國立虎尾科技大學 |

Analysis of Safety Data of Drug Trials = An Update /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Analysis of Safety Data of Drug Trials/ by Ton J. Cleophas, Aeilko H. Zwinderman.
Reminder of title:	An Update /
Author:	Cleophas, Ton J.
other author:	Zwinderman, Aeilko H.
Description:	XI, 217 p. 191 illus., 28 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Medicine. -
Online resource:	https://doi.org/10.1007/978-3-030-05804-3
ISBN:	9783030058043

Analysis of Safety Data of Drug Trials = An Update /
Cleophas, Ton J.

Analysis of Safety Data of Drug TrialsAn Update /[electronic resource] :by Ton J. Cleophas, Aeilko H. Zwinderman. - 1st ed. 2019. - XI, 217 p. 191 illus., 28 illus. in color.online resource.

Preface -- General Introduction -- Significant and Insignificant Adverse Effect -- Incidence Ratios and Reporting Ratios of Adverse Effects -- Safety Analysis and the Alternative Hypothesis -- Forest Plots of Adverse Effects -- Graphics of Adverse Effects -- Repeated Measures Methods for Testing Adverse Effects -- Benefit Risk Ratios -- Equivalence, Non-inferiority and Superiority Testing of Adverse Effects -- Part II The Analysis of Dependent Adverse Effects -- Independent and Dependent Adverse Effects. Categorical Predictors Assessed as Dependent Adverse Effects. Adverse Effect of the Dependent Type in Crossover Trial -- Confoundings and Interactions Assessed as Dependent Adverse Effects -- Subgroup Characteristics Assessed as Dependent Adverse Effects -- Random Effects Assessed as Dependent Adverse Effects -- Outliers Assessed as Dependent Adverse Effects -- Index. .

The authors, as professors in statistics at various universities in Europe, are worrried about the poor quality of safety data analysis of clinical trials, despite its importance in drug development and pharmacovigilance. Clinical trials, not adequately addressing safety, are unethical. An effective approach for the purpose is to present summaries of prevalences. In order to estimate the probability, that the differences between treatment and control group did not occur merely by chance, a statistical test can be performed. This pretty crude method has recently be supplemented with better sensitive methodologies, based on machine learning clusters and networks, and multivariate analyses. Another important novelty with safety data analysis is the new insights into hypothesis testing, favoring the alternative hypotheses instead of the null hypotheses. Finally the issue of dependency is addressed. Adverse effects may be either dependent or independent of the main outcome. Dependent adverse effect are dependent not only on the treatment modalities, but also on the outcome of the trials. Random heterogeneities, outliers, confounders, interaction factors are common in clinical trials, and all of them can be considered kinds of adverse effects of the dependent type. Random regressions and analyses of variance, high dimensional clusterings, partial correlations, structural equations models, and other Bayesian methods are helpful for their analysis. The current edition was particularly written for medical and health professionals and students. It provides examples of modern analytic methods so far largely unused. All of the 16 chapters have two core characteristics, first they are for current usage, second they try and tell what readers need to know in order to understand the methods. Step by step analyses are given and self-assessment examples are supplied. Each chapter can be studied as a stand-alone.

ISBN: 9783030058043

Standard No.: 10.1007/978-3-030-05804-3doiSubjects--Topical Terms:

644133
Medicine.

LC Class. No.: R-RZ

Dewey Class. No.: 610

Analysis of Safety Data of Drug Trials = An Update /
LDR:04143nam a22003855i 4500 001 1005790
003 DE-He213
005 20200630080650.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030058043 $9 978-3-030-05804-3
024 7 $a 10.1007/978-3-030-05804-3 $2 doi
035 $a 978-3-030-05804-3
050 4 $a R-RZ
072 7 $a MBGR $2 bicssc
072 7 $a MED000000 $2 bisacsh
072 7 $a MBGR $2 thema
082 0 4 $a 610 $2 23
100 1 $a Cleophas, Ton J. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 785606
245 1 0 $a Analysis of Safety Data of Drug Trials $h [electronic resource] : $b An Update / $c by Ton J. Cleophas, Aeilko H. Zwinderman.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XI, 217 p. 191 illus., 28 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Preface -- General Introduction -- Significant and Insignificant Adverse Effect -- Incidence Ratios and Reporting Ratios of Adverse Effects -- Safety Analysis and the Alternative Hypothesis -- Forest Plots of Adverse Effects -- Graphics of Adverse Effects -- Repeated Measures Methods for Testing Adverse Effects -- Benefit Risk Ratios -- Equivalence, Non-inferiority and Superiority Testing of Adverse Effects -- Part II The Analysis of Dependent Adverse Effects -- Independent and Dependent Adverse Effects. Categorical Predictors Assessed as Dependent Adverse Effects. Adverse Effect of the Dependent Type in Crossover Trial -- Confoundings and Interactions Assessed as Dependent Adverse Effects -- Subgroup Characteristics Assessed as Dependent Adverse Effects -- Random Effects Assessed as Dependent Adverse Effects -- Outliers Assessed as Dependent Adverse Effects -- Index. .
520 $a The authors, as professors in statistics at various universities in Europe, are worrried about the poor quality of safety data analysis of clinical trials, despite its importance in drug development and pharmacovigilance. Clinical trials, not adequately addressing safety, are unethical. An effective approach for the purpose is to present summaries of prevalences. In order to estimate the probability, that the differences between treatment and control group did not occur merely by chance, a statistical test can be performed. This pretty crude method has recently be supplemented with better sensitive methodologies, based on machine learning clusters and networks, and multivariate analyses. Another important novelty with safety data analysis is the new insights into hypothesis testing, favoring the alternative hypotheses instead of the null hypotheses. Finally the issue of dependency is addressed. Adverse effects may be either dependent or independent of the main outcome. Dependent adverse effect are dependent not only on the treatment modalities, but also on the outcome of the trials. Random heterogeneities, outliers, confounders, interaction factors are common in clinical trials, and all of them can be considered kinds of adverse effects of the dependent type. Random regressions and analyses of variance, high dimensional clusterings, partial correlations, structural equations models, and other Bayesian methods are helpful for their analysis. The current edition was particularly written for medical and health professionals and students. It provides examples of modern analytic methods so far largely unused. All of the 16 chapters have two core characteristics, first they are for current usage, second they try and tell what readers need to know in order to understand the methods. Step by step analyses are given and self-assessment examples are supplied. Each chapter can be studied as a stand-alone.
650 0 $a Medicine. $3 644133
650 0 $a Statistics . $3 1253516
650 1 4 $a Biomedicine, general. $3 1253757
650 2 4 $a Statistics and Computing/Statistics Programs. $3 669775
700 1 $a Zwinderman, Aeilko H. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 785607
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030058036
776 0 8 $i Printed edition: $z 9783030058050
856 4 0 $u https://doi.org/10.1007/978-3-030-05804-3
912 $a ZDB-2-SBL
912 $a ZDB-2-SXB
950 $a Biomedical and Life Sciences (SpringerNature-11642)
950 $a Biomedical and Life Sciences (R0) (SpringerNature-43708)