Robert Gray

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Dr. Gray has worked primarily on problems relating to the analysis of censored data and clinical trials. Some areas of current research focus are developing smoothing techniques for censored failure time data, methods for design and analysis of studies with competing risks endpoints, and methods for multivariate failure time data.


In examining the effect of potential prognostic factors for cancer patients, and in other regression problems with failure time endpoints, methods for exploring relationships are needed as an aid in model building. Methods of inference which require minimal assumptions for validity are also needed. In complete samples smoothing techniques and nonparametric estimation have been extensively studied for these purposes. Dr. Gray has worked on extending some of these techniques, especially spline and kernel estimation methods, to censored data problems. In applications to breast cancer clinical trials, these methods have made it possible to identify nonproportionality in the effects of ER status and tumor necrosis, explore appropriate modeling for variables such as number of positive nodes, tumor size, age, and percent cells in S phase, and identify an interaction in the effects of number of positive nodes and tumor size, among other effects.


In clinical trials studying therapies for chronic diseases in the elderly, it will often happen that some patients will fail from unrelated causes prior to the failure of the disease under study. For situations like this, Dr. Gray has recently studied methods for modeling the probability of failing from particular causes over time, which follows earlier work on testing for equality of these probability functions among treatment groups. Another area of interest is the appropriate definition of endpoints for such trials.


Dr. Gray's work on methods for multivariate failure time data has focused on clustered data problems, which could arise in multi-center clinical trials if patients from the same center are more likely to have similar outcomes than patients from different centers. He has developed methods for testing for the presence of clustering, and for estimating regression parameters for clustered data. He is also currently working on methods for exploring the degree of within cluster association and estimating association parameters, and on methods for improving the efficiency of generalized estimating equations for marginal regression analysis.



Dr. Gray completed his PhD in statistics at Oregon State University in 1982. After joining DFCI as a postdoctoral fellow, he became a faculty member in 1984. He has worked extensively on methods for the analysis of censored failure-time data and competing-risks problems. He has also been a statistician with the Eastern Cooperative Oncology Group, and in 2001 became the head of the ECOG Statistical Center.


Recent Publications

Solin LJ, Gray R, Baehner FL, Butler SM, Hughes LL, Yoshizawa C, Cherbavaz DB, Shak S, Page DL, Sledge GW Jr, Davidson NE, Ingle JN, Perez EA, Wood WC, Sparano JA, Badve S. A Multigene Expression Assay to Predict Local Recurrence Risk for Ductal Carcinoma In Situ of the Breast. J Natl Cancer Inst. 2013 May 2. [Epub ahead of print]


Freidlin B, Sun Z, Gray R, Korn EL. Phase III Clinical Trials That Integrate
Treatment and Biomarker Evaluation. J Clin Oncol. 2013 Apr 8. [Epub ahead of print]


Schneider BP, Gray RJ, Radovich M, Shen F, Vance G, Li L, Jiang G, Miller KD, Gralow JR, Dickler MN, Cobleigh MA, Perez EA, Shenkier TN, Vang Nielsen K, Müller S, Thor A, Sledge GW Jr, Sparano JA, Davidson NE, Badve SS. Prognostic and predictive value of tumor vascular endothelial growth factor gene amplification in metastatic breast cancer treated with paclitaxel with and without bevacizumab; results from ECOG 2100 trial. Clin Cancer Res. 2013 Mar 1;19(5):1281-9.


Hong F, Kahl BS, Gray R. Incremental value in outcome prediction with gene expression-based signatures in diffuse large B-cell lymphoma. Blood. 2013 Jan 3;121(1):156-8.

Tevaarwerk AJ, Gray RJ, Schneider BP, Smith ML, Wagner LI, Fetting JH, Davidson N, Goldstein LJ, Miller KD, Sparano JA. Survival in patients with metastatic recurrent breast cancer after adjuvant chemotherapy: little evidence of improvement over the past 30 years. Cancer. 2013 Mar 15;119(6):1140-8.


Kim HT, Gray R. Three-component cure rate model for nonproportional hazards alternative in the design of randomized clinical trials. Clin Trials. 2012 Apr;9(2):155-63.


Sparano JA, Goldstein LJ, Childs BH, Shak S, Brassard D, Badve S, Baehner FL, Bugarini R, Rowley S, Perez EA, Shulman LN, Martino S, Davidson NE, Kenny PA, Sledge GW Jr, Gray R. Relationship between quantitative GRB7 RNA expression and recurrence after adjuvant anthracycline chemotherapy in triple-negative breast cancer. Clin Cancer Res. 2011 Nov 15;17(22):7194-203.


Brahmer JR, Dahlberg SE, Gray RJ, Schiller JH, Perry MC, Sandler A, Johnson DH. Sex differences in outcome with bevacizumab therapy: analysis of patients with advanced-stage non-small cell lung cancer treated with or without bevacizumab in combination with paclitaxel and carboplatin in the Eastern Cooperative Oncology Group Trial 4599. J Thorac Oncol. 2011 Jan;6(1):103-8.


Gor PP, Su HI, Gray RJ, Gimotty PA, Horn M, Aplenc R, Vaughan WP, Tallman MS, Rebbeck TR, DeMichele A. Cyclophosphamide-metabolizing enzyme polymorphisms and survival outcomes after adjuvant chemotherapy for node-positive breast cancer: a retrospective cohort study. Breast Cancer Res. 2010;12(3):R26.


Wang R, Lagakos SW, Gray RJ. Testing and interval estimation for two-sample survival comparisons with small sample sizes and unequal censoring. Biostatistics. 2010 Oct;11(4):676-92.


Related Links

Eastern Cooperative Oncology Group