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11 June 2020

How can the Estimand Framework Help Us to Address Impacts of the COVID-19 Pandemic? This webinar focused on how the estimand framework can help us to pose and answer clinically relevant questions in the light of the COVID-19 pandemic. This session brings together colleagues from the EFPIA/EFSPI estimand implementation working group and the Estimands in Oncology ESIG.

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Chrissie Fletcher, David Wright, Kaspar Rufibach.

We will consider impacts on ongoing case studies in chronic obstructive pulmonary disease (COPD) and oncology. The COVID 19 pandemic causes disruption of healthcare systems leading to inaccessibility of sites, treatment interruptions and discontinuations, missed or delayed visits, use of unexpected concomitant medications and deaths. The scale of the impact will vary depending on our target population, therapeutic area and the timing of study recruitment relative to the course of the COVID-19 pandemic.

We will show how the estimand framework helps us to:
• revise the treatment effects of interest considering all five estimand attributes including accommodation of unexpected intercurrent events;
• propose sensitivity analyses to explore robustness of departures from assumptions (including missing data assumptions);
• propose supplementary analyses to more fully investigate and understand the trial data.

Our case studies will illustrate how pre-specified estimands are impacted by the COVID-19 pandemic, and how methods for estimation including sensitivity analyses may need to be reconsidered to address missing data issues.

11 June 2020

The 2019 Prize winners were; Mike Smith (Pfizer) for excellence in research around population modelling in drug development and pioneering practical Bayesian methods with drug development in the context of optimising decision making within trials and modelling dose response with pharmacokinetic/pharmacodynamic modelling and Graeme Archer and Jacquie Christie (GSK) for their work on Quantitative Decision-Making for clinical development, which was deemed to be at the cutting edge of revolutionising data driven decision making within the industry.

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Mike Smith, Jacquie Christie

Mike Smith (Pfizer) talks on innovation, play and failing. What is innovation? How do I innovate? Is it a skill that I can learn or improve on? In this presentation I will attempt to define what I mean by innovation and break down what I consider to be drivers of innovation. Some of these are things that you CAN definitely work on. It is true that some are environmental or cultural but even these are things that you can influence or change. I will illustrate how these elements have come together to help me and my colleagues deliver on projects, innovate and break out of “tried and tested” methods, including those cited in my RSS/PSI Statistical Excellence in the Pharmaceutical Industry award.

Jacquie Christie (GSK) talks about Quantitative Decision-Making for Clinical Development. Low productivity and late-stage attrition are well-known pharmaceutical R&D problems; one cause is poor decision-making at key milestones. Failure to consider the impact of current design choices on future investment options increases uncertainty when the decision-point arrives, and consequently increases the risk of a wrong decision. This talk will outline an approach to quantitative decision-making in a completely Bayesian setting. Prior distributions are used to evaluate proposed study designs and decision rules against not only the probability of success of the current study, but that of the subsequent study or set of studies. Termination and progression criteria and associated risks are then clear, allowing more informed decision-making. The approach is applicable to all phases of R&D.

10 June 2020

Alexander Schacht, Mark Baillie, Daniel Saure, Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Rachel Phillips, Markus Vogler, David Carr and Steve Mallett.

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This month the discussion is about visualizations of the satisfaction data using cumulative distribution functions, a tree plot, staggered bar plots, a power BI dashboard and two interactive funnel plots using plotly and RShiny. These examples nicely demonstrate that different displays support different purposes. Some visualizations are telling a story about the data and others help to explore the data. Presented by Bodo Kirsch.

10 June 2020

Inferring what is likely to be true based statistical analysis of data is a very difficult task and certainly not as easy as computing a p-value for declaring H0 to be true or false based on an arbitrary cut-off value. This session will include the leaders from the two most prominent statistical societies in the world – The RSS (Deborah Ashby) and the ASA (Ron Wasserstein) – and moderated by Stephen Ruberg. Listen to their perspectives and sharpen your statistical thinking.

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Stephen Ruberg, Deborah Ashby, Ron Wasserstein. 

Inferring what is likely to be true based statistical analysis of data is a very difficult task and certainly not as easy as computing a p-value for declaring H0 to be true or false based on an arbitrary cut-off value. Much has been written over the last eight decades on hypothesis testing, p-values, Bayesian inference with the conversations (or sometimes acrimonious debate) continuing. This session will include the leaders from the two most prominent statistical societies in the world – The Royal Statistical Society (Deborah Ashby) and the American Statistical Association (Ron Wasserstein) – and moderated by Stephen Ruberg. Listen to their perspectives and sharpen your statistical thinking. This session of the 2020 PSI Conference Webinar Series was kindly sponsored by Astrazeneca.

10 June 2020

Christen Gray, Kirsty Hicks and Elizabeth Williamson each speak on their work related to real world data. Topics include Comparing the impact of unmeasured confounding due to selection bias in external comparator studies using RWD, Advanced Analytics of Digital Data: A focus on sensor data, and how we can use RWD to emulate trials.

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Elizabeth Williamson, Christen Gray, Kirsty Hicks.

Elizabeth’s talk will explore different approaches to trial emulation using RWD using two examples both using data from the UK Clinical Practice Research Datalink (CPRD), a large database of UK primary care records. In the first example, data from the CPRD was used to emulate a trial of macrolide antibiotics on all-cause mortality prior to the relevant trial being conducted. In the second example, data from CPRD was used to generalise the results of the TORCH COPD trial to a patient group less represented among the original trial participants – those with mild COPD.

Christen will speak about augmentation of the control arm of a randomized controlled trial (RCT) with external data, which has been proposed in recent years where standard RCTs face enrolment restrictions. Using real-world data (RWD) for external controls is a natural next step. However, in order to do so, there need to exist accessible methods for researchers which can minimize the risk from unmeasured confounding in this setting. Bayesian borrowing methods, which discount the external data dependent upon the similarity of the outcomes to the internal controls, have been applied when the external data is prior control arms of clinical trials. The simplest of these approaches is the power prior. In using RWD, greater variation in the underlying population and measured variables is expected.

Finally Kirsty speaks on digital data and how it can be used to collect information on sleep patterns, respiration rate, step count and continuous monitoring of heart rate and energy expenditure. Collecting data through digital devices also increases patient engagement and can provide real time compliance monitoring. The regulations for use of digital technologies in clinical trials are still evolving, and current recommendations for the analysis of such data are limited. As a statistician initial questions that spring to mind include ‘How can this volume of data be analysed or represented visually?’ Statistical methods that can be applied to this data are under investigation and this presentation will introduce some of these. This session of the 2020 PSI Conference Webinar Series was kindly sponsored by Amgen.

09 June 2020

This session covers the essential principles that statisticians need to be aware of regarding clinical data and patient privacy (e.g. GDPR) and how data can be re-used responsibly.

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Rebecca Sudlow, Janice Branson, Katherine Tucker.

This session covers the essential principles that statisticians need to be aware of regarding clinical data and patient privacy (e.g. GDPR) and how data can be re-used responsibly. What has changed? Why is data now an asset? Over the last decade we have seen a massive change with regard to data transparency from clinical trials - increase in sharing through CT.gov, EUDraCT as well as many companies and institutions actually allowing access to individual level patient data upon request from researchers. More recently EMA and other Health Authorities have rolled out policies to make documents such as anonymised clinical study reports publicly available. Within Pharma companies we see many initiatives to try to make better use of the wealth of data the companies have and even initiatives to leverage data across companies and from health records in an attempt to have smarter, shorter and more ethical drug development programs. This is all needs to be done taking into account new legal requirements coming from GDPR for example as well as working in the framework of informed consent or anomymizing the data or even exploring newer areas like synthetic data.

09 June 2020

PSI presents 4 very different talks from 4 statisticians still lucky enough to be deemed young in their careers. Jack Keeler will speak on enrichment designs with survival data; Ruth Owen on methods to evaluate the benefit-risk trade-off in individual patients; Inês Reis will give a young statistician’s guide to regulatory statistics and Georgios Nikoladis will talk about Borrowing strength from indirect evidence in HTA. A session not to be missed!

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Jack Keeler, Ruth Owen, Inês Reis, Georgios Nikolaidis.

Jack Keeler
In modern medicine, it is becoming more apparent of patient and disease heterogeneity, and this can have consequences in clinical trials that do not take this into consideration. For example, Ellis and Taylor (2002) mention that ACE inhibitors are less effective in African American patients than White patients when treating heart failure. Many trials do not have sufficient information from early phase trials to definitively predict treatment effects for differing subgroups and some trials explore subgroups as exploratory endpoints, but exploratory conclusions are not always considered concrete. A solution for dealing with the differing biomarkers is to use adaptive trial designs, namely, enrichment designs. Survival trials may benefit greatly from such adaptations as survival trials are some of the longest trials conducted. Using Magnusson and Turnbull’s (2013) Group Sequential Design incorporating Subgroup Selection (GSDS), a trial can use the first interim analysis as a means of discontinuing treatments for subgroups who are not experiencing the desired effect from the treatment. This is making the trial ethically sound, as patients in certain subgroups are saved from ineffective treatments. GSDS does not follow the same boundary calculation rules as normal group-sequential designs, due to the selection criteria, but the conduct of the trial is very similar, making it feel familiar to statisticians. Enrichment trials are currently rare, so an example trial, using simulated survival data, will demonstrate how these trials could perform in reality, and examine the advantages and disadvantages of such designs.

Ruth Owen
Introduction: For many RCTs the efficacy of a new treatment is accompanied by safety concerns. While overall results may demonstrate a favourable risk-benefit trade-off there may be individuals where the harm outweighs the benefit. Methods: We describe methods to predict the individual patient’s absolute benefit and risk based on multivariable models using patient baseline characteristic. Taking account of the relative clinical importance of the respective benefits and harms we develop an algorithm for clinical use whereby rapid decisions can be made on the preferred treatment strategy for each individual patient. Results: We illustrate this approach with findings from three major cardiovascular studies: 1) the SPRINT trial of intensive versus standard blood pressure lowering, where ischaemic benefits are accompanied by some major adverse events 2) the TIMI 50 trial of vorapaxar versus placebo post-myocardial infarction, where ischaemic benefits are accompanied by increased risk of major bleeding 3) a meta-analysis of 7 studies in coronary patients receiving a stent, with the goal of identifying which patients at high risk of bleeding need a shorter duration of effective dual anti-platelet drugs. Conclusions: Our findings illustrate how quantitative methods can help identify those individual patients for whom the risk of harms outweighs the benefits of a new treatment.

Inês Reis
Successful and safe devolvement, licensing and marketing of medicines cannot happen without intense cooperation and dialogue between regulators and pharmaceutical companies. On the regulatory side, the Medicines and Healthcare products Regulatory Agency (MHRA) has decades of experience in medicines and medical devices regulation, during many of which statisticians have been deeply involved. Not only at the level of licensing of medicines, but also in the pharmacovigilance and medical device areas, statisticians play an important role in the Agency's activities, not forgetting their involvement in real-world data collection and analysis (CPRD) and characterisation, standardisation and control of biological medicines (NIBSC). In this talk you will learn about the MHRA, how we work, and the statistician's roles in the system, as well as some hints of current hot topics in regulatory statistics such as estimands and real-world data. You will also discover the types of interactions that can be held with regulators at the UK (MHRA) and European (EMA) levels, the different types of regulatory procedures and how statisticians from both sides of the table can contribute to such dialogue, ultimately helping their companies navigate through the regulatory system more smoothly.

Georgios Nikolaidis
Sparse relative effectiveness evidence is a common problem in Health Technology Assessment (HTA). For example, evidence on a paediatric population may be limited. Usually, in HTA, such indirect evidence is either included by ignoring any differences (`lumping`) or is completely disregarded (`splitting`). However, more sophisticated methods exist in the literature which, rather than `lumping` or `splitting`, impose more moderate, perhaps more appropriate, degrees of information-sharing. We developed network-meta analytic methods for the combination of, aggregate-level, binary, direct and indirect evidence. These can be categorized into functional-, exchangeability-based, prior-based and correlation-based relationships. The estimates produced with each method were subsequently used in a case-study that evaluated the cost-effectiveness and value of information of intravenous-immunoglobulin (IVIG) for adults with severe sepsis and septic shock.

08 June 2020

Deborah Ashby. In 2020 we celebrate the bicentenary of Florence Nightingale’s birth and the need for statistical and data skills to improve health show no signs of abating. What lessons can we draw from Florence Nightingale to shape the future of statistics?

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In this talk Deborah Ashby (Director of the School of Public Health at Imperial College London and President of the RSS) will talk about Florence Nightingale, in the year that we celebrate the bicentenary of her birth. Florence, best known as the Lady with the Lamp, is recognised as a pioneering and passionate statistician. She had argued successfully with her parents to be allowed to study mathematics, and later nursing, and then combined these skills to use data imaginatively and powerfully to improve health. As we celebrate the bicentenary of her birth, the need for statistical and data skills to improve health show no signs of abating. What lessons can we draw from Florence Nightingale to shape the future of statistics?

This session of the 2020 PSI Conference Webinar Series was kindly sponsored by Veramed.

13 May 2020

Alexander Schacht, Mark Baillie, Daniel Saure, Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Rachel Phillips, Markus Vogler, David Carr and Steve Mallett.

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The visualizations in May show survival data of a 4-arm trail with subgroup information. There are different enhancements of the standard KM plot shown as well as a heat map approach. The visualizations also underline the importance of the right coloring and shading. Presented by Lorenz Uhlmann

28 April 2020

Jackie Moynihan

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Jackie Moynihan.

Given the current situation, pretty much everyone is working remotely from home. Some people are used to working remotely either on a regular or full-time basis this, whilst for many this is a new experience.

Remote working, whether chosen or forced, has pros and cons for the company, manager and the statistician. Based on over 15 years’ experience working from home as a contractor and more recently as a manager of home-based statisticians and programmers, this Webinar will give some guidance for both managers and individuals. Some technical advice will be covered but the focus will be on how to recruit and manage remote statisticians as well as some strategies for the day-to-day challenges of being home-based.

This webinar is aimed both at people who are used to working from home as well as at those are being asked to work from home for the first time. Not everyone will have an ideal home-working scenario and may also be juggling family needs at the same time. Areas where we need to adapt from the ideal will be discussed.

23 April 2020

Andy Grieve, Haolun Shi and Daniele De Martini

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Andy Grieve, Haolun Shi and Daniele De Martini.

Watch this Journal Club webinar on “Progressing II Data into Phase III”. Haolun Shi (Simon Fraser University, Burnaby) and Daniele De Martini (Università degli Studi di Milano‐Bicocca, Milan) present their recent work. The webinar will be chaired by Andy Grieve (UCB).

Haolun Shi; START: single‐to‐double arm transition design for phase II clinical trials
Authors: Haolun Shi, Teng Zhang and Guosheng Yin 
Pharmaceutical Statistics, 2020;1–14.
Access the slides here.

Daniele De Martini; Empowering phase II clinical trials to reduce phase III failures
Authors: Daniele De Martini
Pharmaceutical Statistics. 2019;1–9. 
Access the slides here.
 

 

23 April 2020

Lucy Rowell, Chrissie Fletcher & Nigel Howitt

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Lucy Rowell, Chrissie Fletcher & Nigel Howitt - Chrissie and Nigel share their thoughts on how PSI has helped them to be successful in their Careers, and what PSI has to offer to yourself as an individual or as a line manager.
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