Invited Session 6: Overall Survival in Oncology Clinical Trials
Chair: Ying Lu, Stanford University
Ying Lu, Ph.D., is Professor in the Department of Biomedical Data Science, and by courtesy in the Department of Radiology and Departement of Health Research and Policy, Stanford University. He is the Co-Director of the Stanford Center for Innovative Study Design and the Biostatistics Core of the Stanford Cancer Institute. Before his current position, he was the director of VA Cooperative Studies Program Palo Alto Coordinating Center (2009-2016) and a Professor of Biostatistics and Radiology at the University of California, San Francisco (1994-2009). His research areas are biostatistics methodology and applications in clinical trials, statistical evaluation of medical diagnostic tests, and medical decision making. He serves as the biostatistical associate Editor for JCO Precision Oncology and co-editor of the Cancer Research Section of the New England Journal of Statistics and Data Science. Dr. Lu is an elected fellow of the American Association for the Advancement of Science and the American Statistical Association. Dr. Lu initiated the Stat4Onc Annual Symposium with Dr. Ji and Dr. Kummar in 2017 and is the PI of the R13 NCI grant for this conference.
Panelist: LJ Wei, PhD, Harvard T.H. Chan School of Public Health
L.J. Wei's research is in the area of developing statistical methods for the design and analysis of clinical trials. In 1977-78 he introduced the "urn design" for two-arm sequential clinical studies. This design has been utilized in several large-scaled multi-center trials, for example, the Diabetes Control and Complications Trial sponsored by the NIH and the Matching patients to Alcoholism Treatments sponsored by NIAAA. In 1979, he proposed a response adaptive design, a randomized version of Marvin Zelen's play the winner rule, was used in the ECMO trial, a well-known study which evaluated extracorporeal membrane oxygenation for treating newborns with persistent pulmonary hypertension. Currently several trials sponsored by private industry are using this particular design to relax the ethical problem arising in using the conventional 50-50 randomization treatment allocation rule clinical studies. To monitor trials sequentially for economic and ethical reasons, in 1982 Wei and his colleagues presented a rather flexible monitoring scheme, which has become a classical reference for the literature in interim analysis for clinical trials. Dr. Wei has developed numerous methods for analyzing data with multiple outcome or repeated measurements obtained from study subjects. In particular, his "multivariate Cox procedures" to handle multiple event times have become quite popular. He and his colleagues are also responsible for developing alternative models to the Cox proportional hazards model for analyzing survival observations. A very important issue in statistical inference is to check whether the model used to fit the data is appropriate or not. Currently, Wei and his colleagues are developing graphical and numerical methods for checking the adequacy of the Cox proportional hazards model, other semi-parametric survival models, parametric models, and random effects models for repeated measurements. The new procedures are much less subjective than the conventional eye-ball methods based on ordinary residuals plots. Since the cost of computing has been drastically reduced, some analytically intractable statistical problems can be handled numerically. Presently, Wei and his colleagues are working on various resampling methods for quantile regression, rank regression, and regression models for censored data. Dr. Wei is also a senior statistician at the Statistical and Data Analysis Center. He works closely with the medical investigators in Pediatrics AIDS clinical trials for evaluating new treatments for HIV patients.
Panelist: Susan Halabi, PhD, Duke University Medical Center
Susan Halabi, PhD is the James B. Duke Distinguished Professor of Biostatistics and Bioinformatics, and co-chief, Division of Biostatistics, Department of Biostatistics and Bioinformatics at Duke University Medical Center. For over twenty five years, she has been at the forefront of designing and analyzing clinical trials in oncology. She develops novel methods for the design and analysis of clinical studies and innovative variable selection methods for biomarkers and high dimensional data. Dr. Halabi is committed to ensuring statistical rigor in all her clinical studies so that they are impactful to patients and society. Her most significant contributions concern building and validating prognostic models of outcomes for prostate cancer and identifying surrogate endpoints for overall survival. Dr. Halabi has over 275 peer-reviewed publications and has co-edited two books that have become key works in the field: Oncology Clinical Trials (2nd Edition, Demos 2018) and Textbook of Clinical Trials in Oncology (CRC Press 2019). A past-president of the Society for Clinical Trials and the 2022 recipient of the Janet L. Norward Award, Dr. Halabi is a fellow of the Society for Clinical Trials, the American Statistical Association and the American Society for Clinical Oncology.
Panelist: Wenjuan Gu, PhD, FDA
Dr. Gu is a senior mathematical statistician in the Division of Biometric IX in the Office of Biostatistics in the Center for Drug Evaluation and Research (CDER), which supports the pre-market reviews and approvals in the Division of Hematologic Malignancies II, Office of Oncologic Diseases. She is a statistics representative for the Oncology Center of Excellence (OCE) Pediatric Review Committee subcommittee.
Panelist: Dacheng Liu, PhD, Boehringer-Ingelheim
Dacheng Liu serves as the Highly Distinguished Therapeutic Area and Methodology Statistician at Boehringer Ingelheim with 18 years of experience in the pharmaceutical industry. In this role, he provides leadership in driving the statistical quality and fostering innovation of companywide clinical development programs. As the chair of the statistical strategy and review committee, he is instrumental in shaping the organization’s statistical practices. Dacheng represents Boehringer Ingelheim at industry-wide groups, such as PhRMA clinical development working group, and leads collaborations with partners in the US from both industry and academia.
Prior to his current role, Dacheng served as the Global Head of Clinical Data Sciences, and the US Head of Statistics, leading both US and global teams in clinical drug developments of the entire pipeline of Boehringer Ingelheim. He has extensive experience leading early and late-phase projects in multiple disease areas, including landmark studies, regulatory submissions, and FDA advisory committee meetings. He played a key role in harmonizing SOP processes and standardizing statistical methodologies within Boehringer Ingelheim. Dacheng has over 40 publications in areas of clinical research, trial design, statistical methodologies, and machine learning.
Panelist: Wm Kevin Kelly, PhD, Thomas Jefferson University
Dr. Kelly is an internationally respected clinical research in genitourinary oncology that has held leadership positions in National Clinical Trials Network; served as a permanent member of the oncology drug advisory committee for the FDA and currently serves as the medical oncology chair for the NCI Genitourinary Steering. He completed his Medical Oncology fellowship at Memorial Sloan Kettering Cancer Center and was on faculty for over fifteen years where his research focused on novel trial designs for patients with advanced prostate cancer. He subsequently served as the Director of the Clinical Management Research Office in the Yale Comprehensive Cancer Center and was co-Director of the Genitourinary Oncology Program at Yale University. He currently serves as the Chair of the Department of Medical Oncology at Thomas Jefferson University and the Associate Director of Clinical Research at the Sidney Kimmel Cancer Center. His expertise is in drug and biomarker development and trial designin prostate and bladder cancer and has been instrumental in defining the use of many novel therapies and biomarkers in patients with prostate and bladder cancer for all stages of this disease.