Welcome to The Effective Statistician Conference 2024

The 2023 Effective Statistician Conference was certainly a success with more than 800 participants.

Now, the 2024 Effective Statistician Conference is looking at a much more successful result for everyone who wants to know more about effective statistics and its extensive use in making a progressive and productive society.

The best thing about this conference is that it is completely FREE OF CHARGE!

With top speakers included in the program, you are surely going to get the best out of your time and improve your perception of progressive statistics.

With Guest Speakers Anja Schiel, Andy Grieve and many other respected statisticians in the industry,

You are surely going to get the best out of this conference all for FREE.

Register Today and Secure Your Spot Fast.

SPEAKERS

Roles you need to fulfill to succeed that are not in your job description
Abstract: The more experience and seniority you get, the more your success depends on roles you need to succeed in, that rarely get mentioned in your job description. I’ve talked with many experienced people, who don’t move forward because they have a lack of understanding of their roles or not the skills to successfully master them. At every level in your career, you need to work on these roles and the more you progress in your career, the more important these roles get. Of course, you have the role of running your “production”. All the deliverables you promised need to be delivered on time, on budget and with quality. This leads to another role: you need to have an excellent overview of your “finances”. If you want to increase your or your team’s impact and want to stay relevant, you also need further roles: marketing, sales, and R&D. Yes – even if you work as an employee within a bigger organisation, you need to market yourself and your products/services. And you need to “sell” them. If you never innovate, you will easily become redundant or replaceable at one point. To avoid this, you need to invest in your own R&D. And there are further roles, you might not be aware of or neglect. During my presentation at the effective statistician I will summarize various roles and dive deeper in few of them.

Are Estimands and PICOs family or foes?
Abstract: With the implementation of the HTAR (Regulation on health technology assessment) starting in January 2025, the PICO has become a household term, yet many wonder how it relates to the Estimand. And not only is there uncertainty on what this PICO is all about, there is also uncertainty around how they will be constructed and what the consequences potential misalignment between study aims (Estimands) and HTA requirements (PICOs) will be. In this session the intention is to clarify the relationship these two siblings have and why both are rather complimentary and not contradictory. We will explore how PICOs are developed, why there are usually several (but not > 100 as often stated by some pessimists) and how these requirements can be met methodologically.

Entrepreneurialism and the Effective Statistician
Abstract: The stereotypical view of a statistician sees one sat in an office, with a closed door, crunching the numbers. If that were true the ability of such a statistician to influence their environment would be practically non-existent. Half a century ago statisticians from both the quality and management worlds argued that in order for statisticians to be effective they had to be entrepreneurial. In this talk I look at some examples from my own experience of how the entrepreneurial spirit has helped me to further both my influence and my career.

Captivity vs. The Wild: Why Integrated Evidence Plans are Needed and How Statisticians Can Make an Impact
Abstract: Statisticians working in any field really appreciate the importance of a well-devised research question. It makes the design of experiments, collection or re-use of the right data, and application of appropriate analysis methods far more effective. In regulatory submissions of new pharmaceutical products, there are a large number of guidance documents and standard operating procedures from health authorities and individual companies which standardize the way many research challenges are approached. However, when it comes to planning for launch of new medicines, anticipating evidence gaps for clinical practice, and designing additional studies to address those gaps, many
statisticians still find themselves operating in a whirlwind of confusion (new and diverse stakeholders, questions that were not addressed in the regulatory setting, different regulations and even fewer standard procedures, etc). It is like the difference between studying animals in captivity versus the wild. The questions are very different, evolve over time, and may require different means of solving them. The integrated evidence plan is a concept that exists in most large companies and builds directly on the clinical development plan to document the evidence gaps, strategic needs, and tactics to facilitate the appropriate use of new medicines to benefit patients in clinical practice globally. Statisticians and data scientists: do not assume that what has already been done for regulatory approval will carry your product all the way to patients. Engage, be curious, and be a part of new solutions!

A Gentle Introduction to Structural Equation Modeling
Abstract: Structural equation modeling (SEM) is a multivariate statistical approach that combines features of regression analysis with features of measurement theory and confirmatory factor analysis. SEM allows modeling complex cross-sectional and longitudinal relationships between observed and latent “true score” variables that are corrected for random measurement error. In this presentation, I provide a gentle introduction to SEM and demonstrate its advantages for empirical studies that deal with complex variable relationships, including longitudinal and multimethod research.

SEM allows modeling complex cross-sectional and longitudinal relationships between observed and latent “true score” variables that are corrected for random measurement error. In this presentation, I provide a gentle introduction to SEM and demonstrate its advantages for empirical studies that deal with complex variable relationships, including longitudinal and multimethod research.

What to expect when outsourcing NMAs?
Abstract: In the rapidly evolving landscape of healthcare analytics, Network Meta-Analyses (NMAs) have become essential tools for comparative effectiveness research. Outsourcing NMAs can be an attractive option for organizations seeking to leverage specialized expertise and advanced analytical capabilities. However, navigating the outsourcing process can present a unique set of expectations and challenges. This talk aims to provide a roadmap for organizations considering outsourcing NMAs. We will discuss the critical factors to consider when selecting a service provider, including expertise in biostatistics, familiarity with HTA compliance, and a proven track record in advanced statistical methodologies. Furthermore, we will delve into the intricacies of managing communication and project timelines. Attendees will gain insights into optimizing collaboration with external teams to ensure high-quality results, efficiency in delivery, and alignment with project objectives. Emphasis will be placed on understanding the full spectrum of the outsourcing relationship – from initial engagement to the delivery of actionable insights. This presentation is designed to arm decision-makers with the knowledge to effectively manage their NMA projects in the context of outsourcing, ensuring that expectations are not only met but exceeded.

The Effective Statistician and the Leadership: Friend or Pitfall?
Abstract: The talk summarizes the requirements for an effective statistician. Using feedback from team members, there is a wish list of what the perfect statistician is capable of. On top of that there are leadership skills which are in growing demand. In this talk I will explain the balance that every one of us needs in the pharmaceutical industry.

Principles, Priorities and Productivity – Why Learning to Say “No” Can Make You a Better Statistical Leader
Abstract: As statisticians and data scientists, we are trained to support collaborators and customers by providing our expertise in study design, analysis methods and data interpretation. We thrive and gain fulfillment by guiding our business partners through the complexities of our science. Our innate desire to serve and please makes “yes” our default response to a myriad of requests: Can you perform these additional analyses? Do you have time to help with this extra study? Can you deliver that report one week earlier? We succeed by doing for and doing with others. Or do we? One of the common questions I get when teaching and advising developing leaders is “Where do you find time to spend on personal development?” The answer is simple, but challenging in practice: Principles and Priorities. These two things guide behavior, establish boundaries, and keep us focused on the most critical business needs – those that will drive productivity and deliver value for our organizations. In this talk, I will discuss the importance of learning to say “no”, how to build your principles, some simple tricks to prioritize work, and how, in the long run, learning to say “no” will lead to greater business impact and personal advancement.

Agile Pharma: Implications of the Dawn of The Data Science Era
Abstract: It is no secret that, like all businesses, pharmaceutical companies struggle to keep up with the dizzying pace of innovation, process change and technology trends. Pharma culture is understandably infused with higher than average doses of risk aversion, which amplifies these challenges. The result is a cognitively dissonate urgency to access an ever-expanding menu of new skills and abilities while bound by traditional, tried and true approaches and structures. The increasing demand for greater data science skills and abilities throughout the organization, even beyond biometrics, brings this contrast into sharp relief. Sheila Mahoney of LifeSciHub, LLC presents how “Future of Work” theory can increase pharmaceutical agility, efficiency and competitive fitness.

Futility analyses – a strategic tool in drug development and not at all futile!
Abstract: The failure rate of Phase 3 clinical trials remains high, at least in certain indications. A
strategic tool to derisk clinical trials are futility analyses, i.e. an interim analysis with the option to stop a trial because there is little hope it would be statistically significant if run to the end.
While the decision to stop for futility in a specific trial might be the wrong one (a false-negative which we would never learn about) I will illustrate how the systematic use of futility interims pays off on a portfolio level by bringing down the average number of patients or events per trial, potentially dramatically. When statisticians propose to implement a futility analysis in a clinical trial they often meet resistance from trial teams and senior management. I will review arguments that we often hear “against” futility analysis and illustrate that many of these are either myths, outright wrong, or too much focused on the trial at hand and not the drug development enterprise or the patient. This will lead me to share some tips and tricks how statisticians can strategically navigate the discussions around futility analyses. If time permits I will share a few pertinent examples. Expect some spicy quotes!

Want to make precision medicine a reality? A global collaboration is needed!
Abstract: Biomarkers play a bigger and bigger role in drug development, but this is no news to anyone. The term biomarker being widely used, one could think that its meaning is well-understood. But it is not always the case. Actually, what is a biomarker?
Precision medicine (PM) randomised controlled trials (RCTs) aim to demonstrate differential clinical efficacy for specific endophenotypes. Such approaches rely on well-powered biomarker-defined subgroup analyses. The identification and enrollment of eligible patients, based on a biomarker of interest, necessitate the screening of a considerable number of prospective patients.
Many sites participate in multiple studies simultaneously. The objective of this work was to assess the potential impact a PM study could have towards the statistical power, and the recruitment times, of other non-PM studies at sites that seek to recruit patients into both PM and non-PM studies.
For decades, the pharmaceutical industry has tended to develop drugs at a drug-level, requiring competing for patients within and between organisations. This approach poses a challenge to the realisation of precision medicine.
To surmount this obstacle and streamline patient recruitment, it is imperative to enhance information-sharing and collective decision-making on a global scale. The establishment of an industry-wide consortium, facilitating access to comprehensive patient information through broad consent forms, could revolutionise drug development. This collaborative framework would enable stakeholders to transcend organisational boundaries, fostering a more holistic approach to drug development and ultimately advancing the implementation of precision medicine.

Statistical Intrapreneurship 101

Abstract: In today’s dynamic landscape, where technological advancements, novel tools, and evolving methodologies constantly reshape our professional environment, adapting becomes essential. As statisticians and data scientists, we wield analytical thinking, deep domain knowledge, and expertise in intricate designs and methodologies. Our resilience and determination drive us to persist even when faced with challenges.

VUCA—Volatility, Uncertainty, Complexity, and Ambiguity—defines this ever-changing world. But within this landscape lies immense potential for career growth, organizational impact, and personal visibility. By harnessing our existing skills and acquiring new ones, we can navigate VUCA to our advantage.

In my presentation, I will explore fundamental principles for achieving statistical intrapreneurship within a global organization. We’ll uncover strategies to create tangible impact, enhance visibility, and drive our careers forward. Join me as we unlock the power of statistical entrepreneurship in an ever-evolving business ecosystem!

Rank-Based Procedures in Factorial Designs: Hypotheses about Nonparametric Treatment Effects
Abstract: Existing tests for factorial designs in the nonparametric case are based on hypotheses formulated in terms of distributions. Typical null hypotheses, however, are formulated in terms of some parameters or effect measures, particularly in heteroscedastic settings. In this talk, we extend this idea to nonparametric models by introducing a novel nonparametric ANOVA-type-statistic based on ranks which is suitable for testing hypotheses formulated in meaningful nonparametric treatment effects in general factorial designs. This is achieved by a careful in-depth study of the common distribution of rank-based estimators for the treatment effects. Since the statistic is asymptotically not a pivotal quantity we propose different approximation techniques, discuss their theoretic properties, and compare them in extensive simulations together with two additional Wald-type tests.
An extension of the presented idea to general repeated measures designs is briefly outlined. The proposed rank-based procedures maintain the pre-assigned type-I error rate quite accurately, also in unbalanced and heteroscedastic models. A real data example illustrates the application of the proposed methods.

Recruitment in clinical research – cost factor or game changer?
Abstract: Our company Clivolution is a sustainable and value-based personnel consultancy and recruitment agency for clinical research. Since last year, we have also been running a cooperation with Alexander Schacht called Clivoffective. With Clivoffective, we focus on the placement of statisticians, programmers and data analysts and advise companies on selection and optimal team composition. In our presentation, we will talk about why it makes sense and is advantageous for both companies and candidates to work with an agency. We talk about the trend towards specialization and networking, we talk about efficiency, sustainability and values, as well as current trends in job search.

Statisticians can significantly influence drug development, do you know how to add value?
Abstract: Statisticians have many opportunities to positively influence drug development. Examples include using innovative designs to accelerate evidence generation, developing disease prediction models to inform disease area strategies and using automation to deliver results at pace. Technology advances and digital healthcare are transforming ways of working, with a big focus currently on exploring how best to employ AI/ML approaches such as ChatGPT. These elements and increased access to diverse data sources including RCTs, RWE and digital endpoints is enabling statisticians to be seen as strategic drug development partners.

The skills required to be an effective statistician in NextGen R&D continues to evolve, and it is unrealistic to expect every statistician to be an expert in everything. Being able to adapt to change, employ flexible working practices and build a diverse mix of competencies are key enablers for success. In addition to nurturing a strong foundation of technical skills, statisticians who aspire to be effective leaders, have confidence to challenge and influence stakeholders and possess strong communication skills, will create value.

Chrissie will share her perspectives on how the role of statisticians has, and will continue, to change, and highlight the importance for making continuously learning as part of core day-to-day activities. She will reflect on key learnings from her 30+ years of Industry experience and offer advice, hints and tips.

On the True Impact of Screening Endoscopy on Colorectal Cancer Incidence
Abstract: Measured colorectal cancer (CRC) incidence in randomized screening endoscopy trials is biased by inclusion of not-preventable preclinical cancers already present at baseline.
We replicated NordICC, a key trial on prevention by screening endoscopy, with and without inclusion of prevalent cancers. We found that the share of prevalent cancers exceeds 50% in initial years after randomization in both groups. The true impact of screening endoscopy is underestimated by 80% in the first years after screening, and still by 40% after 10 years of follow-up. The preventive effect of screening endoscopy is likely much stronger than reported. Published findings of randomized screening trials underestimate the true preventive effective of screening endoscopy even after 10 year or longer follow-up.

Beyond Numbers: Biostatisticians as Catalysts for Change in Drug Development
Abstract: Biostatisticians are increasingly recognized not just as data analysts, but as strategic leaders capable of significantly influencing drug development pathways. This session will illuminate the transformative role biostatisticians can play when they acquire and enhance soft skills, such as effective communication, to ensure their voices are heard in critical decision-making processes. Emphasizing the importance of developing business acumen, it will explore how biostatisticians can better understand and navigate the broader context in which statistical analysis impacts drug development. The talk will also highlight the unique position of biostatisticians, owing to their training and expertise, in leading the integration and application of AI and ML technologies in drug development. By transcending traditional roles, biostatisticians are poised to become indispensable strategic partners in the journey of drug development, embodying a transformative role as key drivers of change in an industry at the forefront of technological advancement.

Trust me, I’m a statistician
Abstract: The theme for the 2024 World Economic Forum is “Rebuilding Trust”, focusing on “the fundamental principles driving trust, including transparency, consistency and accountability”. But (how) can professional statistics, (how) can we as professional statisticians contribute to rebuilding trust in a world of misinformation, disinformation, and statistical illiteracy?

Why We Need to Improve Software Engineering in Biostatistics
Abstract: Programming is ubiquitous in applied biostatistics, and most statisticians know a programming language – yet software engineering is still neglected as a skill and undervalued as a profession in pharmaceutical statistics. Why is this a problem? Importantly, we run the risk of wrong decisions when relying on code that we wrote ourselves without any code review by other statisticians. When transitioning over undocumented code to successors or other teams, we cannot be sure that they can even use, yet maintain it in the future at all. Also, whether they can reproduce results we produced earlier is a matter of luck. If we later need to add features to our code, and don’t have sufficient tests in place, we will undoubtedly introduce bugs and alter the program behavior without knowing it. Finally, if we need to implement new statistical methods for analyses submitted to regulators, we need to have appropriate software validation pipelines in place, which will demand well developed and tested code. What can we do about it? First and foremost, we must become aware of the problem. Second, we need to take software engineering seriously, starting from education in basic software engineering skills – across schools, universities, and during the work life. Establishing dedicated software engineering teams within academic institutions and companies can be a key factor for the establishment of good software engineering practices and catalyze improvements across research projects. Providing attractive career paths is important for the retainment of talents. Finally, collaboration between software developers from different organizations is key to harness open-source software efficiently and optimally, while building trusted solutions. We illustrate the potential with examples of successful projects.

Driving change as a statistician – experiences from a case study on data visualization
Abstract: Driving change inherently meets resistance. As statisticians we often want to convince other departments on embracing new concepts such as Bayesian methods, adaptive designs, comparative rather than single arms studies, and many more. Many of these concepts take decades or longer to become broadly accepted. In this discussion between Beth Manning – an experienced change agent – and Alexander Schacht, you will hear about a case study on how both increased the adoption of data visualization in a mid-sized pharma company. You will learn about the obstacles they faced, the resources they leveraged and some surprising strategic moves they made to drive change.

The conference is sponsored by:

- - - Sanevidence GmbH
      Sanevidence GmbH is the company behind The Effective Statistician and all its brand. Our goal is to enable statisticians, data scientists and programmers in healthcare to become the best of themselves and achieve their career goals. We provide training on both methodological and people skills in partnership with many leading experts.
  - - MArS Market Access & Pricing Strategy GmbH
      Are you looking for a hands-on consultancy with a strategic vision for the D-A-CH region? MArS has years of experience in planning, filing and negotiating in the three D-A-CH countries and will lead you successfully with your product to your commercial objective!
  - - LifeSciHub Small/Micro-Business Community
      The LifeSciHub Community is comprised of independent expert small, micro businesse. These experts have intentionally decoupled from the corporate ladder, usually at the Director or VP level, in order to practice their expertise as small, independent businesses. The range of expertise is vast- every aspect of drug development requires highly specialized skills, and the LifeSciHub small business community has them in abundance: biometrics, clinical operations, patient engagement, produce launch, CMC, supply chain, clinical contracts, regulatory, pharmacovigilance, computational drug modeling and simulation, RWE, HEOR, medical writing, eTMF. Some “solopreneurs” seeing process or technology gaps, have even created software products to further expedite innovation.
  - - EpiStat – epidemiology, statistics and real world evidence
      Epistat is a research consultancy company specialized in health data sciences and real-world evidence to support pharmaceutical companies throughout all phases of drug development.
      info@epistat.se
      anders.berglund@epistat.se
    - Smart Data Analysis and Statistics
      Smart Data Analysis and Statistics B.V. is at the forefront of biostatistical innovation, expertly converting real-world data into compelling evidence compliant with Health Technology Assessment (HTA) standards. Our commitment to cutting-edge analysis methodologies ensures that our clients are equipped with advanced, scalable solutions that meet the rigorous demands of the healthcare industry.
  - - Clivoffective
      The key to achieving goals in Life Science companies is always people. Clivoffective brings together Life Science companies and talented individuals in the fields of statistics and data science. By doing so, we close open positions for the benefit of the companies all while considering, nurturing, and building on individual talent strengths through our extensive expertise in statistics.
  - - The Effective Statistician Academy
      The Effective Statistician Academy offers four distinct areas of training: Leadership, Innovation, Knowledge, and Excellence. Each area features expert-led courses that are designed to help you gain the skills and knowledge you need to succeed in your career. Whether you’re looking to take your leadership skills to the next level or stay up-to-date on the latest innovations in the field, the Academy has you covered.

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