The aim of this PSI one day meeting is to present an overview of available methods for sample size re-estimation together with several case studies where such methods have been used in late phase clinical trials.
Determining the appropriate sample size is an important part of good clinical trial design. When there is uncertainty about some of the design parameters (e.g. variability, control rate, model parameters), it can be challenging to determine up front the number of subjects required for robust evaluation of the study objectives. The aim of this PSI one day meeting is to present an overview of available methods for sample size re-estimation together with several case studies where such methods have been used in late phase clinical trials. There will be plenty of opportunity for discussion and interaction with other statisticians working in this area. Registration is now closed. Please contact the secretariat if you wish to inquire.
There are two distinct reasons for sample size re-estimation in clinical trials: the first is to maintain power when trial data indicate the response variance has been under-estimated; the second is to adapt to interim estimates of the treatment effect. I shall explain how a combination test can be used to ensure rigorous protection of the type I error rate when sample size is adapted in the light of observed data. I shall describe methods for increasing sample size to maintain power when response variance is higher than expected, based on either blinded or unblended variance estimates. I shall discuss the relationship between trial designs that adjust sample size in response to the estimated treatment effect and group sequential designs, which start with a higher maximum sample size but stop early when the data support such a decision. In particular, I shall describe the “promising zone” approach of Mehta and Pocock (Statistics in Medicine, 2011) and show how to modify this procedure in order reduce the average sample size and achieve similar performance to an efficient group sequential design.
Clinical Trials Consulting &Training Ltd
Sample Size Re-Estimation – Some random observations
I was an author on one of the very early papers on sample size re-estimation (Birkett and Day, Stats in Med, 1994; 13: 2455–2463) and have since followed the field with much interest, some despair, and more than a little exasperation.This talk will illustrate some of these facets – mostly based around such methods used in a regulatory context. Several personal experiences will be included (particularly the ones that went wrong) as well as some of the approaches and myths I see in my regular consulting work. What’s “allowed” and what’s not? What makes sense and what doesn’t?
Blinded sample-size re-estimation in multiple sclerosis clinical trials
Multiple sclerosis (MS) is a progressive, degenerative disease. MS is the most common disorder of the CNS in adults, affecting up to 2.5 million people worldwide. Clinical trials in MS use count, recurrent event and time-to-event primary endpoints. Methodology for blinded sample size re-estimation with such endpoints is briefly reviewed. A case study illustrates how to implement blinded sample size re-estimation in a confirmatory MS trial.
Mike Greenwood, AstraZeneca
Do we need more patients? Your statistics should be correct. Make sure you communicate effectively!
We performed a blinded estimation of the pooled exacerbation rate and shape parameter from a negative binomial model in a COPD exacerbation study. This talk will briefly cover the statistics, the practical aspects and focus on the importance of clear (and understandable to non-statisticians) communication of the results and their implications
Nikhil Chauhan, BTG International Ltd
An experience in implementing the Promising Zone sample size re-estimation methodology (Mehta and Pocock, 2011) in a phase 3 oncology study
I will share my experience in implementing the Promising Zone sample size re-estimation methodology (Mehta and Pocock, 2011) in a phase 3 oncology study for the purposes of obtaining a US FDA marketing approval. I will outline how we decided on using this study design, how the sample size calculation was performed, and how the promising zone boundaries were set. I will also share our experience in demonstrating the acceptability of the study design to FDA, in terms of showing control of Type I error. Reference: Mehta, CR and Pocock, SJ (2011), Adaptive increase in sample size when interim results are promising: A practical guide with examples. Statist. Med., 30: 3267–3284. doi: 10.1002/sim.4102
Blinded sample size re-estimation in a Phase III study investigating Progression Free Survival
The CLARINET study investigated the effect of lanreotide compared to placebo in the treatment of metastatic enteropancreatic neuroendocrine tumours with progression free survival as primary endpoint. We will describe the design of the study, the justification for the blinded sample-size re-estimation and some practical aspects of carrying out that decision, including communication within the company, with the DSMB and with regulatory authorities.
Sample Size Re-estimation : « De-risking » a crucial stage of clinical development
Developing cancer treatments is a high-stakes endeavor – especially for emerging biotechs and specialty pharmas with limited portfolios. Conventional phase 3 trial designs are “all or nothing” propositions and well over 50% of these pivotal studies end in failure. Unlike conventional studies, adaptive approaches allow beneficial design changes following interim analysis (IA). A Sample Size Re-estimation design allows selection of the strategy most likely to succeed. We present a case study of such an adaptive approach used to both effectively “de-risk” the final clinical stage as well as be accepted by FDA reviewers based on the concept of the “Promising Zone”. Rather than committing to a larger sample size up front, the decision is deferred until the clinical evidence justifies cost of added subjects. The strategy provided the confidence company leaders – and investors – needed to launch the final development effort toward approval.
Early Bird Rate (until 14th October 2016)
After 14th October 2016
£120 + VAT
£160 + VAT
£160 + VAT
£220 + VAT
£60 + VAT
£90 + VAT
Registration closes on 26th October 2016
Please contact the PSI secretariat on email@example.com if you have any queries.
Registration is now closed. Please contact the secretariat if you wish to inquire.
PSI New Starters Half-Day Networking Event
An opportunity to meet statisticians from across the pharmaceutical industry in a relaxed and informal setting. An exciting program of events and a chance to work in small groups on a data analysis challenge. Lunch provided.
A Non-PSI Event - Protecting confidentiality and privacy in clinical trial and medical data sets
We are increasingly living in a data driven world. Data are collected in many different ways for a variety of purposes. As such, concerns around protecting the privacy of individuals have increased in recent times.
A PSI Training Course - Practical Approaches to Designing Adaptive Clinical Trials
This hands-on course will provide a deep dive into 4 software packages used to design adaptive clinical trials.
The course will start by providing a general overview of adaptive designs, explaining the different type of adaptations possible and the benefits of each design. Following this, participants will be given the opportunity to have a go at designing trials in R (using RPACTS), EAST, FACTS, and nQuery.
PSI Training Course - Bayesian Practical Course using R and SAS
This practical training course will give a deep dive into performing Bayesian analyses in R and SAS. It is aimed at statisticians who need to be able to conduct Bayesian analyses as part of their day to day work. By the end of the course participants will be able to conduct their own analyses.
This webinar will address operational issues of paramount importance within the healthcare industry with a view to using statistics for the benefit of patients. In attending this webinar, you'll hear more about work being conducted to address some operational issues we face in the health care industrys e.g. patient rectuitment, drug supply and meeting NHS 18 week targets.
PSI Toxicology SIG workshop – 16th and 17th March 2020
The Toxicology SIG provides a forum for statisticians working in regulatory/investigative toxicology, as well as most other pre-clinical areas, to discuss issues and interact with one another.
This 1.5-day workshop will involve approximately 20 statisticians, focusing on discussions around “best practice” in the statistical analysis of various data types.
The afternoon of Day 1 will include a 4.5 hour Bayesian training course focused towards applications in toxicology/pre-clinical, provided by Prof. Dr. Katja Ickstadt and is included in the workshop fee.
The cost will be £270 including VAT per delegate, inclusive of food and one night’s accommodation (and the training course). The workshop is being held at the Crowne Plaza Hotel, Heathrow.
The agenda and topics that will be discussed are yet to be finalised, but please get in touch with firstname.lastname@example.org if you have suggestions. Full details will be circulated in the coming weeks.
This course is aimed at Statisticians and Programmers experienced in SAS, but little or no experience with R.
An Introduction to R studio and the R language, statistical graphics, programming statistical models, simulations and more…
Non-proportional hazards and applications in immuno-oncology
Designs of clinical trials with time to event primary endpoints usually rely on hazards being constant over time. A major challenge in immuno-oncology is the delayed onset of benefit with such therapies and the presence of non-proportional hazards. The impact of this needs to be accounted for in sample size calculations, analysis methodology and reporting. At this meeting, we will examine possible strategies to handle such features, which may not be fully known when the trial is initiated.
The ITIT course will take 25 delegates new to the industry on a complete drug development experience from discovery to marketing. They will visit 6 companies from October 2020 to July 2021 to learn about 6 topics from experts in their field. The ITIT course will have 6 sessions in continental Europe and 3 - 4 sessions in the UK. It promises to be a truly memorable course.