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    Biomarker Driven Studies

    Biomarker Driven Studies

    Matching Patients with Therapy. Biomarkers can be used as targets to devise treatment strategies that exploit current understanding of the biological mechanisms of the disease.


    Wang Y, et. al, A functional model for classifying metastatic lesions integrating scans and biomarkers.  Statistical Methods in Medical Research 29.1 (2020): 137-150.

    Huang M & Hobbs BP.  Estimating mean local posterior predictive benefit for biomarker-guided treatment strategiesStatistical Methods in Medical Research 28.9 (2019): 2820-2833.

    Ma J, Stingo CF, & Hobbs BP.  Bayesian personalized treatment selection strategies that integrate predictive with prognostic determinantsBiometrical Journal 61.4 (2019): 902-917.

    Xiao L, et. al.  Spatial Bayesian modeling of GLCM with application to malignantlesion characterizationJournal of Applied Statistics 46:2 (2019): 230-246.

    Wang Y, et. al.  An Efficient Nonparametric Estimate for Spatially Correlated Functional Data.  Statistics in Biosciences 11 (2019): 162-183.

    Ma J, Hobbs BP, & Stingo CF.  Integrating genomic signatures for treatment selection with Bayesian predictive failure time modelsStatistical Methods in Medical Research 27.7 (2018): 2093-2113.

    Wen Y, et. al.  Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer.  Radiation Oncology 102.4 (2018): 1090-1097.

    Koay EJ, et. al.  A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal AdenocarcinomaClinical Cancer Research 24.23 (2018): 5883-5894.

    Chen N, Chaan N, & Hobbs BP.  Bayesian classifiers of solid lesions with dynamic CT: Integrating enhancement density with washout density and delay intervalIEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

    Shoemaker K, et. al.  Tree-based Methods for Characterizing Tumor Density HeterogeneityBiocomputing (2018): 216-227.

    Ma J, Stingo CF, & Hobbs BP.  Bayesian Predictive Modeling for Genomic Based Personalized Treatment Selection. Biometrics 72.2 (2016): 575-583.

    Azadeb, et. al.  Integrative Bayesian analysis of neuroimaging-genetic data with application to cocaine dependence. NeuroImage 125 (2016): 813-824.

    Ma J, Hobbs BP, & Stingo CF.  Statistical Methods for Establishing Personalized Treatment Rules in Oncology. BioMed Research International (2015).  

    Wang Y, et. al.  Predictive classification of correlated targets with application to detection of metastatic cancer using functional CT imagingBiometrics 71.3 (2015): 792-802.

    Tang C, Hobbs BP, Amer A, et. al.  Development of an Immune-Pathology Informed Radiomics Model for Non-Small Cell Lung CancerScientific Report 8, 1922 (2018).




    Seamless Trial Designs

    Designs to consolidate the phases of drug development through rapid cohort expansion.
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    Master Protocols

    Designs to simultaneously evaluating multiple drugs and/or disease populations in multiple substudies, allowing for efficient and accelerated drug development.
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    Short Course: Drug development of non-cytotoxics

    Half-day Shortcourse: Subtype Identification and Strategies for Trial Design.
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