Moon Shots Program, which brings together the top aspects of academia and industry to swiftly translate data into patient benefits. Their large, important cancer data sets require quantitative input with impact potential. Faculty also partner with our affiliated biostatistics doctoral programs at the University of Texas, Texas A&M University, and Rice University. Our department offers strong resources, including an in-house quantitative research computing team specializing in database design, web-based clinical trial support, scientific programming, and software engineering. For specifics, visit: https://biostatisics.mdanderson.org. Direct further questions to the selection committee chair.
The institution offers competitive salaries and an outstanding personal and professional benefits package. Houston is one of the world’s most innovative and diverse cities, with great neighborhoods; competitive private and public schools; a dynamic music, theater and sports scene; highly acclaimed museums; international cuisine; and year-round outdoor recreational activities.
MD Anderson is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, gender, sexual orientation, age, religion, disability or veteran status, except where such distinction is required by law. All positions are security sensitive and subject to examination of criminal history record information. MD Anderson is a smoke-free and drug-free environment.
Consideration of applications will continue until the positions are filled. Applicants should send a cover letter outlining the relevance of their research experience and interests to the position, a curriculum vitae, a brief statement of current and proposed research, and three letters of recommendation to:
Faculty Search Committee
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
P.O. Box 301402
Houston, TX 77230-1402
Email: biostat-search@mdanderson.org
Join the team that is once again number one in cancer care at The University of Texas MD Anderson Cancer Center, Department of Biostatistics. Ranked by U.S. News and World Report’s annual “Best Hospitals” survey, the institution has held the top two positions since the start of the list. From Nobel-level collaborations to programs that dramatically accelerate the conversion of scientific discovery into clinical realities, your work will help make cancer history.
Exceptional candidates are sought for multiple tenured/tenure-track faculty positions at the Assistant, Associate, or full Professor level. Applicants should demonstrate prowess in interdisciplinary, collaborative scientific research. The department will consider those developing methodologies with application to biomedical research in various areas, with particular interest in early detection and cancer screening, clinical trial design, imaging, and computer-intensive methodology—including machine learning, and integrative analyses of multiplatform high-dimensional data, such as genomic, proteomic, and microbiome analysis. A Ph.D. in statistics, biostatistics, or a related field is required.
The department has 19 faculty members, 37 masters and doctoral-level research analysts, and 10 postdoctoral fellows. Faculty members are actively involved in collaborative and methodological research in diverse areas such as clinical trial design, cancer screening and early detection, bioinformatics, genomic pathway analysis, network analysis, and integrative modeling of multiple types of complex data. This includes high-dimensional omic data, functional data analysis, Bayesian methodology, longitudinal and survival analysis, statistical genetics, population health research, and behavioral/social statistics.
Our faculty collaborate with world-class cancer scientists, such as Dr. James Allison—the 2018 Nobel Prize winner for medicine—in all cancer areas and research levels. Opportunities to support large-scale studies and programs include the Moon Shots Program, which brings together the top aspects of academia and industry to swiftly translate data into patient benefits. Their large, important cancer data sets require quantitative input with impact potential. Faculty also partner with our affiliated biostatistics doctoral programs at the University of Texas, Texas A&M University, and Rice University. Our department offers strong resources, including an in-house quantitative research computing team specializing in database design, web-based clinical trial support, scientific programming, and software engineering. For specifics, visit: https://biostatistics.mdanderson.org. Direct further questions to the selection committee chair.
The institution offers competitive salaries and an outstanding personal and professional benefits package. Houston is one of the world’s most innovative and diverse cities, with great neighborhoods; competitive private and public schools; a dynamic music, theater and sports scene; highly acclaimed museums; international cuisine; and year-round outdoor recreational activities.
MD Anderson is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, gender, sexual orientation, age, religion, disability or veteran status, except where such distinction is required by law. All positions are security sensitive and subject to examination of criminal history record information. MD Anderson is a smoke-free and drug-free environment.
Consideration of applications will continue until the positions are filled. Applicants should send a cover letter outlining the relevance of their research experience and interests to the position, a curriculum vitae, a brief statement of current and proposed research, and three letters of recommendation to:
Faculty Search Committee
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
P.O. Box 301402
Houston, TX 77230-1402
Email: biostat-search@mdanderson.orgStatistical Analyst Position
Successful candidates will join a team of biostatisticians working on a wide variety of collaborative projects in cancer research. The University of Texas MD Anderson Cancer Center supports and promotes professional growth and mentoring, as well as continuing education, creativity, and discovery.
Responsibilities
Collaborate with clinicians and scientists to plan meaningful studies, statistically analyze and communicate/document the results:
- Assess relevant literature and existing data
- Perform simulations and complex statistical analyses using advanced statistical methods and programming
- Prepare statistical considerations for clinical trial designs or grant applications
- Perform biostatistical reviews of research protocols
- Collaborate on development of new statistical methodology
- Prepare written reports, including reports of data for committee and scientific meetings
- Collaborate with investigators on manuscripts
- Make original contributions to research projects
- Take initiative in professional activities
- If hired as or promoted to a senior position, participate in training and supervising junior statistical analysts
To be considered, send a letter of interest, curriculum vitae and three (3) letters of reference (include contact information for references) to dqs-stat-job@mdanderson.org
Minimum Qualifications:
- Master's degree in biostatistics, bioinformatics, statistics, computing, or related field
- Working knowledge of Windows and/or UNIX operating systems
- Experience in statistical programming and analysis
- Excellent oral and written communication skills in English
- Experience with mainframe and/or PC databases, document processing and statistical software such as SAS and S-Plus
Desired Qualifications:
- Experience writing reports and analytical sections of grant applications
- Extensive experience in statistical consulting, data analysis, design and management of clinical trials in the biomedical or cancer research setting
Salary: Competitive; commensurate with experience
EEO & Employment Eligibility
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, sexual orientation, gender identity/expression, disability, veteran status, genetic information or any other basis protected by MD Anderson policy or by federal, state or local laws, unless such distinction is required by law. All positions at MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center provides a smoke-free and drug-free environment.
Postdoctoral Fellow Position
None at this time.