Current Employment
Assistant Professor (tenure-track), Department of Biostatistics, The University of Texas MD Anderson Cancer Center
Other Appointment
Adjunct Assistant Professor, Department of Statistics, Rice University, 2020 - Present
Regular Member, UTHealth Graduate School of Biomedical Sciences, 2020 - Present
Professional Service
Associate Editor, Contemporary Clinical Trials, 2020 - Present
Associate Editor, Biometrical Journal, 2020 - Present
Associate Editor, Pharmaceutical Statistics, 2021 - Present
Editorial Board Member, Statistical Methods in Medical Research, 2020 - Present
Education
Ph.D. Biostatistics, The University of Hong Kong, 2012 - 2016
Postdoctoral Fellow, Department of Biostatistics, University of Washington, 2016 - 2017
Postdoctoral Fellow, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 2017 - 2019
Assistant Professor (tenure-track), Department of Biostatistics, The University of Texas MD Anderson Cancer Center
Other Appointment
Adjunct Assistant Professor, Department of Statistics, Rice University, 2020 - Present
Regular Member, UTHealth Graduate School of Biomedical Sciences, 2020 - Present
Professional Service
Associate Editor, Contemporary Clinical Trials, 2020 - Present
Associate Editor, Biometrical Journal, 2020 - Present
Associate Editor, Pharmaceutical Statistics, 2021 - Present
Editorial Board Member, Statistical Methods in Medical Research, 2020 - Present
Education
Ph.D. Biostatistics, The University of Hong Kong, 2012 - 2016
Postdoctoral Fellow, Department of Biostatistics, University of Washington, 2016 - 2017
Postdoctoral Fellow, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 2017 - 2019
Research Interests
- Bayesian adaptive design
- Robust Bayesian method
- Empirical likelihood approach
- Meta-analysis
- High-dimensional inference
Early Phase Clinical Trial Design
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Adaptive Methods in Precision Medicine
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The primary objective of phase I dose-finding trials is to determine the maximum tolerated dose (MTD). As part of my dissertation, I researched innovative and robust designs for single- or multiple-agent phase I dose-finding trials, enabling a more efficient escalation to the therapeutic dose levels to cope with the changing landscape of cancer research. In addition, I applied some ensemble techniques in machine learning to dose finding in drug-combination trials to stabilize the dose movement especially when the trial data are sparse.
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In recent years, the emergence of precision medicine and immunotherapy has changed the landscape of cancer treatment. Although these advancements can significantly prolong life for some cancer patients, they also bring new features that complicate the design and evaluation of trials--even making the conventional trial designs inefficient and dysfunctional. I develop methods to address several challenges in precesion medicine and immunotherapy, such as late-onset responses and heterogenous treatment effects.
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Meta-Analytic Trial Design
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Other Projects
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Compared to inferences that rely on a single study, a meta-analysis of the data from multiple independent studies can achieve higher statistical power, more accurate estimation, and greater reproducibility, while also accounting for between-study variabilities. When designing new early phase clinical trials, there are often multiple available sources which may be relevant to the current study. I am interested in developing a more robust meta-analytic approach that facilitates borrowing information from multiple historical studies while accounting for both the intrinsic heterogeneity across different studies and the discrepancy between the current and historical studies.
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While I enjoy practical challenges that arise from clinical studies, I also work with my collaborators on developing Bayesian doubly robust methods in causal inference, and studying testing procedures on high dimensional covariance or correlation matrices. I also have consulted for or collaborated with researchers in various fields, such as dentistry and oncology, as well as worked with those in the pharmaceutical industry. In the meantime, I am working to develop software (e.g., R packages, user friendly web-based applications, graphical user interface-based software) for implementation of the proposed methods.
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Teaching
- Rice STAT 630 Topics in Clinical Trials, Fall 2020, 2022
- GSBS 1813 Topics in Clinical Trials, Fall 2020, 2022
Software
- Integrated platform for designing clinical trials: [Shiny App]
- BOIN (Bayesian Optimal Interval) design suites (Singe-agent, drug-combination and late-onset dose finding): [R package][Shiny App][Desktop Program]
- BOIN12 for Phase 1/2 trials: [Shiny App]
- TOP (Time-to-event Bayesian Optimal Phasee II) design: [Shiny App]
- Time-to-event keyboard design: [R code][Shiny App]
- NOC (Nonparametric Overdose Control) design: [R code]
Selected Grants
- NIH/NCI - 1R01CA261978-01 (MPI: Thall/Lin), 7/1/2021 - 6/30/2025, Role: MPI
Papers and Publications (Google Scholar)
- Lin, R., Wang, C., Liu, F. and Xu, Y. (2010). A new numerical method of nonlinear equations by four order Runge-Kutta method, Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference,1295– 1299.
- Yin, G. and Lin, R. (2014). 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.
- Lin, R. and Yin, G. (2015). Bayes factor and posterior probability: a complement of statistical evidence to p-value. Contemporary Clinical Trials 44, 33–35.
- Wen, Y.F., Wong, H.M, Lin, R., Yin, G. and McGrath, C.P. (2015) Inter- ethnic/racial facial variations: a systematic review and Bayesian meta-analysis of photogrammetric studies. PLoS ONE 10: e0134525.
- Yin, G. and Lin, R. (2015). Continual reassessment methods Clinical Trial Design Using SAS: Bayesian and Frequentist Methods, edited by R. Zink and S. Menon. SAS Press.
- Lin, R. and Yin, G. (2015). Adaptive randomization. Clinical Trial Design Using SAS: Bayesian and Frequentist Methods, edited by R. Zink and S. Menon. SAS Press.
- Lin, R. and Yin, G. (2015). Sample size re-estimation in adaptively randomized clinical trials with missing data. Modern Adaptive Randomized Clinical Trials: Statistical, Operational, and Regulatory Aspects, edited by O. Sverdlov. Chapman & Hall/CRC Press.
- Lin, R., Zheng, S., Liu, Z. and Yin, G. (2016) Power computation for hypothesis testing with high-dimensional covariance matrices. Computational Statistics & Data Analysis 104, 10–23.
- Lin, R. and Yin, G. (2016) Bootstrap aggregating continual reassessment method for dose finding in drug-combination trials. The Annals of Applied Statistics 10, 2349-2376.
- 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.
- Lin, R. and Yin, G. (2016). Random walk and parallel crossing Bayesian optimal interval design for dose finding with combined drugs. Frontiers of Biostatistical Methods and Applications in Clinical Oncology. Springer.
- Lin, R. and Yin, G. (2017) Nonparametric overdose control with late-onset toxicity in phase I clinical trials, Biostatistics 18, 180-194. [R code]
- Lin, R. and Yin, G. (2017). Bayesian optimal interval design for dose finding in drug-combination trials, Statistical Methods in Medical Research 26, 2155-2167. [R package] [Shiny App] [Windows desktop program with GUI]
- Lin, R. and Yin, G. (2017) STEIN: A simple toxicity- and efficacy-based interval design for seamless phase I/II clinical trials, Statistics in Medicine 36, 4106-4120.
- Lin, R. and Yin, G. (2018) Uniformly most powerful Bayesian interval design with application to dose finding in oncology, Pharmaceutical Statistics 17, 710-724. [R code]
- Lin, R. (2018). Bayesian Optimal Interval Design with Multiple Toxicity Constraints, Biometrics 74, 1320-1330.
- Yuan, Y., Lin, R., Li, D., Nie, L., Warren, K. E. (2018). Time-to-event Bayesian optimal interval design to accelerate phase I trials. Clinical Cancer Research 24, 4921-4930. [Windows desktop program with GUI] [Shiny App]
- Lin, R, and Yuan, Y. (2019). On the relative efficiency of model-assisted designs: A conditional approach. Journal of Biopharmaceutical Statistics 29, 648-662.
- Lam, C., Lin, R. and Yin, G. (2019) Nonparametric overdose control for dose finding in drug-combination trials. Journal of the Royal Statistical Society: Series C (Applied Statistics) 68, 1111-1130.
- Zhong, Y., Wen, Y., Wong, H. M., Yin, G., Lin, R., and Yang, S. (2019). Trends and patterns of disparities in burden of lung cancer in the United States, 1974-2015. Frontiers in Oncology 9, article 404.
- Yuan, Y. and Lin, R. (2019). Novel designs for early phase drug combination trials. Bayesian Applications in Pharmaceutical Development, edited by Natanegara, F. and Lakshminarayanan, M., Taylor and Francis.
- Lin, R. and Yuan, Y. (2020). Time-to-event model-assisted designs for dose-finding with delayed toxicity. Biostatistics 21, 807-824. [R code][Shiny App]
- Lin, R., Coleman, R. L., and Yuan, Y. (2020). TOP: Time-to-event Bayesian optimal phase II trial design for cancer immunotherapy. Journal of the National Cancer Institute 112, 38-45. [Shiny App]
- Lin, R., Thall, P. F., and Yuan, Y. (2020). An adaptive trial design to optimize dose–schedule regimes with delayed outcomes. Biometrics 76, 304-315.
- Zheng, S., Lin, R., Guo, J. and Yin, G. (2020) Testing the equality of several high-dimensional covariance matrices, Statistica Sinica 30, 35-53.
- Pan, H., Lin, R., Zhou, Yan, and Yuan, Y. (2020). Keyboard and c3+3 designs for phase I drug-combination trials. Contemporary Clinical Trials 92, 1551-7144.
- Park Y., and Lin, R. (2020). Discussion on "Predictively consistent prior effective sample sizes". Invited discussion for Biometrics 76, 595-598.
- Oran, B., de Lima, M., Garcia-Manero, G., Thall P. F., Lin, R., et al. (2020). A phase 3 randomized study of 5-Azacytidine maintenance vs observation after transplant in high risk AML/MDS patients. Blood Advances 4, 5580-5588.
- Lin, R. and Lee, J. J. (2020). Novel Bayesian adaptive designs and their applications in cancer clinical trials. Computational and Methodological Statistics and Biostatistics, Springer.
- Lin, R. Thall, P. F., and Yuan, Y. (2021). A phase I-II basket trial design to optimize dose-schedule regimens based on delayed outcomes. Bayesian Analysis 16, 179-202. [Invited talk at ISBA-BioPharma Webinar: www.youtube.com/watch?v=iWkCTvLIR3I] [Slides]
- Lin, R., Yang, Z., Yin, G., and Yuan, Y. (2021). Sample size re-estimation in adaptive population enrichment trials. Contemporary Clinical Trials 100, 106216.
- Zou, T., Lin, R., Zheng, S., and Tian, G. (2021). Two-sample tests for high dimensional covariance matrices using both difference and ratio. Electronic Journal of Statistics 15, 135-210.
- Shi, H., Cao, J., Yuan, Y., and Lin, R.* (2021). uTPI: A utility-based toxicity probability interval design for dose finding in phase I/II trials. Staitstics in Medicine 40, 2626-2649.
- Lin, R., Zhou, Y., Yan, F., Li, D., and Yuan, Y. (2021). BOIN12: Bayesian optimal interval phase I/II trial design for utility-based dose finding in immunotherapy and targeted therapies. JCO Precision Oncology 4, 1393-1402. [Shiny App]
- Zhou, Y., Lin, R., Kuo, Y., Lee, J. J., and Yuan, Y. (2021). A software platform to design and implement novel early phase clinical trials. JCO Cancer Clinical Informatics 5, 91-101.
- Wen, Y., Chen, M., Yin, G., Lin, R., et al. (2021). Global burden of cancer among adolescents and young adults, 1990-2017: An analysis of the Global Burden of Disease Study 2017. Journal of Hematology & Oncology 14, 89.
- Lin, R., Thall, P. F., and Yuan Y. (2021). BAGS: A Bayesian adaptive group sequential trial design for subgroup-specific survival comparisons. Journal of American Statistical Association 116, 322-334.
- Zhou, Y., Lin, R., and Lee, J. J. (2021). The use of local and nonlocal priors in Bayesian test-based monitoring for single-arm phase II clinical trials. Pharmaceutical Statistics 20, 1183-1199.
- Lin, R. *, Yin, G., and Shi, H. (2021) Adaptive model selection design for optimal biological dose finding in phase I/II clinical trials. Biostatistics, in press.
- Olson, A.+, Lin, R.+, Marin, D.+, et al. (2021). Third-party BK virus-specific cytotoxic T lymphocyte therapy for hemorrhagic cystitis following allotransplantation. Journal of Clinical Oncology 29, 2710-2719.
- Xu, T., Meng, Q. H., Gilchrist, S. C., Lin, S. H., Lin, R., et al. (2021). Assessment of prognostic value of high-sensitivity cardiac troponin T for early prediction of chemoradiotherapy-induced cardiotoxicity in non-small cell lung cancer patients: A secondary analysis of a prospective randomized trial. International Journal of Radiation Oncology*Biology*Physics 111, 907–916.
- Ananthakrishnan, R., Lin, R., He, C., Chen, Y., Li, D., and LaValley M. (2022). An overview of the BOIN design and its current extensions for novel early-phase oncology trials. Contemporary Clinical Trials Communications 28, 100943.
- Lin, R.*, Chan, K. C. G., and Shi, H. (2021). A unified Bayesian framework for inference of area under the ROC curve. Statistical Methods in Medical Research 30, 2269-2287
- Zhou, Y., Lin, R., Lee, J. J., Li, D., Wang, L., Li, R., and Yuan, Y. (2022). TITE-BOIN12: Bayesian optimal interval phase I/II
trial design for utility-based dose finding with late-onset toxicity and efficacy. Statistics in Medicine 41, 1918-1931 - Lin, R., Shi, H., Yin, G., Thall, P. F., Yuan, Y., and Flowers, C. (2022). Random-effects meta-analysis of phase I clinical studies and its application to meta-data-analytic dose finding. Annals of Applied Statistics 16, 2481-2504.
- Liu, R., et al., Lin, R.∗, Marchenko, O. (2022). Accuracy and safety of novel designs for phase I drug-combination oncology trials. Statistics in Biopharmaceutical Research 14, 270-282.
- Chi, X.⋆, Yu, Z., and Lin, R.∗ (2022). BOB: Bayesian optimal design for biosimilar trials with co-primary endpoints. Statistics in Medicine 41, 5319-5334.
- Chihara, D., Lin, R., Flowers, C. R., et al. (2022). Early drug development in solid tumours: analysis of National Cancer Institute-sponsored phase 1 trials. The Lancet 400, 512–521.
- Koutroumpakis, E., XU, T., Lopez-Mattei, J., Gilchrist, S., Corrigan, K., Pan, T., Lu, Y., Irizarry-Caro, J. A., Mohan, R., Zhang, X., Meng, Q., Lin, R., et al. (2022). Coronary Calcium Score on Standard of Care Oncologic CT Scans for the Prediction of Adverse Cardiovascular Events in Patients With Non-Small Cell Lung Cancer Treated With Concurrent Chemoradiotherapy. Frontiers in Cardiovascular Medicine 9, 1071701.
- Glitza Oliva, I. C., Ferguson, S. D., Bassett, R. L., . . ., Lin, R. , . . ., Tawbi, H., and Davies, M. A. (2023). Concurrent intrathecal and intravenous nivolumab for metastatic melanoma patients with leptomeningeal disease. Nature Medicine, in press.
- Naser, M. A., Wahid, K. A., . . ., Lin, R. , . . ., Fuller, C. D., and Mohamed, A. S. R. (2023). Quality assurance assessment of intrafraction diffusion-weighted and T2-weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy. Medical Physics, in press.
- Xu, T.⋆, Shi, H., and Lin, R.∗ (2023+). A single-to-double arm transition phase II design using short-term and long-term endpoints. Pharmaceutical Statistics, in press.
- Lin, R. and Chan, K. C. G. (2023+). A Bayesian doubly robust approach for missing data based on moment selection.
- Zheng, S., Yang, G., Lin, R., and Tian, G. (2023+). Testing linear structure of high dimensional correlation matrix.
- Cheng, G., Liu, Z., and Lin, R. (2023+). A new method for block-diagonal selection and validation based on sample correlation matrices.
- Long, Z., Li, Z., and Lin, R. (2023+). On singular values of large dimensional lag-$\tau$ sample auto-correlation matrices. Under revision in Journal of Statistical Planning and Inference.
* Corresponding author
+ Equal contribution as co-first authors