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Randomized Phase II Cancer Clinical Trials [Hardback]

(Duke University, Durham, North Carolina, USA)
  • Formāts: Hardback, 244 pages, height x width: 234x156 mm, weight: 566 g, 60 Tables, black and white; 13 Illustrations, black and white
  • Sērija : Chapman & Hall/CRC Biostatistics Series
  • Izdošanas datums: 02-May-2013
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-10: 143987185X
  • ISBN-13: 9781439871850
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Randomized Phase II Cancer Clinical TrialsPalielināt
  • Formāts: Hardback, 244 pages, height x width: 234x156 mm, weight: 566 g, 60 Tables, black and white; 13 Illustrations, black and white
  • Sērija : Chapman & Hall/CRC Biostatistics Series
  • Izdošanas datums: 02-May-2013
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-10: 143987185X
  • ISBN-13: 9781439871850
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781439871850.html
Jung (Duke U.) focuses on the middle of three phases of clinical trials, the one that tests the efficacy and safety of a drug or other cancer therapy on 50-100 people to see if large-scale third-level trials are warranted. Because of the small sample size, he says, exact statistical methods are used. He describes diverse statistical design and analysis methods for randomized phase II trials in oncology for cancer clinicians as well as biostatisticians. His topics include single-arm phase II trial design, single-arm phase II clinical trails with time-to-event endpoints, randomized phase II trials for selection without prospective control arms, randomized trials with heterogeneous patient populations, and some flexible phase II clinical trial designs. Annotation ©2013 Book News, Inc., Portland, OR (booknews.com)

In cancer research, a traditional phase II trial is designed as a single-arm trial that compares the experimental therapy to a historical control. This simple trial design has led to several adverse issues, including increased false positivity of phase II trial results and negative phase III trials. To rectify these problems, oncologists and biostatisticians have begun to use a randomized phase II trial that compares an experimental therapy with a prospective control therapy.

Randomized Phase II Cancer Clinical Trials explains how to properly select and accurately use diverse statistical methods for designing and analyzing phase II trials. The author first reviews the statistical methods for single-arm phase II trials since some methodologies for randomized phase II trials stem from single-arm phase II trials and many phase II cancer clinical trials still use single-arm designs. The book then presents methods for randomized phase II trials and describes statistical methods for both single-arm and randomized phase II trials. Although the text focuses on phase II cancer clinical trials, the statistical methods covered can also be used (with minor modifications) in phase II trials for other diseases and in phase III cancer clinical trials.

Suitable for cancer clinicians and biostatisticians, this book shows how randomized phase II trials with a prospective control resolve the shortcomings of traditional single-arm phase II trials. It provides readers with numerous statistical design and analysis methods for randomized phase II trials in oncology.

Recenzijas

"Randomized Phase II Cancer Clinical Trials will be an invaluable source of information and reference for anyone interested in phase II cancer clinical trials, be it a graduate student, a biostatistics professor, or a cancer clinician in need of flexible designs and statistical analyses. informative and interesting to read. The first of its kind, this book introduces the recent development of the promising randomized phase II trials. This book has a very coherent structure and a legible style. The author did an excellent job providing both contextual and technical details in a form that is both engaging and very readable. a practical guidance book for cancer clinicians, as well as an excellent reference book for a more broad course, say, for example, clinical trials." Journal of the American Statistical Association, December 2014

" this book is very timely and it can help biostatisticians and oncologists design more elaborate cancer clinical trials. This book is well written and nicely organized to illustrate statistical concepts and methods in both single-arm and randomized phase II cancer clinical trials. This book is certainly one of the best textbooks for a graduate-level clinical trial course in the biostatistics department. Also, oncologists with weak statistical background can easily understand the statistical concepts of the phase II cancer clinical trials since the author tries to explain the key concepts with many tables and figures instead of relying on equations." Biometrics, September 2014

" the book is unique in that it focuses solely on phase II cancer clinical trials with its emphasis on randomised trials. It goes far beyond what is covered on phase II clinical trials in cancer in books, for example, in Buyse et al. (1984) and more recently in Crowley & Hoering (2012) or Green et al. (2012). As such, it will definitely serve well as a reference for those involved in phase II cancer c

Preface xiii
1 Introduction
1(4)
2 Single-Arm Phase II Trial Designs
5(20)
2.1 Single-Stage Designs
5(6)
2.1.1 Design of Single-Stage Phase II Trial
6(5)
2.2 Two-Stage Designs
11(7)
2.2.1 Gehan's Design
11(1)
2.2.2 Simon's Optimal Design
11(1)
2.2.3 Admissible Designs
12(2)
2.2.3.1 A Class of Admissible Designs
14(1)
2.2.3.2 Search for Admissible Designs
15(3)
2.3 Two-Stage Designs with Both Upper and Lower Stopping Values
18(5)
References
23(2)
3 Inference on the Binomial Probability in Single-Arm Multistage Clinical Trials
25(26)
3.1 Point Estimation
26(9)
3.1.1 Two-Stage Designs
28(1)
3.1.2 Numerical Studies
29(6)
3.2 Confidence Intervals
35(1)
3.3 P-Values
36(7)
3.3.1 P-Values under Two-Stage Designs
38(5)
3.4 When Realized Sample Size Is Different from That Specified in Design
43(5)
References
48(3)
4 Single-Arm Phase II Clinical Trials with Time-to-Event Endpoints
51(20)
4.1 A Test Based on Median Survival Time
51(5)
4.1.1 Statistical Testing
52(1)
4.1.2 Sample Size Calculation
53(1)
4.1.2.1 Under Uniform Accrual and Exponential Survival Models
54(2)
4.1.2.2 When Accrual Rate Is Given
56(1)
4.2 Maximum Likelihood Method for Exponential Distribution
56(3)
4.2.1 Statistical Testing
57(1)
4.2.2 Sample Size Calculation
57(1)
4.2.2.1 Under a Uniform Accrual Model
58(1)
4.2.2.2 When Accrual Rate Is Known
58(1)
4.3 One-Sample Log-Rank Test
59(4)
4.3.1 Statistical Testing
60(1)
4.3.2 Sample Size Calculation
60(1)
4.3.2.1 Under Proportional Hazards Model Assumption
61(1)
4.3.2.2 Under Uniform Accrual and Exponential Survival Models
62(1)
4.3.2.3 When Accrual Rate Is Given
62(1)
4.4 Two-Stage Trials Using One-Sample Log-Rank Test
63(6)
4.4.1 Two-Stage One-Sample Log-Rank Test
64(1)
4.4.2 Sample Size Calculation
65(2)
4.4.2.1 Under Uniform Accrual and Exponential Survival Models
67(2)
4.5 Binomial Testing on t-Year Survival Probability
69(1)
References
69(2)
5 Single-Arm Phase II Trials with Heterogeneous Patient Populations: Binary and Survival Outcomes
71(20)
5.1 Binary Outcome Case
72(14)
5.1.1 Single-Stage Designs
73(1)
5.1.1.1 Unstratified Testing
73(1)
5.1.1.2 Stratified Testing
74(4)
5.1.2 Two-Stage Designs
78(1)
5.1.2.1 Unstratified Testing
79(1)
5.1.2.2 Stratified Testing
79(4)
5.1.3 Some Extensions
83(1)
5.1.3.1 Conditional P-Value
83(1)
5.1.3.2 When There Are More than Two Subpopulations
84(2)
5.2 Survival Outcome Case: Stratified One-Sample Log-Rank Test
86(3)
5.2.1 Statistical Testing
86(1)
5.2.2 Sample Size Calculation
87(1)
5.2.2.1 Under Uniform Accrual and Exponential Survival Models
88(1)
5.2.2.2 When Accrual Rate Is Given
88(1)
References
89(2)
6 Randomized Phase II Trials for Selection: No Prospective Control Arms
91(14)
6.1 With a Historical Control
93(8)
6.1.1 When Both Arms Have Identical Two-Stage Designs
93(1)
6.1.1.1 One-Sided Test
93(4)
6.1.1.2 Two-Sided Test
97(1)
6.1.2 When Two Arms Have Different Two-Stage Designs
98(1)
6.1.2.1 One-Sided Test
99(1)
6.1.2.2 Two-Sided Test
100(1)
6.2 When No Historical Control Exists
101(1)
6.3 Extension to More than Two Arms
102(1)
6.3.1 When a Historical Control Exists
102(1)
6.3.2 When No Historical Control Exists
103(1)
References
103(2)
7 Randomized Phase II Cancer Clinical Trials with a Prospective Control on Binary Endpoints (I): Two-Sample Binomial Test
105(36)
7.1 Two-Sample Binomial Test
106(20)
7.1.1 Single-Stage Design
106(1)
7.1.2 Two-Stage Designs with Interim Futility Test
107(10)
7.1.2.1 Optimal Design
117(1)
7.1.2.2 Minimax Design
118(1)
7.1.3 Extensions
119(1)
7.1.3.1 Unbalanced Randomized Trials
119(2)
7.1.3.2 Strict Type I and II Error Control
121(1)
7.1.3.3 Randomized Trials with One Control and K Experimental Arms
122(4)
7.2 Two-Stage Designs with Both Upper and Lower Stopping Values
126(12)
7.2.1 Strict Control of Type I Error Rate and Power
138(1)
7.3 Discussions
138(2)
References
140(1)
8 Randomized Phase II Cancer Clinical Trials with a Prospective Control on Binary Endpoints (II): Fisher's Exact Test
141(34)
8.1 Single-Stage Design
142(2)
8.1.1 Algorithm for Single-Stage Design
143(1)
8.2 Two-Stage Design
144(15)
8.2.1 Two-Stage Designs with a Futility Interim Test Only
144(10)
8.2.1.1 Choice of a1 and a
154(1)
8.2.1.2 Choice of n1 and n2
155(2)
8.2.2 Two-Stage Designs with Both Superiority and Futility Interim Tests
157(1)
8.2.2.1 Choice of a1, b1, and a
157(1)
8.2.2.2 Choice of n1 and n2
158(1)
8.3 Extensions
159(12)
8.3.1 Unbalanced Two-Stage Randomized Trials
159(11)
8.3.2 Conditional P-Value
170(1)
8.4 Discussions
171(2)
References
173(2)
9 Randomized Phase II Trials with Heterogeneous Patient Populations: Stratified Fisher's Exact Test
175(16)
9.1 Single-Stage Stratified Fisher's Exact Test
175(10)
9.1.1 Statistical Testing
176(1)
9.1.2 Power and Sample Size Calculation
177(3)
9.1.3 Numerical Studies
180(4)
9.1.4 Discussions
184(1)
9.2 Two-Stage Designs with an Interim Futility Test
185(5)
9.2.1 How to Choose (a1, a)
187(1)
9.2.2 Two-Stage Designs for Stratified Fisher's Exact Test
188(1)
9.2.3 Conditional P-Value
189(1)
References
190(1)
10 Randomized Phase II Clinical Trials Based on Survival Endpoints: Two-Sample Log-Rank Test
191(16)
10.1 Two-Sample Log-Rank Test
191(4)
10.1.1 Test Statistic
191(1)
10.1.2 Sample Size Calculation
192(1)
10.1.2.1 Under Exponential Survival and Uniform Censoring Distributions
193(1)
10.1.2.2 When Accrual Rate Is Specified Instead of Accrual Period
194(1)
10.2 Two-Stage Log-Rank Test
195(7)
10.2.1 Statistical Testing
195(2)
10.2.2 Sample Size Calculation
197(4)
10.2.2.1 Under Uniform Accrual and Exponential Survival Models
201(1)
10.3 Stratified Two-Sample Log-Rank Test for Single-Stage Designs
202(3)
10.3.1 Test Statistic
202(1)
10.3.2 Sample Size Calculation
203(2)
References
205(2)
11 Some Flexible Phase II Clinical Trial Designs
207(12)
11.1 Comparing Survival Distributions under General Hypothesis Testing
207(9)
11.1.1 Generalized Log-Rank Test
208(1)
11.1.2 Sample Size Calculation
209(1)
11.1.2.1 Under Uniform Accrual and Exponential Survival Models
210(1)
11.1.2.2 When Accrual Rate Is Specified Instead of Accrual Period
211(1)
11.1.3 Sample Size Calculation under a General Accrual Pattern
212(4)
11.2 Randomized Phase II Trials for Comparing Maintenance Therapies
216(3)
11.2.1 Two-Sample Log-Rank Test
216(1)
11.2.2 Sample Size Calculation
217(2)
References 219(2)
Index 221
Sin-Ho Jung is a professor of biostatistics and bioinformatics at Duke University School of Medicine. He earned a PhD from the University of Wisconsin-Madison. His research interests include clinical trial design, survival analysis, longitudinal data analysis, clustered data analysis, ROC curve analysis, and microarray studies.