Statistical Science

Celebrating 70: An Interview with Don Berry

Dalene Stangl, Lurdes Y. T. Inoue, and Telba Z. Irony

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Donald (Don) Arthur Berry, born May 26, 1940 in Southbridge, Massachusetts, earned his A.B. degree in mathematics from Dartmouth College and his M.A. and Ph.D. in statistics from Yale University. He served first on the faculty at the University of Minnesota and subsequently held endowed chair positions at Duke University and The University of Texas M.D. Anderson Center. At the time of the interview he served as Head of the Division of Quantitative Sciences, and Chairman and Professor of the Department of Biostatistics at UT M.D. Anderson Center.

Don’s research deals with the theory and applications of statistics, especially Bayesian methods for sequential design of experiments. His work challenges the status quo, always striving to improve design and analysis of clinical trials, genetic modeling and the process of health-related decision making. His research impacts health research broadly, but has achieved the greatest influence in cancer research. As of 2010, he has published over 200 articles and 10 books and has mentored 24 Ph.D. and 16 M.S. students.

Don’s honors include fellowship election to the International Statistical Institute, the American Statistical Association and the Institute of Mathematical Statistics. He gave Presidential invited addresses to the Western North American Region of the International Biometric Society (New Mexico, 2004), the Canadian Statistical Society (Ottawa, 2006) and the Eastern North American Region of the International Biometric Society (Washington, 2008).

Don married Donna Berry in 1960. Together they raised six children, Don, Mike, Tim, Scott, Jennifer and Erin. Celebrating Don’s 70th birthday, the authors co-organized two invited sessions and a dinner reception at the ENAR 2010 in New Orleans. This interview occurred while his family, friends, colleagues and students gathered to celebrate his birthday and his contributions to statistics.

Article information

Statist. Sci. Volume 27, Number 1 (2012), 144-159.

First available in Project Euclid: 14 March 2012

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Bayesian inference adaptive design clinical trials mammography


Stangl, Dalene; Inoue, Lurdes Y. T.; Irony, Telba Z. Celebrating 70: An Interview with Don Berry. Statist. Sci. 27 (2012), no. 1, 144--159. doi:10.1214/11-STS366.

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  • Berry, D. A. (1972). A Bernoulli two-armed bandit. Ann. Math. Statist. 43 871–897.
  • Berry, D. A. (1998). Benefits and risks of screening mammography for women in their forties: A statistical appraisal. Journal of the National Cancer Institute 90 1431–1439.
  • Berry, D. A. (2006). Bayesian clinical trials. Nature Reviews Drug Discovery 5 27–36.
  • Berry, D. A. (2008). Commentary: The science of doping. Nature 454 692–693.
  • Berry, D. A. and Berry, T. D. (1985). The probability of a field goal: Rating kickers. Amer. Statist. 39 152–155.
  • Berry, D. A. and Fristedt, B. (1985). Bandit Problems: Sequential Allocation of Experiments. Chapman & Hall, London.
  • Berry, D. A. and Stangl, D. (eds.) (1996). Bayesian Biostatistics. Dekker, New York.
  • Berry, D. A., Cronin, K. A., Plevritis, S. K., Fryback, D. G., Clarke, L., Zelen, M., Mandelblatt, J. S., Yakovlev, A. Y., Habbema, J. D. F. Feuer, E. J. and for the Cancer Intervention and Surveillance Modeling Network (CISNET) (2005). Effect of screening and adjuvant therapy on mortality from breast cancer. New England Journal of Medicine 353 1784-1792.
  • Berry, D. A., Parmigiani, G., Sanchez, J., Schildkraut, J. and Winer, E. (1997). Probability of carrying a mutation of breast-ovarian cancer gene BRCA1 based on family history. J. Natl. Cancer Inst. 89 227–238.
  • Berry, D. A., Müller, P., Grieve, A. P., Smith, M., Parke, T., Blazek, R., Mitchard, N. and Krams, M. (2002a). Adaptive Bayesian designs for dose-ranging drug trials. In Case Studies in Bayesian Statistics, Vol. V (Pittsburgh, PA, 1999) (C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli and M. West, eds.). Lecture Notes in Statist. 162 99–181. Springer, New York.
  • Berry, D. A., Iversen, E. S. Jr., Gudbjartsson, D. F., Hiller, E. H., Garber, J. E., Peshkin, B. N., Lerman, C., Watson, P., Lynch, H. T., Hilsenbeck, S. G., Rubinstein, W. S., Hughes, K. S. and Parmigiani, G. (2002b). BRCAPRO validation, sensitivity of genetic testing of BRCA1/BRCA2, and prevalence of other breast cancer susceptibility genes. J. Clin. Oncol. 20 2701–2712.
  • Berry, D. A., Inoue, L., Shen, Y., Venier, J., Cohen, D., Bondy, M., Theriault, R. and Munsell, M. F. (2006). Modeling the Impact of Treatment and Screening on Breast Cancer Mortality: A Bayesian Approach. Monograph of the Journal of the National Cancer Institute Number 36 30–36.
  • Biswas, S., Liu, D. D., Lee, J. J. and Berry, D. A. (2009). Bayesian clinical trials at the University of Texas M. D. Anderson Cancer Center. Clinical Trials 6 205–216.
  • Couzin, J. (2004). The new math of clinical trials. Science 303 784–786.
  • Gøtzsche, P. C. and Olsen, O. (2000). Is screening for breast cancer with mammography justifiable? Lancet 355 129–134.
  • Kolata, G. (2009a). New guidelines suggest cutback in mammograms. The New York Times 11/17/09. Available at
  • Kolata, G. (2009b). Behind cancer guidelines, quest for data. The New York Times 11/22/09. Available at
  • Kolmogorov, A. N. (1956). Foundations of the Theory of Probability, 2nd ed. Chelsea Publishing Co., New York.
  • Mandelblatt, J. S., Cronin, K. A., Bailey, S., Berry, D. A., de Koning, H. J., Draisma, G., Huang, H., Lee, S. J., Munsell, M., Plevritis, S. K., Ravdin, P., Schechter, C. B., Sigal, B., Stoto, M. A., Stout, N. K., van Ravesteyn, N. T., Venier, J., Zelen, M., Feuer, E. J. and for the Breast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET) (2009). Effects of mammographic screening under different screening schedules: Model estimates of potential benefits and harms. Annals of Internal Medicine 151 738–747.
  • New York Times Editorial (2005). The NewYork Times 11/6/05. Available at
  • Parmigiani, G., Berry, D. A. and Aguilar, O. (1998). Determining carrier probabilities for breast cancer susceptibility genes BRCA1 and BRCA2. The American Journal of Human Genetics 62 145–158.
  • Peck, P. (2005). Results are in: Mammograms save lives. CNN, October 27, 2005. Available at
  • Ravdin, P. M., Cronin, K. A., Howlader, N., Berg, C. D., Chlebowski, R. T., Feuer, E. J., Edwards, B. K. and Berry, D. A. (2007). The decrease in breast-cancer incidence in 2003 in the United States. N. Engl. J. Med. 356 1670–1674.
  • Stangl, D. and Berry, D. A. (2000). Meta-Analysis in Medicine and Health Policy. Dekker, New York.
  • Stein, R. (2009). Breast exam guidelines now call for less testing. The Washington Post 11/17/09. Available at
  • Thompson, W. R. (1933). On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25 275–294.
  • Thorp, E. O. (1966). Beat the Dealer: A Winning Strategy for the Game of Twenty-one: A Scientific Analysis of the World-Wide Game Known Variously as Blackjack, Twenty-one, Vingt-et-un, Pontoon, or Van-John. Random House, New York.