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Springer Series in Pharmaceutical Statistics Meinhard Kieser Methods and Applications of Sample Size Calculation and Recalculation in Clinical Trials Springer Series in Pharmaceutical Statistics Series Editors Thomas Permutt, Walnut Creek, CA, USA José Pinheiro, Raritan, NJ, USA Frank Bretz, Basel, Switzerland Peter Müller, Austin, TX, USA Recentadvancesinstatisticshaveledtonewconceptsandsolutionsindifferentareas of pharmaceutical research and development. “Springer Series in Pharmaceutical Statistics” focuses on developments in pharmaceutical statistics and their practical applications in the industry. The main target groups are researchers in the pharmaceutical industry, regulatory agencies and members of the academic community working in the field of pharmaceutical statistics. In order to encourage exchanges between experts in the pharma industry working on the same problems from different perspectives, an additional goal of the series is to provide reference materialfornon-statisticians.Thevolumeswillincludetheresultsofrecentresearch conductedbytheauthorsandadheretohighscholarlystandards.Volumesfocusing on software implementation (e.g. in SAS or R) are especially welcome. The book series covers different aspects of pharmaceutical research, such as drug discovery, developmentandproduction. More information about this series at http://www.springer.com/series/15122 Meinhard Kieser Methods and Applications of Sample Size Calculation and Recalculation in Clinical Trials 123 Meinhard Kieser Institute of Medical Biometry andInformatics University of Heidelberg Heidelberg, Baden-Württemberg, Germany ISSN 2366-8695 ISSN 2366-8709 (electronic) SpringerSeries inPharmaceutical Statistics ISBN978-3-030-49527-5 ISBN978-3-030-49528-2 (eBook) https://doi.org/10.1007/978-3-030-49528-2 MathematicsSubjectClassification: 62P10 ©SpringerNatureSwitzerlandAG2020 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained hereinorforanyerrorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregard tojurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland To Yvonne Preface Correctcalculationoftherequiredsamplesizeisessentialformedicalresearchpro- jects.Inclinicaltrials,againinknowledgecanonlybeachievedifthesamplesize ofthestudyissufficientlyhigh.Atthesametime,thesamplesizeshouldnotbelarger thannecessaryduetoethicalandeconomicreasons.Therefore,samplesizecalcula- tionisoneofthemostfrequentandimportanttopicsofbiostatisticalconsultingaswell asamajorissuewhenassessingclinicaltrialprotocolsinethicscommittees. This book provides methods for sample size calculation and recalculation for a wide range of scenarios encountered when planning clinical trials. To facilitate a deeper understanding of the procedures, the derivations of the methods are pre- sented within a common general framework. Furthermore, application of the methods isillustrated by real clinical trial examples and source code written in the software R implementing the presented approaches is provided. In addition, numeroushintsaregiventopublishedcontributionsonthetopic.Bythis,thebook aimsatgivinganup-to-dateoverviewonsample sizecalculationandrecalculation addressing both application-oriented practitioners and biostatisticians who are also interested in the theoretical background of the methods they apply. Numerouscolleagueshavecontributedtothesuccessofthisbook.Firstofall,I would like to thank Andrea Wendel for her extremely patient and careful writing of the manuscript. I gratefully acknowledge the very valuable contributions made by Dr. Marietta Kirchner and Dr. Katrin Jensen that considerably improved the presentationandcontent.Dr.LauraBennerandDr.SvenjaSchülerkindlyprepared the R code implementing the presented sample size methods, performed compu- tations,andreviewedvariouschapters.Largepartsofthebookarebasedoncourses I held within the Master Program “Medical Biometry/Biostatistics” conducted by the Institute of Medical Biometry and Informatics (IMBI) at the University of Heidelberg and within summer schools on the topic. The book profited from dis- cussions with the students as well as from the thorough review of draft versions of the book by my colleagues at the IMBI Lukas Baumann, Rouven Behnisch, Samuel Kilian, Johannes Krisam, Jan Meis, Maximilian Pilz, and Stella Erdmann, who also contributed R code, performed computations, and prepared figures. In addition,IamgratefultoSpringerPublishersandtheEditorsoftheSpringerSeries vii viii Preface in Pharmaceutical Statistics for giving me the opportunity to publish this book. Aspecialthank goesto Dr. Eva Hiripi from Springerfor herimportant advice and support. Definitely, I would not have been able to prepare the work without the continuing encouragement by my wife Yvonne. Her unique ability to inspire and motivate and to ensure at the same time welcome distractions created perfect conditions for writing this book. Heidelberg, Germany Meinhard Kieser April 2020 Contents Part I Basics 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1 Background and Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.1 The ChroPac Trial . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.2 The Parkinson Trial . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3 General Considerations When Calculating Sample Sizes . . . . . . 7 2 Statistical Test and Sample Size Calculation. . . . . . . . . . . . . . . . . . 11 2.1 The Main Principle of Statistical Testing . . . . . . . . . . . . . . . . . 11 2.2 The Main Principle of Sample Size Calculation . . . . . . . . . . . . 14 Part II Sample Size Calculation 3 Comparison of Two Groups for Normally Distributed Outcomes and Test for Difference or Superiority . . . . . . . . . . . . . . . . . . . . . . 19 3.1 Background and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2 z-Test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.3 t-Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.4 Analysis of Covariance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.5 Bayesian Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.5.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.5.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4 Comparison of Two Groups for Continuous and Ordered Categorical Outcomes and Test for Difference or Superiority. . . . . 37 4.1 Background and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.2 Continuous Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 ix x Contents 4.3 Ordered Categorical Outcomes . . . . . . . . . . . . . . . . . . . . . . . . 40 4.3.1 Assumption-Free Approach. . . . . . . . . . . . . . . . . . . . . 40 4.3.2 Assuming Proportional Odds. . . . . . . . . . . . . . . . . . . . 43 5 Comparison of Two Groups for Binary Outcomes and Test for Difference or Superiority . . . . . . . . . . . . . . . . . . . . . . 47 5.1 Background and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.2 Asymptotic Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 5.2.1 Difference of Rates as Effect Measure . . . . . . . . . . . . . 48 5.2.2 Risk Ratio as Effect Measure . . . . . . . . . . . . . . . . . . . 53 5.2.3 Odds Ratio as Effect Measure. . . . . . . . . . . . . . . . . . . 55 5.2.4 Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3 Exact Unconditional Tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 5.3.1 Basic Concepts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 5.3.2 Fisher-Boschloo Test . . . . . . . . . . . . . . . . . . . . . . . . . 61 6 Comparison of Two Groups for Time-to-Event Outcomes and Test for Difference or Superiority . . . . . . . . . . . . . . . . . . . . . . 65 6.1 Background and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 6.1.1 Time-to-Event Data . . . . . . . . . . . . . . . . . . . . . . . . . . 65 6.1.2 Sample Size Calculation for Time-to-Event Data . . . . . 67 6.2 Exponentially Distributed Time-to-Event Data . . . . . . . . . . . . . 68 6.3 Time-to-Event Data with Proportional Hazards. . . . . . . . . . . . . 70 6.3.1 Approach of Schoenfeld . . . . . . . . . . . . . . . . . . . . . . . 71 6.3.2 Approach of Freedman. . . . . . . . . . . . . . . . . . . . . . . . 72 7 Comparison of More Than Two Groups and Test for Difference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 7.1 Background and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 7.2 Normally Distributed Outcomes. . . . . . . . . . . . . . . . . . . . . . . . 79 7.3 Continuous Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 7.4 Binary Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 7.4.1 Chi-Square Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 7.4.2 Cochran-Armitage Test. . . . . . . . . . . . . . . . . . . . . . . . 84 7.5 Time-to-Event Outcomes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 8 Comparison of Two Groups and Test for Non-Inferiority . . . . . . . 91 8.1 Background and Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 8.2 Normally Distributed Outcomes. . . . . . . . . . . . . . . . . . . . . . . . 92 8.2.1 Difference of Means as Effect Measure . . . . . . . . . . . . 92 8.2.2 Ratio of Means as Effect Measure. . . . . . . . . . . . . . . . 95 8.3 Continuous and Ordered Categorical Outcomes . . . . . . . . . . . . 97

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