Ph.D. Student Profile

Minh Tung  Phung, MPH

Minh Tung Phung, MPH

  • Doctoral Student

Education

MPH, University of Auckland, New Zealand, 2018

Research Interests & Projects

My research interests include cancer epidemiology, risk prediction, causal inference, and statistical methods. My research interests focus on applying causal inference methods to identify novel factors associated with cancer risk and mortality, and then incorporating them into risk stratification models to identify people with high risk to inform prevention and/or treatment. I am also interested in primary data collection. 

Current research

My doctoral dissertation is related to develop three risk stratification models: one model is to identify women with high risk of ovarian cancer for further primary prevention; one model is to identify ovarian cancer patients with high risk of getting residual disease after primary cytoreduction surgery in order to assist their treatment decision; and one model to identify Southern Vietnamese women with high risk of cervical cancer who should screen more often. I use the big data from the Ovarian Cancer Association Consortium in the two projects related to ovarian cancer. I have been collecting primary data in Vietnam for the cervical cancer project, including a cross-sectional study and six focus groups. My previous research was related to developing and validating a risk prediction model to inform precision treatment for breast cancer patients in New Zealand using data from cancer registries. My other projects are related to identifying novel factors related to ovarian cancer risk and mortality, assessing interactions between risk factors, and analyzing the trends of ovarian cancer by race/ethnicity and histotype in the U.S using SEER data.

Selected Publications

  • Brieger, K.K.*, Phung, M.T.*, Mukherjee, B., Bakulski, K.M., Anton-Culver, H., Bandera, E.V., Bowtell, D., Cramer, D.W., DeFazio, A., Doherty, J.A., Fereday, S., Fortner, R.T., Gayther, S., Gentry-Maharaj, A., Goode, E.L., Goodman, M.T., Harris, H.R., Matsuo, K., Menon, U., Modugno, F., Moysich, K., Qin, B., Ramus, S.J., Risch, H., Rossing, M.A., Schildkraut, J.M., Trabert, B., Vierkant, R.A., Winham, S.J., Wentzensen, N., Wu, A.H., Ziogas, A., Khoja, L., Cho, K., McLean, K., Richardson, J., Grout, B., Chase, A., McKinnon, C., Brenton, J.D., Terry, K.L., Pharoah, P., Berchuck, A., Hanley, G.E., Webb, P.M., Pike, M.C., Pearce, C.L., for the Ovarian Cancer Association Consortium. High pre-diagnosis inflammation-related risk score associated with decreased ovarian cancer survival. Cancer Epidemiology, Biomarkers & Prevention (Accepted- In printing) *Similar in author order. 
  • Phung, M.T. The Australian Ovarian Cancer Study, Webb, P.M., Doherty, J.A., Harris, H.R., Thompson, P.J., Goodman, M.T., Moysich, K., Modugno, F., Ness, R.B., Schildkraut, J., Berchuck, A., Cramer, D.W., Terry, K.L., Titus, L., Lee, A.W., Pike, M.C., Wu, A.H., & Pearce, C.L. on behalf of the Ovarian Cancer Association Consortium (2021). DMPA use associated with decreased risk of ovarian cancer: the mounting evidence of a protective role of progestins. Cancer Epidemiology, Biomarkers & Prevention. doi: 10.1158/1055-9965.EPI-20-1355.
  • Lee, A.W., Rosenzweig, S., Wiensch, A., The Australian Ovarian Cancer Study Group, Ramus, S.J., Menon, U., Gentry-Maharaj, A., Gayther, S.A., Ziogas, A., Anton-Culver, H., Whittemore, A.S., Sieh, W., Rothstein, J.H., McGuire, V., Wentzensen, N., Bandera, E.V., Terry, K.L., Cramer, D.W., Schildkraut, J.M., Berchuck, A., Goode, E.L., Kjaer, S.K., Jensen, A., Ness, R.B., Modugno, F., Moysich, K., Thompson, P.J., Goodman, M.T., Carney, M.E., Chang-Claude, J., Rossing, M.A., Harris, H.R., Doherty, J.A., Risch, H.A., Khoja, L., Alimujiang, A., Phung, M.T., Brieger, K., Mukherjee, B., Pharoah, P.D.P., Wu, A.H., Chenevix-Trench, G., Pike, M.C., Webb, P.M., and Pearce, C.L. (2020) Expanding our understanding of hormones and ovarian cancer risk: The role of incomplete pregnancies. JNCI: Journal of the National Cancer Institute. doi: 10.1093/jnci/djaa099.
  • Phung, T.M., Tin Tin, S., & Elwood, M. (2019). Prognostic models for breast cancer: A systematic review. BMC cancer19(1), 230. doi:10.1186/s12885-019-5442-6.
  • Elwood, J. M., Tawfiq, E., TinTin, S., Marshall, R. J., Phung, T. M., Campbell, I., Harvey, V., … Lawrenson, R. (2018). Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index. BMC cancer, 18(1), 897. doi:10.1186/s12885-018-4791-x.

Additional Information

Ovarian cancer association consortium  http://ocac.ccge.medschl.cam.ac.uk/