Zhou Lan

Zhou Lan

Now the Associate Director of Real-World Evidence Analytics at Sanofi; Past Biostatistics Faculty at Brigham and Women's Hospital, Harvard Medical School.

Zhou (Joe) Lan

Who am I?

Zhou (Joe) Lan is an associate director at Real-World Evidence Analytics on Sanofi’s HEVA Team. He earned his PhD in Statistics from North Carolina State University in 2019 and has since focused on real-world evidence studies examining treatment effectiveness, as well as biobank studies supporting R&D biomarker investigation, at Brigham and Women’s Hospital–Harvard Medical School.

As both a lead investigator and collaborative team member in medical research, he has contributed to numerous studies with publications in prestigious journals including JAMIA Open, NEJM, JAHA, JAMA Network Open, Circulation, Neuro-Oncology, and Imaging Neuroscience. As trained biostatistician and data scientist, he has served as lead author on more than 15 publications in prominent journals such as Technometrics, Biometrics, Journal of the Royal Statistical Society: Series A, Data Science in Science.

Investigation Areas

Biobank studies supporting R&D biomarker investigation

  • Neuroscience
    Zhou L, Chen Y, Rushmore J, Zekelman L, Makris N, Rathi Y, Golby AJ, Zhang F, O’Donnell LJ.
    Fiber Microstructure Quantile (FMQ) Regression: A Novel Statistical Approach for Analyzing White Matter Bundles from Periphery to Core.
    Imaging Neuroscience, 3:11, 2025.
    DOI: https://doi.org/10.1162/imaga00569

  • Neuroscience
    Legarreta JH et al.
    Towards an Informed Choice of Diffusion MRI Image Contrasts for Cerebellar Segmentation.
    Human Brain Mapping, 46(11), 2025.
    DOI: https://doi.org/10.1002/hbm.70317

  • Neuroscience
    Lan Z, Foster S, Charney M et al.
    Neurometabolic Network (NMetNet) for Functional Neurological Disorder in Children and Adolescents.
    NeuroImage: Clinical, 46, 2025.

  • Neuroscience
    Beroukhim B et al.
    A novel automated pipeline to assess MR spectroscopy quality control.
    Journal of Neuroimaging, 35(1), 2025.

  • Oncology
    Youssef G et al.
    Prognostic Significance of MGMT Promoter Methylation Status in IDH-mutant Glioma.
    Neuro-Oncology, 2025.

  • Oncology
    Nakhate V et al.
    Evaluation of Sex Differences in Survival Among Glioblastoma Patients Treated with Immune Checkpoint Inhibitors.
    Neuro-Oncology Advances, 2025.

  • Oncology
    Lasica AB et al.
    Clinical, Molecular, and Radiological Predictors of Prognosis in Newly Diagnosed Astrocytoma, IDH-mutant, WHO Grade 4.
    Neuro-Oncology, 27(9):2382–2398, 2025.

  • Cardiology
    Lopez DM et al.
    Utility of 18F-Flurpiridaz PET Relative Flow Reserve in Differentiating Obstructive from Nonobstructive Coronary Artery Disease.
    Circulation: Cardiovascular Imaging, 18(11): e018323, 2025.

  • Cardiology
    Hummel JP et al.
    Predictors of Right Ventricular Pacing in Patients Undergoing Implantable Defibrillator Placement.
    Journal of Cardiovascular Electrophysiology, 36(4), 2025.

  • Oncology
    Lasica AB et al.
    Clinical and Radiographic Predictors of Prognosis in Astrocytoma, IDH-Mutant, WHO Grade 4.
    Neuro-Oncology, 26(Suppl 8): viii188–viii189, 2024.

Real-World Evidence Analytics

  • Cardiology
    McGonagle B et al.
    Association Between Active Cancer and Risk of Thrombotic and Cardiovascular Outcomes in Outpatients with COVID-19.
    TH Open, 2025.

  • Cardiology
    Bikdeli B et al.
    Adjudicated Cardiovascular Events in Patients With COVID‐19.
    Journal of the American Heart Association, 14(24): e044011, 2025.

  • Cardiology
    Scimeca G et al.
    Predictors of Venous Thromboembolic Events in Hospitalized Patients with COVID-19.
    Journal of Thrombosis and Thrombolysis, 58(4):485–496, 2025.

  • Cardiology
    Leyva H et al.
    Non-O Blood Groups and Cardiovascular Outcomes in COVID-19.
    JACC: Advances, 4(4):101641, 2025.

  • Cardiology
    Bikdeli B et al.
    Low Absolute Risk of Thrombotic and Cardiovascular Events in Outpatient Pregnant Women with COVID-19.
    Thrombosis Research, 237:209–215, 2024.

  • Endocrinology
    Thurber EG et al.
    Impact of Telemedicine Use on Subsequent Glycemic Control in Patients with Diabetes.
    Diabetes, 73(Suppl 1):1078-P, 2024.

  • Endocrinology
    Shah N et al.
    Impact of Delays in Statin Therapy Due to Statin Nonacceptance on Cardiovascular Outcomes in Patients with Diabetes.
    Diabetes, 73(Suppl 1):56-OR, 2024.

  • Cardiology
    Brown CJ et al.
    Assessment of Sex Disparities in Nonacceptance of Statin Therapy and LDL Cholesterol Levels Among Patients at High Cardiovascular Risk.
    JAMA Network Open, 6(2): e231047, 2023.

  • Cardiology
    Bikdeli B et al.
    Major Cardiovascular Events After COVID-19: CORONA-VTE-Network Study.
    Thrombosis Research, 228:94–104, 2023.

Clinical Trials

  • Cardiology
    Pfeferman M et al.
    Impact of Enduring Risk Factors on Efficacy and Safety of Extended Anticoagulation for Provoked Venous Thromboembolism.
    Thrombosis Research, 2026.

  • Cardiology
    Piazza G et al.
    Apixaban for Extended Treatment of Provoked Venous Thromboembolism.
    New England Journal of Medicine, 393(12):1166–1176, 2025.

Statistical Methodology

  • Statistical Methods
    Yan L, Zhang X, Lan Z, Bandyopadhyay D, Wu Y, Alzheimer’s Disease Neuroimaging Initiative.
    Variable Screening and Spatial Smoothing in Fréchet Regression with Application to Diffusion Tensor Imaging.
    The Annals of Applied Statistics, 19(1):655–679, 2025.

  • Statistical Methods
    Roy A, Lan Z.
    Double Soft-Thresholded Model for Multi-Group Scalar on Vector-Valued Image Regression.
    Bayesian Analysis, 2026.

  • Statistical Methods
    Lan Z, Roy A, Alzheimer’s Disease Neuroimaging Initiative.
    Spatial von-Mises Fisher Regression for Directional Data.
    Technometrics, 67(4):706–715, 2025.

  • Statistical Methods
    Lan Z, Bao L.
    Multivariate Spatial Modeling for Predicting Missing HIV Prevalence Rates Among Key Populations.
    Journal of the Royal Statistical Society: Series A (Statistics in Society), 187(2), 2024.
    DOI: https://doi.org/10.1093/jrsssa/qnad113

  • Statistical Methods
    Lan Z.
    Correlated Wishart Matrices Classification via an Expectation-Maximization Composite Likelihood-Based Algorithm.
    Statistics and Its Interface, 17(2):173–185, 2024.

  • Statistical Methods
    Lan Z, Reich BJ, Bandyopadhyay D.
    A Spatial Bayesian Semiparametric Mixture Model for Positive Definite Matrices with Applications in Diffusion Tensor Imaging.
    Canadian Journal of Statistics, 49(1):129–149, 2021.

  • Statistical Methods
    Lan Z, Reich BJ, Guinness J, Bandyopadhyay D, Ma L, Moeller FG.
    Geostatistical Modeling of Positive Definite Matrices: An Application to Diffusion Tensor Imaging.
    Biometrics, 2021.

  • Software
    Lan Z, Zhao Y, Kang J, Yu T.
    Bayesian Network Feature Finder (BANFF): an R Package for Gene Network Feature Selection.
    Bioinformatics, 32(23):3685–3687, 2016.