Robert Gray

Professor
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Research


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.

 

Biography

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

Paemka L, McCullagh BN, Abou Alaiwa MH, Stoltz DA, Dong Q, Randak CO, Gray RD, McCray PB Jr. Monocyte derived macrophages from CF pigs exhibit increased inflammatory responses at birth. J Cyst Fibros. 2017 Apr 1. pii:
S1569-1993(17)30090-5.

 

Gray RD, Downey D, Taggart CC. Biomarkers to monitor exacerbations in cystic
fibrosis. Expert Rev Respir Med. 2017 Apr;11(4):255-257.

 

Del Villar-Guerra R, Gray RD, Chaires JB. Characterization of Quadruplex DNA
Structure by Circular Dichroism. Curr Protoc Nucleic Acid Chem. 2017 Mar
2;68:17.8.1-17.8.16.

 

Gray RD, Parker KH, Quail MA, Taylor AM, Biglino G. A method to implement the
reservoir-wave hypothesis using phase-contrast magnetic resonance imaging.
MethodsX. 2016 Aug 25;3:508-512.

 

Jeffery U, Gray RD, LeVine DN. A Simple Fluorescence Assay for Quantification
of Canine Neutrophil Extracellular Trap Release. J Vis Exp. 2016 Nov 21;(117).

 

Solin LJ, Gray R, Hughes LL, Wood WC, Lowen MA, Badve SS, Baehner FL, Ingle
JN, Perez EA, Recht A, Sparano JA, Davidson NE. Reply to C. Shah et al. J Clin
Oncol. 2016 May 20;34(15):1824-5.

 

Li S, Gray RJ. Estimating treatment effect in a proportional hazards model in
randomized clinical trials with all-or-nothing compliance. Biometrics. 2016
Sep;72(3):742-50.

 

Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, Geyer CE
Jr, Dees EC, Perez EA, Olson JA Jr, Zujewski J, Lively T, Badve SS, Saphner TJ,
Wagner LI, Whelan TJ, Ellis MJ, Paik S, Wood WC, Ravdin P, Keane MM, Gomez Moreno HL, Reddy PS, Goggins TF, Mayer IA, Brufsky AM, Toppmeyer DL, Kaklamani VG, Atkins JN, Berenberg JL, Sledge GW. Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. N Engl J Med. 2015 Nov 19;373(21):2005-14.

 

Solin LJ, Gray R, Hughes LL, Wood WC, Lowen MA, Badve SS, Baehner FL, Ingle
JN, Perez EA, Recht A, Sparano JA, Davidson NE. Surgical Excision Without
Radiation for Ductal Carcinoma in Situ of the Breast: 12-Year Results From the
ECOG-ACRIN E5194 Study. J Clin Oncol. 2015 Nov 20;33(33):3938-44.

 

Adams S, Gray RJ, Demaria S, Goldstein L, Perez EA, Shulman LN, Martino S,
Wang M, Jones VE, Saphner TJ, Wolff AC, Wood WC, Davidson NE, Sledge GW, Sparano JA, Badve SS. Prognostic value of tumor-infiltrating lymphocytes in
triple-negative breast cancers from two phase III randomized adjuvant breast
cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol. 2014 Sep 20;32(27):2959-66.

 

Related Links

Eastern Cooperative Oncology Group