scholarly journals Adaptive group sequential survival comparisons based on log-rank and pointwise test statistics

2021 ◽  
pp. 096228022110432
Author(s):  
Jannik Feld ◽  
Andreas Faldum ◽  
Rene Schmidt
Keyword(s):  
Survival Rate ◽  
Sample Size ◽  
Small Sample ◽  
Adaptive Designs ◽  
Rank Test ◽  
Rank Statistic ◽  
Group Sequential ◽  
Independent Increments ◽  
Allocation Ratio ◽  
Dependent Sample

Whereas the theory of confirmatory adaptive designs is well understood for uncensored data, implementation of adaptive designs in the context of survival trials remains challenging. Commonly used adaptive survival tests are based on the independent increments structure of the log-rank statistic. This implies some relevant limitations: On the one hand, essentially only the interim log-rank statistic may be used for design modifications (such as data-dependent sample size recalculation). Furthermore, the treatment arm allocation ratio in these classical methods is assumed to be constant throughout the trial period. Here, we propose an extension of the independent increments approach to adaptive survival tests that addresses some of these limitations. We present a confirmatory adaptive two-sample log-rank test that allows rejection regions and sample size recalculation rules to be based not only on the interim log-rank statistic, but also on point-wise survival rate estimates, simultaneously. In addition, the possibility is opened to adapt the treatment arm allocation ratio after each interim analysis in a data-dependent way. The ability to include point-wise survival rate estimators in the rejection region of a test for comparing survival curves might be attractive, e.g., for seamless phase II/III designs. Data-dependent adaptation of the allocation ratio could be helpful in multi-arm trials in order to successively steer recruitment into the study arms with the greatest chances of success. The methodology is motivated by the LOGGIC Europe Trial from pediatric oncology. Distributional properties are derived using martingale techniques in the large sample limit. Small sample properties are studied by simulation.

A group sequential design and sample size estimation for an immunotherapy trial with a delayed treatment effect

2020 ◽  
pp. 096228022098078
Author(s):  
Bosheng Li ◽  
Liwen Su ◽  
Jun Gao ◽  
Liyun Jiang ◽  
Fangrong Yan
Keyword(s):  
Sample Size ◽  
Treatment Effect ◽  
Search Algorithm ◽  
Rank Test ◽  
Group Sequential Design ◽  
Group Sequential ◽  
Delayed Treatment ◽  
Maximum Sample Size ◽  
Analytical Estimation ◽  
Immunotherapy Trial

A delayed treatment effect is often observed in the confirmatory trials for immunotherapies and is reflected by a delayed separation of the survival curves of the immunotherapy groups versus the control groups. This phenomenon makes the design based on the log-rank test not applicable because this design would violate the proportional hazard assumption and cause loss of power. Thus, we propose a group sequential design allowing early termination on the basis of efficacy based on a more powerful piecewise weighted log-rank test for an immunotherapy trial with a delayed treatment effect. We present an approach on the group sequential monitoring, in which the information time is defined based on the number of events occurring after the delay time. Furthermore, we developed a one-dimensional search algorithm to determine the required maximum sample size for the proposed design, which uses an analytical estimation obtained by the inflation factor as an initial value and an empirical power function calculated by a simulation-based procedure as an objective function. In the simulation, we tested the unstable accuracy of the analytical estimation, the consistent accuracy of the maximum sample size determined by the search algorithm and the advantages of the proposed design on saving sample size.

Effectiveness of online versus live multi-family psychoeducation group therapy for children and adolescents with mood or anxiety disorders: a pilot study

2016 ◽  
Vol 30 (4) ◽  
Author(s):  
Iman Sapru ◽  
Sarosh Khalid-Khan ◽  
Elaine Choi ◽  
Nazanin Alavi ◽  
Archana Patel ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Group Therapy ◽  
Anxiety Disorders ◽  
Sample Size ◽  
Small Sample Size ◽  
Statistical Significance ◽  
Relative Effectiveness ◽  
Small Sample ◽  
Rank Test ◽  
Family Psychoeducation

Abstract Objective: [1] To highlight the effectiveness of multi-family psychoeducation group therapy (MFPGT) in children with mood or anxiety disorders; [2] to measure change in knowledge and awareness of mood and anxiety disorders in families and children; and [3] to compare the relative effectiveness of online compared to live MFPGT. Method: Participants included families of children (12 years or younger) referred with a mood or anxiety disorder to the Division of Child and Adolescent Psychiatry at Queen’s University (n=16) who were on a waitlist to see a psychiatrist. Change was measured through questionnaires for all parents before and after the program. Using SPSS v22, comparisons between the online (n=6) and live (n=10) groups were made using the Mann-Whitney U test and within group comparisons were made using Wilcoxon signed-rank test. Results: The online and live education groups showed similar overall improvements in knowledge acquisition and expressed emotion in participating families. However, statistical significance must be interpreted with caution due to the small sample size. Conclusions: Online MFPGT may be an effective way to increase knowledge, provide resources and support and build on skills thus giving individuals more control and confidence when dealing with a mood or anxiety disorder while on a waitlist. MFPGT showed equal efficacy in live and online groups, indicating that the online program has the potential to be a more convenient and accessible program for families. More research is needed with a greater sample size.

An improved one-sample log-rank test

2020 ◽  
Vol 29 (10) ◽  
pp. 2814-2829
Author(s):  
Laura Kerschke ◽  
Andreas Faldum ◽  
Rene Schmidt
Keyword(s):  
Sample Size ◽  
Type I Error ◽  
Survival Curve ◽  
Rank Test ◽  
Rank Statistic ◽  
Type I ◽  
Time To Event ◽  
Log Rank Test ◽  
Alternative Approach ◽  
The One

The one-sample log-rank test allows to compare the survival of a single sample with a prefixed reference survival curve. It naturally applies in single-arm phase IIa trials with time-to-event endpoint. Several authors have described that the original one-sample log-rank test is conservative when sample size is small and have proposed strategies to correct the conservativeness. Here, we propose an alternative approach to improve the one-sample log-rank test. Our new one-sample log-rank statistic is based on the unique transformation of the underlying counting process martingale such that the moments of the limiting normal distribution have no shared parameters. Simulation results show that the new one-sample log-rank test gives type I error rate and power close to the nominal levels also when sample size is small, while relevantly reducing the required sample size to achieve the desired power as compared to current approaches to design studies to compare the survival outcome of a sample with a reference.

scholarly journals Type I error inflation of log-rank test with small sample size : A permutation approach and simulation studies

2020 ◽  
Vol 53 (2) ◽  
pp. 93-109
Author(s):  
ZHENG WANG ◽  
ALICIA ZHANG ◽  
YUQI CHEN ◽  
QUI TRAN ◽  
CHRIS HOLLAND
Keyword(s):  
Sample Size ◽  
Type I Error ◽  
Influential Factors ◽  
Small Sample ◽  
Standard Normal Distribution ◽  
Rank Test ◽  
Control Group ◽  
Type I ◽  
Sequential Designs ◽  
Log Rank Test

The log-rank test is a well-accepted non parametric test in comparing the survival time be- tween experimental and control group in regulatory settings. However, we have observed type I error inflation as high as 28% using the test in the simulation settings we have with even moderate sample sizes. In this paper, we explore several factors that potentially con- tribute to the inflation by simulation. Sample size, randomization ratio and significance levels are found to be influential factors. We propose an alternative log-rank test using an approximate permutation distribution instead of the standard normal distribution. It is shown that type I error is controlled when applying the approximate permutation test to both simple clinical trial designs and complicated group sequential designs.

Application of Ultrasound Elastography for Assessing Intestinal Fibrosis in Inflammatory Bowel Disease: Fiction or Reality?

2020 ◽  
Vol 21 ◽  
Author(s):  
Roberto Gabbiadini ◽  
Eirini Zacharopoulou ◽  
Federica Furfaro ◽  
Vincenzo Craviotto ◽  
Alessandra Zilli ◽  
...  
Keyword(s):  
Inflammatory Bowel Disease ◽  
Sample Size ◽  
Bowel Disease ◽  
Small Sample Size ◽  
Shear Wave Elastography ◽  
Small Sample ◽  
Ultrasound Elastography ◽  
Invasive Technique ◽  
Intestinal Fibrosis ◽  
Inflammatory Bowel

Background: Intestinal fibrosis and subsequent strictures represent an important burden in inflammatory bowel disease (IBD). The detection and evaluation of the degree of fibrosis in stricturing Crohn’s disease (CD) is important to address the best therapeutic strategy (medical anti-inflammatory therapy, endoscopic dilation, surgery). Ultrasound elastography (USE) is a non-invasive technique that has been proposed in the field of IBD for evaluating intestinal stiffness as a biomarker of intestinal fibrosis. Objective: The aim of this review is to discuss the ability and current role of ultrasound elastography in the assessment of intestinal fibrosis. Results and Conclusion: Data on USE in IBD are provided by pilot and proof-of-concept studies with small sample size. The first type of USE investigated was strain elastography, while shear wave elastography has been introduced lately. Despite the heterogeneity of the methods of the studies, USE has been proven to be able to assess intestinal fibrosis in patients with stricturing CD. However, before introducing this technique in current practice, further studies with larger sample size and homogeneous parameters, testing reproducibility, and identification of validated cut-off values are needed.

MHealth Applications for People with Cognitive Impairment and Their Caregivers: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Qing Zhao ◽  
Pei Chen ◽  
Yu Zhang ◽  
Haining Liu ◽  
Xianwen Li
Keyword(s):  
Cognitive Impairment ◽  
Sample Size ◽  
Research Design ◽  
Scoping Review ◽  
Life Support ◽  
Small Sample ◽  
Mobile Technologies ◽  
Control Group ◽  
Caregiver Support ◽  
The Impact

BACKGROUND Mobile health application has become an important tool for healthcare systems. One such tool is the delivery of assisting in people with cognitive impairment and their caregivers. OBJECTIVE This scoping review aims to explore and evaluate the existing evidence and challenges on the use of mHealth applications that assisting in people with cognitive impairment and their caregivers. METHODS Nine databases, including PubMed, EMBASE, Cochrane, PsycARTICLES, CINAHL, Web of Science, Applied Science & Technology Source, IEEE Xplore and the ACM Digital Library were searched from inception through June 2020 for the studies of mHealth applications on people with cognitive impairment and their caregivers. Two reviewers independently extracted, checked synthesized data independently. RESULTS Of the 6101 studies retrieved, 64 studies met the inclusion criteria. Three categories emerged from this scoping review. These categories are ‘application functionality’, ‘evaluation strategies’, ‘barriers and challenges’. All the included studies were categorized into 7 groups based on functionality: (1) cognitive assessment; (2) cognitive training; (3) life support; (4) caregiver support; (5) symptom management; (6) reminiscence therapy; (7) exercise intervention. The included studies were broadly categorized into four types: (1) Usability testing; (2) Pilot and feasibility studies; (3) Validation studies; and (4) Efficacy or Effectiveness design. These studies had many defects in research design such as: (1) small sample size; (2) deficiency in active control group; (3) deficiency in analyzing the effectiveness of intervention components; (4) lack of adverse reactions and economic evaluation; (5) lack of consideration about the education level, electronic health literacy and smartphone proficiency of the participants; (6) deficiency in assessment tool; (7) lack of rating the quality of mHealth application. Some progress should be improved in the design of smartphone application functionality, such as: (1) the design of cognitive measurements and training game need to be differentiated; (2) reduce the impact of the learning effect. Besides this, few studies used health behavior theory and performed with standardized reporting. CONCLUSIONS Preliminary results show that mobile technologies facilitate the assistance in people with cognitive impairment and their caregivers. The majority of mHealth application interventions incorporated usability outcome and health outcomes. However, these studies have many defects in research design that limit the extrapolation of research. The content of mHealth application is urgently improved to adapt to demonstrate the real effect. In addition, further research with strong methodological rigor and adequate sample size are needed to examine the feasibility, effectiveness, and cost-effectiveness of mHealth applications for people with cognitive impairment and their caregivers.

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