Medical Product Safety Evaluation: Biological Models and Statistical Methods

ISBN-13: 9781466508088 / Angielski / Twarda / 2018 / 354 str.

Jie Chen; Joseph F. Heyse; T. L. Lai

Opis

Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Issues and challenges in the design and analysis of safety studies are covered.

Recenzje

"This book provides comprehensive coverage of the statistical methods for evaluating medical product safety in different stages of development life-cycle: from pre-clinical to clinical, and to post marketing studies. As the evaluation of safety of medical products including drugs, vaccines, devices are becoming increasingly important, more and more novel and complex statistical methods have recently been proposed and used. This book gives a very detailed account of the framework for safety evaluation as well as in-depth descriptions of many advanced statistical methods. As far as I am aware, it is the only book that covers such a broad arrays of topics in safety evaluation. Therefore, this book should be appealing to a very large audience, including graduate students and professional statisticians in industry, government, and academia. I think it can be used as a textbook (as many parts of the materials have been used for short courses or part of graduate degree course) or a reference book for practicing statisticians... Overall, I found the book to be a very important contribution to the scientific community."
~Ivan Chan, AbbVie

Spis treści

List of Figures List of Tables Preface 1. Introduction Expecting the unexpected A brief history of medical product regulation Science of safety Differences and similarities between efficacy and safety endpoints Regulatory guidelines and drug withdrawals Medical product safety, adverse events and adverse drug reactions Medical product safety Adverse events versus adverse drug reactions Safety data coding Drug dictionaries WHO Drug Dictionary Anatomical Therapeutic Chemical (ATC) classification NCI Drug Dictionary Adverse event dictionaries Medical Dictionary for Regulatory Activities (Med-DRA) Common Terminology Criteria for Adverse Events (CTCAE) WHO’s Adverse Reaction Terminology (WHO-ART) ICD and COSTART Serious adverse events and safety signals Statistical strategies for safety evaluation and a road map for readers Safety data collection and analysis Safety databases and sequential surveillance in pharmacovigilance An interdisciplinary approach and how the book can be read Supplements and problems 2. Biological Models and Associated Statistical Methods Quantitative structure-activity relationship (QSAR) Toxicity endpoints Molecular descriptors Statistical models in QSAR/QSTR Model validation Pharmacokinetic-pharmacodynamic models Analysis of preclinical safety data Carcinogenicity Reproductive and developmental toxicity Correlated binary and trinary outcomes within litters Dose response Predictive cardiotoxicity The Comprehensive in vitro Proarrythmia Assay (CiPA) Background Ion channels, in silico models and stem-cell derived cardiomyocyte assays Phase I ECG studies Concentration-QTc modeling Toxicogenomics in predictive toxicology Components of TGx TGx biomarkers Regulatory framework in predictive toxicology Regulatory guidelines Safety biomarker qualification In silico models in predictive toxicology Supplements and problems 3. Benefit-Risk Some examples of B-R assessment Tysabri Lorcaserin Crizotinib Critical ingredients for B-R evaluation Planning process Qualitative and quantitative evaluations Benefit-risk formulations A multidisciplinary approach incorporating multiple perspectives Multi-criteria statistical decision theory Multi-criteria decision analysis Stochastic multi-criteria acceptability analysis Stochastic multi-criteria discriminatory method B-R methods using clinical trial data Quality-adjusted benefit-risk assessment methods Q-TWiST Quality-adjusted survival analysis Testing QAL differences between treatment and control Additional statistical methods Number needed to treat(NNT) Incremental net benefits (INB) Weighting schemes, uncertainty, models, supplemental data and patient-level data Bayesian methods Endpoint selection and other considerations Other statistical considerations Supplements and problems 4. Design and Analysis of Clinical Trials with Safety Endpoints Dose escalation in phase I clinical trials Rule-based designs Model-based designs: CRM EWOC, Bayesian threshold designs Individual versus collective ethics and approximate dynamic programming Extensions to combination therapies Modifications for cytostatic cancer therapies Safety considerations for the design of phase II and III studies Challenges of safety evaluation in phase II andphase III trials Conditioning on rare adverse events and the RESTexample A sequential conditioning method and an efficient sequential GLR test Designs for both efficacy and safety endpoints Summary of clinical trial safety data Integrated summary of safety (ISS) Development safety update Clinical safety endpoints Laboratory test results Vital signs Contents Graphic display of safety data Graphic display for proportions and counts Graphic displays for continuous data Statistical methods for the analysis of clinical safety data Incidence rates and confidence intervals Confidence intervals based on Wald’s approximation and moment Confidence intervals based on variance estimate recovery Confidence intervals based on parameter constraint Confidence intervals with stratification Regression models Poisson regression Negative binomial models Rare event analysis Zero-inflated regression models Generalized extreme value regression Time-to-event analysis and competing risks Recurrent events Mean cumulative function Regression models Supplements and problems 5. Multiplicity in the Evaluation of Clinical Safety Data An illustrative example A three-tier adverse event categorization system The MMRV combination vaccine trial Multiplicity issues in efficacy and safety evaluations P-values, FDR and some variants Double false discovery rate and its control FDR control for discrete data Bayesian methods for safety evaluation Berry and Berry’s hierarchical mixture model Gould’s Bayesian screening model Compound decisions and an empirical Bayes approach Supplements and Problems 6. Causal Inference from Post-Marketing Data Post-marketing data collection Clinical trials with safety endpoints Observational pharmacoepidemiologic studies using registries Prospective cohort observational studies Retrospective observational studies Potential outcomes and counterfactuals Causes of effects in attributions for serious adverse health outcomes Counterfactuals, potential outcomes, and Rubin’s causal model Frequentist, Bayesian, and missing data approaches Causal inference from observational studies Matching, sub classification, and standardization Propensity score: Theory and implementation Control for confounding via estimated propensityscore Inverse probability weighting Unmeasured confounding Instrumental variables Econometrics background, instrumental variable tests and GMM extensions Trend-in-trend research design of observational studies Supplements and problems 7. Safety Databases: Statistical Analysis and Pharmacovigilance Safety databases Preclinical data Clinical trial data FDA Adverse Event Reporting System (FAERS) Vaccine Adverse Event Reporting System and Vaccine Safety Link VigiBase Medicare, Medicaid Database, and health insurance claims databases Adverse event reporting database for medical devices Statistical issues in analysis of spontaneous AE databases Statistical methods for the analysis of safety database Reporting ratios and disproportionality analysis Empirical Bayes shrinkage estimation of log ratios Combining results from multiple safety studies by meta-analysis Fixed effects model for combining studies Random effect model for combining studies Meta-analysis of rare events Meta-analysis using individual subject data Bayesian meta-analysis Pharmacoepidemiologic approaches Information content differences among different safety databases and from web-based epidemiologic studies Case-control and self-controlled case series (SCCS) approaches OMOP and systematic pharmacovigilance Postmarketing pharmacoepidemiologic studies: Examples from biologic therapies Quantitative signal detection and machine learning Likelihood ratio tests Supplements and problems 8. Sequential Methods for Safety Surveillance Overview of sequential change detection and diagnosis Combining sequential testing and detection for pharmacovigilance MaxSPRT, CMaxSPRT and sequential GLR tests Implementation of CMaxSPRT Adjustment for confounding Supplement and problems Bibliography Index