Statistical Methods for Evaluating Safety in Medical Product Development

Автор: Gould, Lawrence
Название: Statistical Methods for Evaluating Safety in Medical Product Development
Язык: английский
Издательство: Chichester, England: Wiley
Год: 2015
Объем: 400 p.
Формат: pdf
Размер: 12,2 mb
This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature.
Provides a guide to statistical methods and application in medical product development
Assists readers in undertaking design and analysis of experiments at various stages of product development
Features case studies throughout the book, as well as, SAS and R code
 CONTENT:
Preface
List of Contributors
1 Introduction
A. Lawrence Gould
1.1 Introduction
1.2 Background and context
1.3 A fundamental principle for understanding safety evaluation
1.4 Stages of safety evaluation in drug development
1.5 National medical product safety monitoring strategy
1.6 Adverse events vs adverse drug reactions, and an overall view safety evaluation
1.7 A brief historical perspective on safety evaluation
1.8 International conference on harmonization
1.9 ICH guidelines References
2 Safety graphics
A. Lawrence Gould
2.1 Introduction
2.1.1 Example and general objectives
2.1.2 What is the graphic trying to say?
2.2 Principles and guidance for constructing effective graphics
2.2.1 General principles
2.3 Graphical displays for addressing specific issues
2.3.1 Frequency of adverse event reports or occurrences
2.3.2 Timing of adverse event reports or occurrences
2.3.3 Temporal variation of vital sign and laboratory measurements
2.3.4 Temporal variation of combinations of vital sign and laboratory-measurements
2.3.5 Functional/multidimensional data
2.3.6 Multivariate outlier detection with multiplicity adjustment based on robust estimates of mean and covariance matrix
2.3.7 Monitoring individual patient trends
2.4 Discussion
References
3 QSAR modeling: prediction of biological activity from chemical structure Andy Liaw and Vladimir Svetnik
3.1 Introduction
3.2 Data
3.2.1 Chemical descriptors
3.2.2 Activity data
3.3 Model building
3.3.1 Random forests
3.3.2 Stochastic gradient boosting
3.4 Model validation and interpretation
3.5 Data example
3.6 Discussion References
4 Ethical and practical issues in phase 1 trials in healthy volunteers Stephen Senn
4.1 Introduction
4.2 Ethical basics
4.3 Inferential matters
4.3.1 Analysis of serious side-effects
4.3.2 Timing of events
4.4 Design for subject safety
4.4.1 Dosing interval
4.4.2 Contemporary dosing
4.5 Analysis
4.5.1 Objectives of first-in-man trials
4.5.2 (In)adequacy of statistical analysis plans
4.5.3 ‘Formal’ statistical analyses
4.6 Design for analysis
4.6.1 Treatment assignments and the role of placebo
4.6.2 Dose-escalation trial design issues
4.6.3 Precision at interim stages
4.7 Some final thoughts
4.7.1 Sharing information
4.8 Conclusions
4.9 Further reading References
5 Phase 1 trials
A. Lawrence Gould
5.1 Introduction
5.2 Dose determined by toxicity
5.2.1 Algorithmic (rule-based) approaches
5.3 Model-based approaches
5.3.1 Basic CRM design
5.3.2 Adaptive refinement of dosage list
5.3.3 Hybrid designs
5.3.4 Comparisons with rule-based designs
5.4 Model-based designs with more than one treatment (or non-monotonic toxicity)
5.5 Designs considering toxicity and efficacy
5.5.1 Binary' efficacy and toxicity considered jointly
5.5.2 Use of surrogate efficacy outcomes
5.5.3 Reduction of efficacy and toxicity outcomes to ordered categories
5.5.4 Binary' toxicity and continuous efficacy
5.5.5 Time to occurrence of binary toxicity and efficacy endpoints
5.5.6 Determining dosage and treatment schedule
5.6 Combinations of active agents
5.7 Software
5.8 Discussion References
6 Summarizing adverse event risk A. Lawrence Gould
6.1 Introduction
6.2 Summarization of key features of adverse event occurrence
6.3 Confidence/credible intervals for risk differences and ratios
6.3.1 Metrics
6.3.2 Coverage and interpretation
6.3.3 Binomial model
6.3.4 Poisson model
6.3.5 Computational results
6.4 Screening for adverse events
6.4.1 Outline of approach
6.4.2 Distributional model
6.4.3 Specification of priors
6.4.4 Example
6.5 Discussion References
7 Statistical analysis of recurrent adverse events Liqun Diao, Richard J. Cook and Ker-Ai Lee
7.1 Introduction
7.2 Recurrent adverse event analysis
7.2.1 Statistical methods for a single sample
7.2.2 Recurrent event analysis and death
7.2.3 Summary statistics for recurrent adverse events
7.3 Comparisons of adverse event rates
7.4 Remarks on computing and an application
7.4.1 Computing and software
7.4.2 Illustration: Analyses of bleeding in a transfusion trial
7.5 Discussion
References
Cardiovascular toxicity, especially QT/QTc prolongation Arne Ring and Robert Schall
8.1 Introduction
8.1.1 The QT interval as a biomarker of cardiovascular risk
8.1.2 Association of the QT interval with the heart rate
8.2 Implementation in preclinical and clinical drug development
8.2.1 Evaluations from sponsor perspective
8.2.2 Regulatory considerations on TQT trials
8.3 Design considerations for ‘‘Thorough QT trials”
8.3.1 Selection of therapeutic and supra-therapeutic exposure
8.3.2 Singlc-vcrsus multiple-dose studies: co-administration of interacting drugs
8.3.3 Baseline measurements
8.3.4 Parallel versus cross-over design
8.3.5 Timing of ECG measurements
8.3.6 Sample size
8.3.7 Complex situations
8.3.8 TQT trials in patients
8.4 Statistical analysis: thorough QT/QTc study
8.4.1 Data
8.4.2 Heart rate correction
8.4.3 A general framework for the assessment of QT prolongation
8.4.4 Statistical inference: Proof of “Lack of QT prolongation”
8.4.5 Mixed models for data from TQT studies
8.5 Examples of ECG trial designs and analyses from the literature
8.5.1 Parallel trial: Nalmefene
8.5.2 Cross-over trial: Linagliptin
8.5.3 Cross-over with minor QTc effect: Sitagliptin
8.5.4 TQT study with heart rate changes but without QTc effect: Darifenacin
8.5.5 Trial with both changes in HR and QT(c): Tolterodine
8.5.6 Boosting the exposure with pharmacokinetic interactions: Domperidone
8.5.7 Double placebo TQT cross-over design
8.6 Other issues in cardiovascular safety
8.6.1 Rosiglitazonc
8.6.2 Requirements of the FDA guidance
8.6.3 Impact on the development of antidiabetic drugs
8.6.4 General impact on biomarker validation References
9 Hepatotoxicity Donald C. Trost
9.1 Introduction
9.2 Liver biology and chemistry
9.2.1 Liver function
9.2.2 Liver pathology
9.2.3 Clinical laboratory tests for liver status
9.2.4 Other clinical manifestations of liver abnormalities
9.3 Drug-induced liver injury
9.3.1 Literature review
9.3.2 Liver toxicology
9.3.3 Clinical trial design
9.4 Classical statistical approaches to the detection of hepatic toxicity
9.4.1 Statistical distributions of analytes
9.4.2 Reference limits
9.4.3 Hy’s rule and other empirical methods
9.5 Stochastic process models for liver homeostasis
9.5.1 The Omstcin-Uhlcnbeck process model
9.5.2 OU data analysis
9.5.3 OU model applied to reference limits
9.6 Summary References
10 Neurotoxicity
A. Lawrence Gould
10.1 Introduction
10.2 Multivariate longitudinal observations
10.3 Electroencephalograms (EEGs)
10.3.1 Special considerations
10.3.2 Mixed effect models
10.3.3 Spatial smoothing by incorporating spatial relationships of channels
10.3.4 Explicit adjustment for muscle-induced (non-EEG) artifacts
10.3.5 Potential extensions
10.4 Discussion
References
11 Safety monitoring Jay Herson
11.1 Introduction
11.2 Planning for safety monitoring
11.3 Safety monitoring-sponsor view (masked, treatment groups pooled)
11.3.1 Frequentist methods for masked or pooled analysis
11.3.2 Likelihood methods for masked or pooled analysis
11.3.3 Bayesian methods for masked or pooled analysis
11.4 Safety monitoring-DMC view (partially or completely unmasked)
11.4.1 DMC data review operations
11.4.2 Types of safety data routinely reviewed
11.4.3 Assay sensitivity
11.4.4 Comparing safety between treatments
11.5 Future challenges in safety monitoring
11.5.1 Adaptive designs
11.5.2 Changes in the setting of clinical trials
11.5.3 New technologies
11.6 Conclusions References
12 Sequential testing for safety evaluation Jie Chen
12.1 Introduction
12.2 Sequential probability ratio test (SPRT)
12.2.1 Wald SPRT basics
12.2.2 SPRT for a single-parameter exponential family
12.2.3 A clinical trial example
12.2.4 Application to monitoring occurrence of adverse events
12.3 Sequential generalized likelihood ratio tests
12.3.1 Sequential GLR tests and stopping boundaries
12.3.2 Extension of sequential GLR tests to multiparameter exponential families
12.3.3 Implementation of sequential GLR tests
12.3.4 Example from Section 12.2.3, continued
12.4 Concluding remarks References
13 Evaluation of post-marketing safety using spontaneous reporting databases Ismati Ahmed, Bernard Begaud and Pascale Tubert-Bitter
13.1 Introduction
13.2 Data structure
13.3 Disproportionality methods
13.3.1 Frequentist methods
13.3.2 Bayesian methods
13.4 Issues and biases
13.4.1 Notoriety bias
13.4.2 Dilution bias
13.4.3 Competition bias
13.5 Method comparisons
13.6 Further refinements
13.6.1 Recent improvements on the detection rule
13.6.2 Bayesian screening approach
13.6.3 Confounding and interactions
13.6.4 Comparison of two signals
13.6.5 An alternative approach References
14 Pharmacovigilance using observational/longitudinal databases and web-based information A. Lawrence Gould
14.1 Introduction
14.2 Methods based on observational databases
14.2.1 Disproportionality analysis with redefinition of report frequency table entries
14.2.2 LGPS and LEOPARD
14.2.3 Self-controlled case series (SCCS)
14.2.4 Case-control approach
14.2.5 Self-controlled cohort
14.2.6 Temporal pattern discovery
14.2.7 Unexpected temporal association rules
14.2.8 Time to onset for vaccine safety
14.3 Web-based pharmacovigilance (infodemiology and infoveillance)
14.4 Discussion References
Index
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