Sijin Wen, PhD, MS, MA, BS

Professor

Organization:

West Virginia University School of Public Health

Department:

Epidemiology and Biostatistics

Classification:

Faculty

• PhD, The University of Texas Health Science Center of Houston, 2009
• MS, University of British Columbia, Canada, 2001
• MA, York University, Toronto, Canada, 1998
• BS, Zhongshan University, Guangzhou, China, 1983

1. Sharma S, Stansbury R, Mudgal M, Srinivasan P, Rojas E, Olgers KK, Knollinger S, Selim BJ, Wen S (2025). Post-Discharge non-invasive ventilation for hypercapnic respiratory failure: Outcomes in a Rural Cohort. PLoS One. 2025 Apr 16;20(4):e0321420. doi: 10.1371/journal.pone.032142
2. Shultz C, Gates C, Petros W, Ross K, Veltri L, Craig M, Wen S, Primerano DA, Hazlehurst L, Denvir J, Sdrimas K (2023). Association of genetic variants and survival in patients with acute myeloid leukemia in rural Appalachia. Cancer Rep (Hoboken). 2023 Mar; 6(3):e1746. doi: 10.1002/cnr2.1746.
3. Azimian A, Pyrialakou VD, Lavrenz S, Wen S (2021). Exploring the effects of area-level factors on traffic crash frequency by severity using multivariate space-time models. Analytic Methods in Accident Research. 2021 Sep 1; 31:100163. https://doi.org/10.1016/j.amar.2021.100163
4. Bassler J, Ducatman A, Elliott M, Wen S, Wahlang B, Barnett J, Cave MC. (2019). Environmental perfluoroalkyl acid exposures are associated with liver disease characterized by apoptosis and altered serum adipocytokines. Environ Pollut. 274: 1055-106.
5. Wen S, Ning J, Collins SP, Berry D (2017). A response-adaptive design of initial therapy for emergency department patients with heart failure. Contemporary Clinical Trials. 52:46-53. PMID: 27838474
6. Wen S, Huang X, Frankowski RF, Cormier JN, Pisters P (2016). A Bayesian multivariate joint frailty model for disease recurrences and survival. Statistics in Medicine. 35(26):4794-4812. PMID: 27383540
7. Mathew P, Wen S, Morita S, Thall PF (2011). Placental growth factor and soluble c-kit receptor dynamics characterize the cytokine signature of imatinib in prostate cancer and bone metastases. Journal of Interferon & Cytokine Research. 31(7):539-44. PMID: 21323568.
8. Wang J, Wen S, Symmans WF, Pusztai L, Coombes KR (2009). The bimodality index: A criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data. Cancer Informatics. 7: 199-216. PMID: 19718451
9. Do K-A, McLachlan GJ, Bean R, Wen S (2007). Application of Gene shaving and mixture models to cluster microarray gene expression data. Cancer Informatics. 5: 25-43. PMID: 19390667
10. MacNab YC, Farell P, Gustafson P, Wen S (2004). Estimation in Bayesian disease mapping. Biometrics. 60 (4), 865 – 873. PMID: 15606406
11. Gustafson P, MacNab YC, Wen S (2004). On the value of derivative evaluations and random walk suppression in Markov chain Monte Carlo algorithms. Statistics and Computing. 14 (1): 23 – 37.

2019: Faculty Excellences in Research Award, School of Public Health, WVU

2011: Performance Reward, Department of Biostatistics, MD Anderson Cancer Center, Houston.

2008: Performance Reward, Department of Biostatistics, MD Anderson Cancer Center, Houston.

Sijin Wen is a Professor in the Department of Biostatistics in the School of Public Health at West Virginia University, with a joint appointment in the Mary Babb Randolph Cancer Center. Dr. Wen received his PhD in Biostatistics at The University of Texas Health Science Center in Houston (2009). He previously was a Principal Statistical Analyst at MD Anderson Cancer Center from 2001- 2012, and had served as a biostatistician on several NIH/NCI funded grants such as NCI Specialized Program of Research Excellence (SPORE) in prostate cancer and genitourinary cancer, respectively. Dr. Wen participates in the design and analysis of numerous clinical trials, laboratory experiments and observational studies. He has extensive skills with simulations for clinical trial designs. Much of his work has been computer-intensive and draws heavily on Markov Chain Monte Carlo (MCMC) algorithms for inference.

Most of the research that Dr. Wen is engaged in is motivated by cancer research. His research interests include adaptive designs, interim analysis on efficacy and toxicity in clinical trials for cancer patients, multiple disease recurrences, multivariate survival analysis, and various applied statistical problems. In addition, Dr. Wen is interested in analyzing gene expression data from microarrays, protein arrays or tissue arrays, using clustering algorithms and statistical modeling. He has implemented algorithms and tools for analyzing high-throughput data sets. These analyses identify sets of genes that can be used to distinguish features between normal tissue versus cancer; different types or stages of cancer; or treated versus untreated cancer cells.