Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics

The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.

Focuses on statistical applications from clinical trials, biomarker analysis, and personalized medicine to applications in finance and business analytics A unique selection of papers from broad and multi-disciplinary critical hot topics - from academic, government, and industry perspectives - to appeal to a wide variety of applied research interests All papers feature original, peer-reviewed content Includes supplementary material: sn.pub/extras

Autorentext

Jianchang Lin, Ph.D., is Principal Statistician at Takeda Pharmaceuticals, with extensive experience in oncology drug clinical development, including leading successful NDA/MAA submissions and worldwide drug approvals. Dr. Lin's research interests include Bayesian methodologies, survival analysis and Bayesian adaptive designs, and their application in clinical trials.

Bushi Wang, Ph.D., is a biostatistician at Boehringer Ingelheim Pharmaceuticals, Inc. He researches clinical trials across different therapeutic areas and different phases, largely focusing on late stage oncology and cardiovascular trials, supporting approval. He is co-founder of the Multiple Comparison Procedures Society, a .U.S organization supporting the international MCP conferences.

Xiaowen Hu, Ph.D., is Assistant Professor in the Department of Statistics, Colorado State University. Her research interests include spatial analysis, time series analysis, Bayesian analysis, and statistical analysis in business and empirical finance.

Kun Chen, Ph.D., is Assistant Professor in the Department of Statistics, University of Connecticut. His research interests include multivariate analysis, dimension reduction, robust statistics, statistical computing and their broad applications in ecology, genetics, public health, and other areas of applied statistics.

Ray Liu, Ph.D., is Head of the Statistical Innovation and Consultation Center at Takeda Pharmaceuticals, Inc. His research interests include design and analysis of omics studies, integrated analysis, and text mining.

Inhalt

[cutting to roughly 30 papers]

1. Generalized Confidence Interval Approach for A Statistical Decision Framework Applicable to Multipopulation Tailoring Trials

2. Multi-Regional Clinical Trials Where we have been and where we are going

3. Composite endpoints: Some common misconceptions

4. DIA Adaptive Design Scientific Working Group Best Practices Team: Objectives and Case Studies

5. Methods for Flexible Sample-Size Design in Clinical Trials

6. Statistical Challenges in Testing Multiple Endpoints in Complex Trial Designs

7. Generalized Holm's procedure for multiple testing problem

8. Assessing Benefit and Consistency of Treatment Effect under a Discrete Random Effects Model in Multiregional Clinical Trials
   9. Multiplicity Adjustment in Vaccine Efficacy Trial with Adaptive Population-Enrichment Design

9. Identification of Biomarker Signatures Using Adaptive Elastic Net

10. Design and Analysis of Multiregional Clinical Trials in Evaluation of Medical Devices: A Two-component Bayesian Approach for Targeted Regulatory Decision Making

11. Evaluation of strategies for designing Phase 2 dose finding studies

12. Bayesian Hierarchical Monotone Regression I-splines for Dose-Response Assessment and Drug-Drug Interaction Analysis

13. Continuous Safety Signal Monitoring with Blinded Data

14. Bayesian integration of in vitro biomarker data to in vivo safety assessment

15. Bayesian Path Specific Frailty Models for Multi-state Survival Data with Applications

16. Sample Size Allocation in a Dose-Ranging Trial Combined with PoC 18. A Bayesian Approach For Subgroup Analysis

17. Design Considerations in Dose Finding Studies

18. Identifying Predictive Biomarkers in A Dose-Response Study

19. A nationwide cohort study of Influenza vaccine on stroke prevention in the chronic kidney disease population

20. Multivariate Spatial Modeling on Spheres

21. Statistical Method for Change-set Analysis

22. Statistical Issues in Health Related Quality of Life research

23. Analysis of clustered longitudinal/functional data

24. Variable Selection Methods for Functional Regression Models

25. Promoting Similarity of Sparsity Structures in Integrative Analysis

26. Optimal Estimation for The Functional Cox Model 29. Bayesian Spatial Clustering Method and Its Application In Radiology

27. Bayesian Nonlinear Model Selection for Gene Regulatory Networks

28. Innovated Interaction Screening for High-Dimensional Nonlinear Classification

29. Spatial Bayesian Hierarchical Model for small area estimation of categorical data

30. Evaluate the Most Accurate Animal Model With Application to Pediatric Medulloblastoma

31. Analysis Optimization for Biomarker and Subgroup Identification

32. Statistical Methods for Analytical Comparability36. Design and Statistical Analysis of Multidrug Combinations in Preclinical Studies and Clinical Trials

33. Composite Kernel Machine Regression Based on Likelihood Ratio Test and its Application on Genomic Studies 38. Statistical Applications for Biosimilar Product Development

34. Correcting Ascertainment Bias in Biomarker Identification

35. Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials

36. ROC-based meta analysis with individual level information

37. Optimal Marker-Adaptive Designs for Targeted Therapy Based on Imperfectly Measured Biomarkers

38. Statistical considerations for evaluating prognostic imaging biomarkers

39. Stacking survival models.- Estimation of Discrete Survival Function through the Modeling of Diagnostic Accuracy for Mismeasured Outcome Data

40. A Bivariate Copula Random-Effects Model for Length of Stay and Cost

41. Non-inferiority tests for prognostic models

42. Explained Variation in Correlated Survival Data 48. Web-based Analytics for Business Decision Making

43. Economic Movement and Mental Health: A Population-based Study

44. Hypothesis Test of Mediation Effect in Causal Mediation Model with High-dimensional Mediators