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Statistical thinking for non-statisticians in drug regulation / / Richard Kay
| Statistical thinking for non-statisticians in drug regulation / / Richard Kay |
| Autore | Kay R (Richard), <1949-> |
| Edizione | [Third edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley-Blackwell, , [2023] |
| Descrizione fisica | 1 online resource (435 pages) |
| Disciplina | 338.476151 |
| Soggetto topico | Drug approval |
| ISBN |
9781119867395
9781119867388 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface to the third edition -- Preface to the second edition -- Preface to the first edition -- Abbreviations -- CHAPTER 1 Basic ideas in clinical trial design -- 1.1 Historical perspective -- 1.2 Control groups -- 1.3 Placebos and blinding -- 1.4 Randomisation -- 1.4.1 Unrestricted randomisation -- 1.4.2 Block randomisation -- 1.4.3 Unequal randomisation -- 1.4.4 Stratified randomisation -- 1.4.5 Central randomisation -- 1.4.6 Dynamic allocation and minimisation -- 1.4.7 Cluster randomisation -- 1.5 Bias and precision -- 1.6 Between- and within-patient designs -- 1.7 Crossover trials -- 1.8 Signal, noise and evidence -- 1.8.1 Signal -- 1.8.2 Noise -- 1.8.3 Signal-to-noise ratio -- 1.9 Confirmatory and exploratory trials -- 1.10 Superiority, equivalence and non-inferiority trials -- 1.11 Endpoint types -- 1.12 Choice of endpoint -- 1.12.1 Primary endpoints -- 1.12.2 Secondary endpoints -- 1.12.3 Surrogate endpoints -- 1.12.4 Global assessment endpoints -- 1.12.5 Composite endpoints -- 1.12.6 Categorisation -- CHAPTER 2 Sampling and inferential statistics -- 2.1 Sample and population -- 2.2 Sample statistics and population parameters -- 2.2.1 Sample and population distribution -- 2.2.2 Median and mean -- 2.2.3 Standard deviation -- 2.2.4 Notation -- 2.2.5 Box plots -- 2.3 The normal distribution -- 2.4 Sampling and the standard error of the mean -- 2.5 Standard errors more generally -- 2.5.1 The standard error for the difference between two means -- 2.5.2 Standard errors for proportions -- 2.5.3 The general setting -- CHAPTER 3 Confidence intervals and p-values -- 3.1 Confidence intervals for a single mean -- 3.1.1 The 95% confidence interval -- 3.1.2 Changing the confidence coefficient -- 3.1.3 Changing the multiplying constant -- 3.1.4 The role of the standard error.
3.2 Confidence intervals for other parameters -- 3.2.1 Difference between two means -- 3.2.2 Confidence interval for proportions -- 3.2.3 General case -- 3.2.4 Bootstrap confidence interval -- 3.3 Hypothesis testing -- 3.3.1 Interpreting the p-value -- 3.3.2 Calculating the p-value -- 3.3.3 A common process -- 3.3.4 The language of statistical significance -- 3.3.5 One-sided and two-sided tests -- CHAPTER 4 Tests for simple treatment comparisons -- 4.1 The unpaired t-test -- 4.2 The paired t-test -- 4.3 Interpreting the t-tests -- 4.4 The chi-square test for binary endpoints -- 4.4.1 Pearson chi-square -- 4.4.2 The link to a ratio of the signal to the standard error -- 4.5 Measures of treatment benefit -- 4.5.1 Odds ratio -- 4.5.2 Relative risk -- 4.5.3 Relative and absolute risk reduction -- 4.5.4 Number needed to treat -- 4.5.5 Confidence intervals -- 4.5.6 Interpretation -- 4.6 Fisher's exact test -- 4.7 Tests for categorical and ordered categorical endpoints -- 4.7.1 Categorical endpoints -- 4.7.2 Ordered categorical (ordinal) endpoints -- 4.7.3 Measures of treatment benefit -- 4.8 Count endpoints -- 4.9 Extensions for multiple treatment groups -- 4.9.1 Continuous endpoints -- 4.9.2 Binary, categorical and ordered categorical endpoints -- 4.9.3 Dose-ranging studies -- 4.9.4 Further discussion -- CHAPTER 5 Adjusting the analysis -- 5.1 Objectives for adjusted analysis -- 5.2 Comparing treatments for continuous endpoints -- 5.3 Least squares means -- 5.4 Evaluating the homogeneity of the treatment effect -- 5.4.1 Treatment-by-factor interactions -- 5.4.2 Quantitative and qualitative interactions -- 5.5 Methods for binary and ordered categorical endpoints -- 5.6 Multi-centre trials -- 5.6.1 Adjusting for centre -- 5.6.2 Significant treatment-by-centre interactions -- 5.6.3 Combining centres -- CHAPTER 6 Regression and analysis of covariance. 6.1 Adjusting for baseline factors -- 6.2 Simple linear regression -- 6.3 Multiple regression -- 6.4 Logistic regression for binary endpoints -- 6.4.1 Negative binomial regression for count endpoints -- 6.5 Analysis of covariance for continuous outcomes -- 6.5.1 Main effect of treatment -- 6.5.2 Treatment-by-covariate interactions -- 6.5.3 A single model -- 6.5.4 Connection with adjusted analyses -- 6.5.5 Advantages of ANCOVA -- 6.5.6 Least squares means -- 6.5.7 Random element -- 6.6 Other endpoint types -- 6.6.1 Binary endpoints and extensions -- 6.6.2 Count endpoints -- 6.7 Mixed models -- 6.8 Regulatory aspects of the use of covariates -- 6.9 Baseline testing -- 6.10 Correlation and regression -- CHAPTER 7 Intention-to-treat, analysis sets and missing data -- 7.1 The principle of intention-to-treat -- 7.2 The practice of intention-to-treat -- 7.2.1 Full analysis set -- 7.2.2 Per-protocol set -- 7.2.3 Further aspects of ITT -- 7.3 Missing data -- 7.3.1 Introduction -- 7.3.2 Complete cases analysis -- 7.3.3 Last observation carried forward (LOCF) -- 7.3.4 Baseline observation carried forward (BOCF) -- 7.3.5 Success/failure classification -- 7.3.6 Worst-case/best-case classification -- 7.3.7 Sensitivity -- 7.3.8 Avoidance of missing data -- 7.3.9 Classification of missing data -- 7.3.10 Multiple imputation -- 7.4 Intention-to-treat and time-to-event data -- 7.5 General questions and considerations -- CHAPTER 8 Estimands -- 8.1 ICH E9 (R1) -- 8.2 Attributes of an estimand -- 8.2.1 Population -- 8.2.2 Variable -- 8.2.3 Intercurrent event (ICE) -- 8.2.4 Statistic for treatment effect -- 8.3 Estimand strategies -- 8.3.1 Five strategies -- 8.3.2 Treatment policy, composite and hypothetical strategies -- 8.3.3 While on treatment -- 8.3.4 Principal stratification -- 8.4 Sensitivity and supplementary analyses -- 8.4.1 Main estimator. 8.4.2 Sensitivity analyses -- 8.4.3 Supplementary analyses -- CHAPTER 9 Power, sample size and clinical relevance -- 9.1 Type I and type II errors -- 9.2 Power -- 9.3 Calculating sample size -- 9.4 Impact of changing the parameters -- 9.4.1 Standard deviation -- 9.4.2 Event rate in the control group -- 9.4.3 Clinically relevant difference -- 9.5 Regulatory aspects -- 9.5.1 Power 80% -- 9.5.2 Sample size adjustment -- 9.6 Reporting the sample size calculation -- 9.7 Post hoc power -- 9.8 Link between p-values and confidence intervals -- 9.9 Confidence intervals for clinical importance -- 9.10 Misinterpretation of the p-value -- 9.10.1 Conclusions of similarity -- 9.10.2 The problem with 0.05 -- 9.11 Single pivotal trial and 0.05 -- CHAPTER 10 Multiple testing -- 10.1 Inflation of the type I error -- 10.1.1 False positives -- 10.1.2 A simulated trial -- 10.2 How does multiplicity arise? -- 10.3 Regulatory and scientific view -- 10.4 Methods for adjustment -- 10.4.1 Bonferroni correction -- 10.4.2 Holm correction -- 10.4.3 Hochberg correction -- 10.4.4 Interim analyses -- 10.5 Avoiding adjustment -- 10.5.1 Co-primary endpoints -- 10.5.2 Composite endpoints -- 10.5.3 Hierarchical testing -- 10.6 Fallback procedure -- 10.7 Multiple comparisons of treatments -- 10.8 Subgroup testing -- 10.9 Other aspects of multiplicity -- 10.9.1 Using different statistical tests -- 10.9.2 Different analysis sets and methods for missing data -- 10.9.3 Pre-planning -- 10.9.4 Nominal significance -- CHAPTER 11 Non-parametric and related methods -- 11.1 Assumptions underlying the t-tests and their extensions -- 11.2 Homogeneity of variance -- 11.3 The assumption of normality -- 11.4 Non-normality and transformations -- 11.5 Non-parametric tests -- 11.5.1 The Mann-Whitney U-test -- 11.5.2 The Wilcoxon signed rank test -- 11.5.3 General comments. 11.6 Advantages and disadvantages of non-parametric methods -- 11.7 Outliers -- CHAPTER 12 Equivalence and non-inferiority -- 12.1 Demonstrating similarity -- 12.2 Confidence intervals for equivalence -- 12.3 Confidence intervals for non-inferiority -- 12.4 A p-value approach -- 12.5 Assay sensitivity -- 12.6 Analysis sets -- 12.7 The choice of -- 12.7.1 Bioequivalence -- 12.7.2 Therapeutic equivalence, biosimilars -- 12.7.3 Non-inferiority -- 12.7.4 The 10% rule for cure rates -- 12.7.5 The synthesis method -- 12.8 Biocreep and constancy -- 12.9 Sample size calculations -- 12.10 Switching between non-inferiority and superiority -- 12.11 Biosimilars -- CHAPTER 13 The analysis of survival data -- 13.1 Time-to-event data and censoring -- 13.2 Kaplan-Meier curves -- 13.2.1 Plotting Kaplan-Meier curves -- 13.2.2 Event rates and relative risk -- 13.2.3 Median event times -- 13.3 Treatment comparisons -- 13.4 The hazard ratio -- 13.4.1 The hazard rate -- 13.4.2 Constant hazard ratio -- 13.4.3 Non-constant hazard ratio -- 13.4.4 Link to survival curves -- 13.4.5 Calculating Kaplan-Meier curves -- 13.5 Restricted mean survival time -- 13.6 Adjusted analyses -- 13.6.1 Stratified methods -- 13.6.2 Proportional hazards regression -- 13.6.3 Accelerated failure time model -- 13.7 Independent censoring -- 13.8 Crossover -- 13.8.1 Rank Preserving Structural Failure Time Model -- 13.8.2 Regulatory position -- 13.9 Composite time-to-event endpoints -- 13.9.1 Cumulative incidence functions -- 13.9.2 Regulatory position -- 13.10 Sample size calculations -- CHAPTER 14 Interim analysis and data monitoring committees -- 14.1 Stopping rules for interim analysis -- 14.2 Stopping for efficacy and futility -- 14.2.1 Efficacy -- 14.2.2 Futility and conditional power -- 14.2.3 Some practical issues -- 14.2.4 Point estimates and confidence intervals -- 14.3 Monitoring safety. 14.4 Data monitoring committees. |
| Record Nr. | UNINA-9910678187803321 |
Kay R (Richard), <1949->
|
||
| Hoboken, New Jersey : , : Wiley-Blackwell, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical thinking for non-statisticians in drug regulation / / Richard Kay
| Statistical thinking for non-statisticians in drug regulation / / Richard Kay |
| Autore | Kay R (Richard), <1949-> |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Chichester, England : , : Wiley Blackwell, , 2015 |
| Descrizione fisica | 1 online resource (370 p.) |
| Disciplina | 615.5/80724 |
| Soggetto topico |
Drugs - Testing
Drugs - Design |
| ISBN |
1-118-47097-4
1-118-47099-0 1-118-47096-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Basic ideas in clinical trial design -- Sampling and inferential statistics -- Confidence intervals and p-values -- Tests for simple treatment comparisons -- Adjusting the analysis -- Regression and analysis of covariance -- Intention-to-treat and analysis sets -- Power and sample size -- Statistical significance and clinical importance -- Multiple testing -- Non-parametric and related methods -- Equivalence and non-inferiority -- The analysis of survival data -- Interim analysis and data monitoring committees -- Bayesian statistics -- Adaptive designs -- Observational studies -- Meta-analysis -- Methods for the safety analysis and safety monitoring -- Diagnosis -- The role of statistics and statisticians. |
| Record Nr. | UNINA-9910132349003321 |
|
Kay R (Richard), <1949->
|
||
| Chichester, England : , : Wiley Blackwell, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical thinking for non-statisticians in drug regulation / / Richard Kay
| Statistical thinking for non-statisticians in drug regulation / / Richard Kay |
| Autore | Kay R (Richard), <1949-> |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Chichester, England : , : Wiley Blackwell, , 2015 |
| Descrizione fisica | 1 online resource (370 p.) |
| Disciplina | 615.5/80724 |
| Soggetto topico |
Drugs - Testing
Drugs - Design |
| ISBN |
1-118-47097-4
1-118-47099-0 1-118-47096-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Basic ideas in clinical trial design -- Sampling and inferential statistics -- Confidence intervals and p-values -- Tests for simple treatment comparisons -- Adjusting the analysis -- Regression and analysis of covariance -- Intention-to-treat and analysis sets -- Power and sample size -- Statistical significance and clinical importance -- Multiple testing -- Non-parametric and related methods -- Equivalence and non-inferiority -- The analysis of survival data -- Interim analysis and data monitoring committees -- Bayesian statistics -- Adaptive designs -- Observational studies -- Meta-analysis -- Methods for the safety analysis and safety monitoring -- Diagnosis -- The role of statistics and statisticians. |
| Record Nr. | UNINA-9910818219503321 |
|
Kay R (Richard), <1949->
|
||
| Chichester, England : , : Wiley Blackwell, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||