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Teaching Staff

Professor YIN, Guosheng

Professor YIN, Guosheng

Patrick S C Poon Professor in Statistics and Actuarial Science and Chair Professor, Department of Statistics & Actuarial Science, Faculty of Science, HKU

MA (Temple); MSc (N Carolina); PhD (N Carolina)

  • 3917 8313
  • 2858 9041
  • Rm 233, Run Run Shaw Building

Research Interests:

  • AI, Bayesian methods
  • Big data
  • Clinical trials
  • Deep learning
  • High-dimensional analysis
  • Machine learning
  • Survival analysis

 

Awards and Honors:

2013 | Fellow of the American Statistical Association
2012 | Elected Member of the International Statistical Institute
2009 | James E. Grizzle Distinguished Alumni Award, Department of Biostatistics, University of North Carolina at Chapel Hill.

 

Publications:

Book

  1. Yin, G. and Shi, H. (2018). Statistical Design and Analysis in Clinical Trials (in Chinese). Higher Education Press, China.
  2. Yin, G. (2012). Clinical Trial Design: Bayesian and Frequentist Adaptive Methods by John Wiley & Sons (Wiley Series in Probability and Statistics). Hoboken, New Jersey, USA. Japanese translated version by Teramukai, S. and Daimon, T. (2014), Medical Publications, Tokyo, Japan.

Statistical Methodologies

  1. Jiang, F., Yin, G. and Dominici, F. (2018). Bayesian model selection approach to boundary detection with non-local priors. 2018 Conference on Neural Information Processing Systems (NIPS).
  2. Lin, R. and Yin, G. (2018). Uniformly most powerful Bayesian interval design for dose finding. Pharmaceutical Statistics, in press.
  3. Shi, H. and Yin, G. (2018). Control of type I error rates in Bayesian sequential designs. Bayesian Analysis, in press.
  4. Zheng, S, Lin, R., Guo, J. and Yin, G. (2018). Testing homogeneity of high-dimensional covariance matrices. Statistica Sinica, in press.
  5. Lam, C. K., Xu, Y., and Yin, G. (2018). Dynamic portfolio choice without cash. Quantitative Finance, in press.
  6. Liu, Y. and Yin, G. (2018). Average holding price. Annals of Financial Economics 13, No. 01. https://doi.org/10.1142/S2010495218500021).
  7. Shi, H. and Yin, G. (2018). Bayesian enhancement two-stage design for single-arm phase II clinical trials with binary and time-to-event endpoints. Biometrics 74, 1055–1064.
  8. Jiang, F., Ma, Y., and Yin, G. (2018). Kernel-based adaptive randomization toward balance in continuous and discrete covariates. Statistica Sinica, in press.
  9. Li, H., Cao, Z., and Yin, G. (2018). Varying-association copula models for multivariate survival data. Canadian Journal of Statistics, in press.
  10. Dong, F., and Yin, G. (2018). Maximum likelihood estimation for incomplete multinomial data via the weaver algorithm. Statistics and Computing 28, 1095–1117.
  11. Yin, G., Chen, N., and Lee, J. J. (2018). Bayesian adaptive randomization and trial monitoring with predictive probability for time-to-event endpoint. Statistics in Bioscience 10, pp420–438.
  12. Wang, G., Zou, C., and Yin, G. (2018). Change-point detection in multinomial data with a large number of categories. Annals of Statistics 46, 2020–2044.
  13. Shi, H. and Yin, G. (2018). Boosting conditional logit model. Journal of Choice Modeling 26, 48–63.
  14. Zhang, J., Yin, G., Liu, Y., and Wu, Y. (2018). Censored cumulative residual independent screening for ultrahigh-dimensional survival data. Lifetime Data Analysis 24, 273–292.
  15. Shi, H. and Yin, G. (2018). Two-stage seamless transition design from open-label singlearm to randomized double-arm clinical trials. Statistical Methods in Medical Research 27, 158–171.
  16. Lin, R. and Yin, G. (2017). STEIN: A simple toxicity and efficacy interval design for seamless phase I/II clinical trials. Statistics in Medicine 36, 4106–4120.
  17. Duan, X., and Yin, G. (2017). Ensemble approaches to estimating the population mean with missing response. Scandinavian Journal of Statistics 44, 899–917.
  18. Yin, G., Lam, C. K., and Shi, H. (2017). Bayesian randomized clinical trials: from fixed to adaptive design. Contemporary Clinical Trials 59, 77–86.
  19. Shi, H. and Yin, G. (2017). Landmark cure rate models with with time-dependent covariates. Statistical Methods in Medical Research 26, 2042–2054.
  20. Liu, Y. and Yin, G. (2017). Partitioned log-rank tests for the overall homogeneity of hazard rate functions. Lifetime Data Analysis 23, 400–425.
  21. Lin, R. and Yin, G. (2017). Bayesian optimal interval design for dose finding in drugcombination trials. Statistical Methods in Medical Research 26, 2155–2167.
  22. Zhao, X., Wu, Y., and Yin, G. (2017). Sieve maximum likelihood estimation for a general class of accelerated hazards models with bundled parameters. Bernoulli 23, 3385–3411.
  23. Lin, R. and Yin, G. (2017). Nonparametric overdose control with late-onset toxicity in phase I clinical trials. Biostatistics 18, 180–194.
  24. Wu, Y. and Yin, G. (2017). Cure rate quantile regression accommodating both finite and infinite survival times. Canadian Journal of Statistics 45, 29–43.
  25. Wu, Y. and Yin, G. (2017). Multiple imputation for cure rate quantile regression with censored data. Biometrics 73, 94–103.
  26. Shi, H. and Yin, G. (2017). Bayesian two-stage design for phase II clinical trials with switching hypothesis tests. Bayesian Analysis 12, 31–51.
  27. Lin, R. and Yin, G. (2016). Bayesian optimal interval design for drug-combination trials. Frontiers of Biostatistical Methods and Applications in Clinical Oncology. Springer.
  28. Lin, R. and Yin, G. (2016). Robust optimal interval design for high-dimensional dose finding in multi-agent combination trials. ICSA book proceedings for the symposium at Calgary. Springer.
  29. Lin, R., Liu, Z., Zheng, S., and Yin, G. (2016). Power computation for hypothesis testing with high-dimensional covariance matrices. Computational Statistics & Data Analysis 104, 10–23.
  30. Lin, R. and Yin, G. (2016). Bootstrap aggregating continual reassessment method for dose finding in drug-combination trials. Annals of Applied Statistics 10, 2349–2376.
  31. Li, H., Duan, X., and Yin, G. (2016). Generalized method of moments for additive hazards model with clustered dental survival data. Scandinavian Journal of Statistics 43, 1124–1139.
  32. Xu, J., Yin, G., Ohlssen, D., and Bretz, F. (2016). Bayesian two-stage dose finding for cytostatic agents via model adaptation. Journal of Royal Statistical Society C - Applied Statistics 65, 465–482.
  33. Lin, R. and Yin, G. (2015). Bayes factor and posterior probability: complementary statistical evidence to p-value. Contemporary Clinical Trials 44, 33–35.
  34. Morita, S., Sakamaki, K., and Yin, G. (2015). Detecting overall survival benefit derived from survival postprogression rather than progression-free survival. Journal of the National Cancer Institute 107 (8), djv133, doi:10.1093/jnci/djv133.
  35. Ro, K., Zou, C., Wang, Z., and Yin, G. (2015). Outlier detection for high dimensional data. Biometrika 102, 589–599.
  36. Jin, I. H., Huo, L., Yuan, Y., and Yin, G. (2015). Phase I trial design for drug combinations with Bayesian model averaging. Pharmaceutical Statistics 14, 108–119.
  37. Yin, G. and Lin, R. (2015). Continual reassessment methods. Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods Chapter 5, edited by R. Zink and S. Menon, pp. 133–162. SAS Institute Inc., Cary, NC, USA.
  38. Lin, R. and Yin, G. (2015). Overview of adaptive randomization. Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods Chapter 9, edited by R. Zink and S. Menon, pp. 247–272. SAS Institute Inc., Cary, NC, USA.
  39. Lin, R. and Yin, G. (2015). Sample size re-estimation in adaptively randomized clinical trials with missing data. Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects, edited by O. Sverdlov, pp. 269–286. Chapman & Hall/CRC Press.
  40. Wu, Y., Ma, Y., and Yin, G. (2015). Smoothed and corrected score approach to censored quantile regression with measurement errors. Journal of the American Statistical Association 110, 1670–1683.
  41. Yin, G. and Lin, R. (2015). Comments on ‘Competing designs for drug combination in phase I dose-finding clinical trials’ by M-K. Riviere, F. Dubois and S. Zohar Letter to Editor -Statistics in Medicine 34, 13–17.
  42. Wu, Y. and Yin, G. (2015). Conditional quantile screening in ultrahigh-dimensional heterogeneous data. Biometrika 102, 65–76.
  43. Wang, X., Zhang, J., Yu, L., and Yin, G. (2014). Generalized partially linear single-index model for zero-inflated count data. Statistics in Medicine 34, 876–886.
  44. Zou, C., Yin, G., Feng, L., and Wang, Z. (2014). Nonparametric maximum likelihood approach to multiple change-point problems. Annals of Statistics 42, 970–1002.
  45. Xu, J. and Yin, G. (2014). Two-stage adaptive randomization for delayed response in clinical trials. Journal of Royal Statistical Society C - Applied Statistics 63, 559–578.
  46. Yin, G., Zeng, D., and Li, H. (2014). Censored quantile regression with varying coefficients. Statistica Sinica 24, 855–870.
  47. Wu, Y. and Yin, G. (2013). Cure rate quantile regression for censored data with a survival fraction. Journal of the American Statistical Association 108, 1517–1531.
  48. Liu, S., Yin, G., and Yuan, Y. (2013). Bayesian data augmentation dose finding with continual reassessment method and delayed toxicity. Annals of Applied Statistics 7, 2138– 2156.
  49. Yin, G. and Ma, Y. (2013). Pearson-type goodness-of-fit test with bootstrap maximum likelihood estimation. Electronic Journal of Statistics 7, 412–427.
  50. Shi, Y. and Yin, G. (2013). Escalation with overdose control for phase I drug-combination trials. Statistics in Medicine 32, 4400–4412.
  51. Ma, Y. and Yin, G. (2013). Testing overall and subpopulation treatment effects with measurement errors. Statistica Sinica 23, 1019–1042.
  52. Yin, G., Zheng, S., and Xu, J. (2013). Two-stage dose finding for cytostatic agents in phase I clinical trials. Statistics in Medicine 32, 644–660.
  53. Yin, G., Zheng, S., and Xu, J. (2013). Fractional dose-finding methods with late-onset toxicity in phase I clinical trials. Journal of Biopharmaceutical Statistics 23, 856–870.
  54. Gu, X., Yin, G., and Lee, J. J. (2013). Bayesian two-stage Lasso strategies for biomarker selection in personalized medicine development. Contemporary Clinical Trials 36, 642–650.
  55. Huo, L., Yuan, Y., and Yin, G. (2012). Bayesian dose finding for combined drugs with discrete and continuous doses. Bayesian Analysis 7, 235–252.
  56. Diao, G. and Yin, G. (2012). A general transformation class of semiparametric cure rate frailty models. Annals of the Institute of Statistical Mathematics 64, 959–989.
  57. Yin, G., Chen, N., and Lee, J. J. (2012). Phase II trial design with Bayesian adaptive randomization and predictive probability. Journal of Royal Statistical Society C -Applied Statistics 61, 219–235.
  58. Lee, J. J., Chen, N., and Yin, G. (2012). Worth adapting? Revisiting the usefulness of outcome-adaptive randomization. Clinical Cancer Research 18, 4498–4507.
  59. Garcia, T., Ma, Y., and Yin, G. (2011). Efficiency improvement in a class of survival models through model-free covariate incorporation. Lifetime Data Analysis 7, 552–565.
  60. Yuan, Y. and Yin, G. (2011). Dose-response curve estimation: A semiparametric mixture approach. Biometrics 67, 1543–1554.
  61. Yuan, Y. and Yin, G. (2011). Robust EM continual reassessment method in oncology dose finding. Journal of the American Statistical Association 106, 818–831.
  62. Yin, G., Ma, Y., Liang, F., and Yuan, Y. (2011). Stochastic generalized method of moments. Journal of Computational and Graphical Statistics 20, 714–727.
  63. Yuan, Y. and Yin, G. (2011). Bayesian hybrid dose-finding design in phase I oncology clinical trials. Statistics in Medicine 30, 2098–2108.
  64. Yuan, Y. and Yin, G. (2011). Bayesian Phase I/II adaptively randomized oncology trials with combined drugs. Annals of Applied Statistics 5, 924–942.
  65. Ma, Y. and Yin, G. (2011). Censored quantile regression with covariate measurement errors. Statistica Sinica 21, 949–971.
  66. Lei, X., Yuan, Y., and Yin, G. (2011). Bayesian phase II clinical trial design with time-toevent adaptive randomization. Lifetime Data Analysis 17, 156–174.
  67. Yuan, Y. and Yin, G. (2011). On the usefulness of outcome-adaptive randomization. Journal of Clinical Oncology 29, e390–e392.
  68. Yin, G. and Yuan, Y. (2010). Correspondence to the discussion of “Bayesian dose finding in oncology for drug combinations by copula regression.” Journal of Royal Statistical Society C { Applied Statistics 59, 544–546.
  69. Ma, Y. and Yin, G. (2010). Semiparametric median residual life model and inference. Canadian Journal of Statistics 38, 665–679.
  70. Yuan, Y. and Yin, G. (2010). Bayesian quantile regression for longitudinal studies with nonignorable missing data. Biometrics 66, 105–114.
  71. Yin, G. and Yuan, Y. (2010). Bayesian approach for adaptive design. Handbook of Adap- tive Designs in Pharmaceutical and Clinical Development, A. Pong, and S.-C. Chow, (eds.), Chapter 3. pp. (3-1)–(3-19). Boca Raton, FL: Chapman & Hall/CRC.
  72. Yin, G. and Nieto-Barajas, L. E. (2009). Bayesian cure rate model accommodating multiplicative and additive covariates. Statistics and Its Interface 2, 513–521.
  73. Yin, G. and Li, H. (2009). Least squares estimation of varying-coefficient hazard regression with application to breast cancer dose-intensity data. Canadian Journal of Statistics 37, 659–674.
  74. Yin, G. and Yuan, Y. (2009). Bayesian model averaging continual reassessment method in phase I clinical trials. Journal of the American Statistical Association 104, 954–968.
  75. Yin, G. (2009). Bayesian generalized method of moments (with discussion). Bayesian Anal- ysis 4, 191–208; and Rejoinder, 217–222.
  76. Yuan, Y. and Yin, G. (2009). Bayesian dose finding by jointly modeling toxicity and efficacy as time-to-event outcomes. Journal of Royal Statistical Society C { Applied Statistics 58, 719–736.
  77. Li, H. and Yin, G. (2009). Generalized method of moments for linear regression with clustered failure time data. Biometrika 96, 293–306.
  78. Yin, G. and Yuan, Y. (2009). Bayesian dose finding in oncology for drug combinations by copula regression. Journal of Royal Statistical Society C { Applied Statistics 58, 211–224.
  79. Yin, G. (2009). Bayesian chi-squared goodness-of-fit test for censored data. Journal of Statistical Planning and Inference 139, 1474–1483.
  80. Yin, G. and Yuan, Y. (2009). A latent contingency table approach to dose finding for combinations of two agents. Biometrics 65, 866–875.
  81. Yin, G. (2008). Bayesian transformation cure frailty models with multivariate failure time data. Statistics in Medicine 27, 5929–5940.
  82. Yuan, Y. and Yin, G. (2008). Sequential continual reassessment method for two-dimensional dose finding. Statistics in Medicine 27, 5664–5678.
  83. Yin, G., Li, H., and Zeng, D. (2008). Partially linear additive hazards regression with varying coefficients. Journal of the American Statistical Association 103, 1200–1213.
  84. Yin, G., Zeng, D., and Li, H. (2008). Power-transformed linear quantile regression with censored data. Journal of the American Statistical Association 103, 1214–1224.
  85. Ma, Y. and Yin, G. (2008). Cure rate model with mismeasured covariates under transformation. Journal of the American Statistical Association 103, 743–756.
  86. Nieto-Barajas, L. E. and Yin, G. (2008). Bayesian semiparametric cure rate model with an unknown threshold. Scandinavian Journal of Statistics 35, 540–556.
  87. Li, H., Yin, G., and Zhou, Y. (2007). Local likelihood with time-varying coefficient additive hazards model. Canadian Journal of Statistics 35, 321–337.
  88. Ji, Y., Yin, G., Tsui, K.-W., Kolonin, M. G., Sun, J., Arap, W., Pasqualini, R., and Do, K.-A. (2007). Bayesian mixture models for complex high-dimensional count data in phage display experiments. Journal of Royal Statistical Society C { Applied Statistics 56, 1–14.
  89. Cong, X., Yin, G., and Shen, Y. (2007). Marginal analysis of correlated failure time data with informative cluster sizes. Biometrics 63, 663–672.
  90. Yin, G. (2007). Model checking for additive hazards model with multivariate survival data. Journal of Multivariate Analysis 98, 1018–1032.
  91. Ji, Y., Li, Y., and Yin, G. (2007). Bayesian dose finding in phase I clinical trials based on a new statistical framework. Statistica Sinica 17, 531–547.
  92. Yin, G. and Ibrahim, J. (2006). Bayesian transformation hazard models. The Second Lehmann Symposium-Optimality, IMS Lecture Notes-Monographs Series, 170–182.
  93. Yin, G., Li, Y., and Ji, Y. (2006). Bayesian dose-finding in phase I/II trials using toxicity and efficacy odds ratio. Biometrics 62, 777–784.
  94. Zeng, D., Yin, G., and Ibrahim, J. (2006). Semiparametric transformation models for survival data with a cure fraction. Journal of the American Statistical Association 101, 670–684.
  95. Yin, G. and Zeng, D. (2006). Efficient algorithm for computing maximum likelihood estimates in linear transformation models. Journal of Computational and Graphical Statistics 15, 228–245.
  96. Yin, G. and Ibrahim, J. (2005). Cure rate models: a unified approach. Canadian Journal of Statistics 33, 559–570.
  97. Zeng, D., Yin, G., and Ibrahim, J. (2005). Inference for a class of transformed hazard models. Journal of the American Statistical Association 100, 1000–1008.
  98. Yin, G. and Ibrahim, J. (2005). Bayesian frailty models based on Box-Cox transformed hazards. Statistica Sinica 15, 781–794.
  99. Yin, G. and Shen, Y. (2005). Self-designing trial combining with classical group sequential monitoring. Journal of Biopharmaceutical Statistics 15, 667–675.
  100. Yin, G. (2005). Bayesian cure rate frailty models with application to a root canal therapy study. Biometrics 61, 552–558.
  101. Yin, G. and Ibrahim, J. (2005). A general class of Bayesian survival models with zero and non-zero cure fractions. Biometrics 61, 403–412.
  102. Yin, G. and Shen, Y. (2005). Adaptive design and estimation in randomized clinical trials with correlated observations. Biometrics 61, 362–369.
  103. Zeng, D., Lin, D. Y., and Yin, G. (2005). Maximum likelihood estimation in proportional odds model with random effects. Journal of the American Statistical Association 100, 470– 483.
  104. Yin, G. and Ibrahim, J. (2005). A class of Bayesian shared gamma frailty models with multivariate failure time data. Biometrics 61, 209–217.
  105. Yin, G. and Cai, J. (2005). Quantile regression models with multivariate failure time data. Biometrics 61, 152–162.
  106. Yin, G. and Zeng, D. (2005). Pair chart test for an early survival difference. Lifetime Data Analysis 11, 117–129.
  107. Yin, G. and Hu, J. (2004). Two simulation methods for constructing confidence bands under the additive risk model. Journal of Biopharmaceutical Statistics 14, 389–402.
  108. Hu, J., Yin, G., Morris, J. S., Zhang, L., and Wright, A. F. (2004). Entropy and survivalbased weights to combine Affymetrix array types and analyze differential expression and survival. Methods of Microarray Data Analysis IV, Critical Assessment of Microarray Data Analysis, eds. J. S. Shoemaker and S. M. Lin, pp. 95–108.
  109. Morris, J. S., Yin, G., Baggerly, K., Wu, C., and Zhang, L. (2004). Pooling information across different studies and oligonucleotide chip types to identify prognostic genes for lung cancer. Methods of Microarray Data Analysis IV, Critical Assessment of Microarray Data Analysis, eds. J. S. Shoemaker and S. M. Lin, pp. 51–66.
  110. Yin, G. and Cai, J. (2004). Additive hazards model for multivariate failure time data. Biometrika 91, 801–818.
  111. Hu, J. and Yin, G. (2003). A semiparametric regression model for oligonucleotide arrays. Journal of Modern Applied Statistical Methods 2, 256–267.
  112. Yin, G., Cai, J., and Kim, J. (2003). Quantile inference with multivariate failure time data. Biometrical Journal 45, 602–617.

Collaborative Research

  1. Card´o-Vila, M., Marchi´o, S., Sato, M., Staquicini, F., Bronk, J., Yin, G., Zurita, A., Lee, J. J., Hong, W., Wistuba, I., Arap, W., and Pasqualini, R. (2016). Interleukin-11 receptor is a candidate target for ligand-directed therapy in lung cancer: analysis of clinical samples and BMTP-11 pre-clinical activity. American Journal of Pathology 186, 2162–2170.
  2. Wen, Y. F., Wong, H. M., Lin, R., Yin, G., and C. P. McGrath (2015). Inter-ethnic/racial facial variations: A systematic review and Bayesian meta-analysis of photogrammetric studies. Plos One, DOI:10.1371/journal.pone.0134525
  3. Arun, B. K., Dhinghra, K., Valero, V., Kau, S.-W., Broglio, K., Booser, D., Guerra, L., Yin, G., Walters, R., Sahin, A., Ibrahim, N., Buzdar, A. U., Frye, D., Sneige, N., Strom, E., Ross, M., Theriault, R., Vadhan-Raj, S., Hortobagyi, G. N. (2011). Randomized trial of dose intensive neoadjuvant chemotherapy with or without G-CSF in locally advanced breast cancer: long-term results. Oncologist 16, 1527–1534.
  4. Richards, K. L., Zhang, B., Sun, M., Dong, W., Churchill, J., Bachinski, L. L., Wilson, C. D., Baggerly, K. A., Yin, G., Hayes, D. N., Wistuba, I. I. and Krahe, R. (2011). Methylation of the candidate biomarker TCF21 is very frequent across a spectrum of early stage non-small cell lung cancers. Cancer 117, 606–617.
  5. Yuan, P., Kadara, H., Behrens, C., Tang, X., Woods, D., Solis, L. M., Huang, J., Spinola, M., Dong, W., Yin, G., Fujimoto, J., Kim, E., Xie, Y., Girard, L., Moran, C., Hong, W. K., Minna, J. D. and Wistuba, I. I. (2010). Sex determining region Y-box 2 (SOX2) is a potential cell-lineage gene highly expressed in the pathogenesis of squamous cell carcinomas of the lung. PLos ONE 5, e9112. doi:10.1371/journal.pone.0009112
  6. Arun, B. K., Granville, L. A., Yin, G., Middleton, L. P., Dawood, S., Shu, W.-K., Kamal, A., Hsu, L., Hortobagyi, G. N. and Sahin, A. A. (2010). Gluthation-S-transferase-pi (GST-pi) expression in early breast cancer: associated with outcome and response to chemotherapy. Cancer Investigation 28, 554–559.
  7. Sun, M., Behrens, C., Feng, L., Ozburn, N., Tang, X., Yin, G., Komaki, R., Varella-Garcia, M., Hong, W. K., Aldape, K. D. and Wistuba, I. I. (2009). HER family receptor abnormalities in lung cancer brain metastases and corresponding primary tumors. Clinical Cancer Research 15, 4829–4837.
  8. Rivera, E., Mejia, J., Arun, B., Adinin, R., Walters, R., Abenaa B., A., Broglio, K., Yin, G., Hortobagyi, G. and Valero, V. (2008). Phase III study comparing the use of docetaxel on an every-three-week versus weekly schedule in the treatment of metastatic breast cancer. Cancer 112, 1455–1461.
  9. Arun, B., Valero, V., Logan, C., Broglio, K., Rivera, E., Brewster, A., Yin, G., Green, M., Kuerer, H., Gong, Y., Browne, D., Hortobagyi1, G. N. and Sneige, N. (2007). Comparison of ductal lavage and random periareolar fine needle aspiration as tissue acquisition methods in early breast cancer prevention trials. Clinical Cancer Research 13, 4943–4948.
  10. Gonzalez, R. J., Buzdar, A. U., Symmans, W. F., Yen, T. W., Broglio, K. R., Lucci, A., Esteva, F. J., Yin, G. and Kuerer, H. M. (2007). Novel clinical trial designs for treatment of ductal carcinoma in situ of the breast with trastuzumab (herceptin). Breast Journal 13, 72–75.
  11. Rivera, E., Meyers, C., Groves, M., Valero, V., Francis, D., Arun, B., Broglio, K., Yin, G., Hortobagyi, G. N. and Buchholz, T. (2006). Phase I study of capecitabine in combination with temozolomide in the treatment of patients with brain metastases from breast carcinoma. Cancer 107, 1348–1354.
  12. Sneige, N., Liu, B., Yin, G. and Arun, B. K. (2006). Correlation of cytologic findings and chromosomal instability detected by fluorescence in situ hybridization in breast fine-needle aspiration specimens from women at high risk for breast cancer. Modern Pathology 19, 622– 629.
  13. Klos, K. S., Sun, M., Tan, M., Zhou, X., Li, P., Yang, W., Yin, G. and Yu, D. (2006). ErbB2 increases VEGF protein synthesis via activation of the mTOR/p70S6K pathway leading to increased angiogenesis and spontaneous metastasis of human breast cancer cells. Cancer Research 66, 2028–2037.
  14. Tan, M., Li, P., Sun, M., Yin, G. and Yu, D. (2006). Upregulation and activation of PKC by ErbB2 through Src promotes breast cancer cell invasion that can be blocked by combined treatment with PKC and Src inhibitors. Oncogene 25, 3286–3295.
  15. Hanrahan, E. O., Broglio, K. R., Buzdar, A. U., Theriault, R. L., Valero, V., Cristofanilli, M., Yin, G., Kau, S.-W., Hortobagyi, G. N. and Rivera, E. (2005). Combined-modality treatment for isolated recurrences of breast carcinoma. Cancer 104, 1158–1171.
  16. Caplan, D., Cai, J., Yin, G. and White, A. (2005). Root canal filled versus non-root canal filled teeth: a retrospective comparison of survival times. Journal of Public Health Dentistry 65, 90–96.
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