Dongsheng Tu

Title: Professor
E-Mail: dtu@ctg.queensu.ca
Webpage: http://meds.queensu.ca/qcri/mentors/ri_dt.htm

Degrees

B. Sc. (University of Science and Technology of China)

Ph. D. (Medical University of South Carolina)

Research Interests

I am one of the Senior Biostaticians in the National Cancer Institute of Canada Clinical Trials Group cross-appointed to the Department of Mathematics and Statistics. I spend most of my time in the design, management and analysis of the clinical trials sponsored by National Cancer Institute of Canada, US National Cancer Institute, and pharmaceutical companies. My research in statistical methodology is driven by the need to solve some interesting mathematical and statistical problems in the design and analysis of clinical trials. For example, one of the trials I analyzed was selected as a pivotal study for the final US Food and Drug Administration (FDA) approval of marketing Epirubicin in US as an adjuvant treatment for early breast cancer. During the analysis of this trial and the presentation of the results to the FDA, an interesting question on whether statistical tests of treatment effect should be adjusted for baseline patient characteristics has come out. In a recent paper coauthored with two physicians, we first discussed some statistical principles and regulatory aspects around this issue. A student has worked with me to explore this question further to identify what is the best method to perform the covariates adjustments when an adjustment is necessary. The results were presented recently at the annual meeting of the Society for Clinical Trials.

Another example is my research on statistical issues in the design and analysis of equivalence clinical trials. The objective of these trials is to show that a new treatment has the same efficacy as a standard treatment, which is very different from that of conventional trials to show one treatment is different from another. Traditional methods of statistical analysis cannot be applied to the design and analysis of these trials. I have published several papers that derived mathematical formulas for sample size determination and developed some statistical procedures for statistical analysis when the primary endpoint of the trials is binary or ordinal categorical. I recently supervised a student to study statistical procedures for the analysis of equivalence clinical trials with survival endpoint.

Recently, the investigation of prognostic factors for patients with ovarian and breast cancers stimulated my interests in studying some general issues on the applications of Cox proportional hazards regression models in cancer clinical trials. I first supervised a student to study the applications of some resampling methods to variable selection and model validation of the Cox models. Collaborating with a visiting scholar from Beijing University, I proposed a Bartlett type adjustment to Rao.s score test in Cox proportional hazard models. Recently I worked with a student to explore the applications of some nonparametric regression methods as alternatives to the Cox model in the identification of prognostic factors for cancer patients.

Research Interests (Cont.d)

Besides the research in methodology issues in biostatistics, I am also interested in the general mathematical theory of statistics, especially the large sample theory of resampling methods including the jackknife and bootstrap. Some early results of my research in this area have been summarized in the book coauthored with Dr. Jun Shao.

Selected Publications

Rao's Score Tests in Survival Analysis: Examples and Bartlett Type Adjustments, Communications in Statistics Theory and Methods, accepted.

Adjusting Treatment Effects for Covariates in Clinical Trials: Statistical and Regulatory Issues, (with K. Shalay and J. Pater), Drug Information Journal 34 (2000) 511-523.

On the Use of the Ratio or the Odds Ratio of Cure Rates in therapeutic equivalence clinical trials with Binary Clinical Endpoints, Journal of Biopharmaceutical Statistics 8 (1998), 263-282.

Factors Predictive of Survival After First Relapse or Progression in Advanced Epithelial Ovarian Carcinoma: A Decision Tree Analysis Derived Model with Test and Validation Groups (with P. J. Hoskins, K. James, J. Pater and B. Koski ), Gynecologic Oncology 70 (1998) 224-230.

A Comparative Study of Some Statistical Procedures in Establishing Therapeutic Equivalence of Non-Systemic Drugs with binary endpoints, Drug Information Journal 31 (1997) 1291-1300.

Two One-sided Tests Procedures in Establishing Therapeutic Equivalence with Binary Clinical Endpoints: Fixed Sample Performances and Sample Size Determination, Journal of Statistical Computing and Simulations 59 (1997) 271-190.

A Bartlett Type Correction for the Subject-Years Method in Comparing Survival Data to a Standard Population (with A. J. Gross), Statistics and Probability Letters 29 (1996) 149-157.

The Jackknife and Bootstrap (with J. Shao), Springer, New York, xvii+516, 1995.

Accurate Confidence Intervals for the Ratio of Specific Occurrence/Exposure Rates in Risk and Survival Analysis (with A. J. Gross), Biometrical Journal 37 (1995) 611-626.

Recent Graduate Students (in Maths. and Stats.)

I have supervised/co-supervised students in both the Department of Mathematics and Statistics and the Department of Community Health and Epidemiology and at Queen's. Listed below are students from Mathematics and Statistics only.

Y. Luo, Ph.D. in progress.

Y. Liu, Statistical Procedures for Therapeutic Equivalence Clinical Trials with Survival Endpoints, M.Sc. (2001 Spring).

D. Lam, Statistical Analysis of Stratified Clinical Trials with Survival Endpoints, M.Sc. (2001 Spring)

J. Bakal, Identifying Prognostic Factors for Women with Early Breast Cancer: Proportional Hazards Regression Models and Alternatives, M.Sc. (1999 Fall).

Contact Info

Department of Math & Stats
Jeffery Hall, University Ave.
Kingston, ON Canada, K7L 3N6
Phone: (613) 533-2390
Fax: (613) 533-2964
mathstat@mast.queensu.ca

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