Utility values in health technology assessments: a statistician's perspective

This paper provides an introduction to utilities for statisticians working mainly in clinical research who have not had experience of health technology assessment work. Utility is the numeric valuation applied to a health state based on the preference of being in that state relative to perfect health. Utilities are often combined with survival data in health economic modelling to obtain quality‐adjusted life years. There are several methods available for deriving the preference weights and the health states to which they are applied, and combining them to estimate utilities, and the clinical statistician has valuable skills that can be applied in ensuring the robustness of the trial design, data collection and analyses to obtain and handle this data. In addition to raising awareness of the subject and providing source references, the paper outlines the concepts and approaches around utilities using examples, discusses some of the key issues, and proposes areas where statisticians can collaborate with health economic colleagues to improve the quality of this important element of health technology assessment. Copyright © 2014 John Wiley & Sons, Ltd.     

Providing Consulting Experiences Through Role Playing in a Graduate Statistics Course

An effective method for improving the communication skills of graduate students in statistics and biostatistics is to provide consultations with non‐statistical researchers. Unfortunately, those experiences can be difficult to arrange or occur too infrequently to be reliable. The current study sought to help students develop both written and oral communication skills within an existing graduate biostatistics course by having students partake in role‐playing consultations. Though the class size was small, the students felt these activities helped improve their oral and written communication skills, and made them more aware of a biostatistician's role in consulting. There was also modest improvement in the students perceived function as a consulting biostatistician. Simulated consultations can be an effective educational tool for promoting the development of soft skills necessary for developing successful statisticians, can be implemented in existing courses, and do not require reliance upon external collaborators. Embedding these types of exercises within an existing curriculum can also be a cost‐effective alternative for programs that do not have formal consulting training.     

Bill Cochran: His Contributions to Medicine and Public Health and Some Personal Recollections

There is a tremendous need in our technological society to train statisticians for all sectors of education, government, and industry. Because statistical training has largely been restricted to graduate schools, the profession is losing many good students to other fields of study. Members of the statistics community are encouraged to reach out to high-school students and undergraduate students to increase the awareness of statistics as a scientific field of study and as a professional career. The ASA Council of Chapters has recently completed a slide presentation entitled “Statistical Science: The Profession,” which was professionally developed to aid this endeavor. In addition, high-school teachers, high-school counselors, and professors of mathematics and science education are identified as important audiences for hearing this message and for broadening general public awareness of what our profession has to offer.     

Regression Using Pairs vs. Regression on Differences: A Real-life Case Study for a Master's Level Methods Class

When teaching regression classes real-life examples help emphasize the importance of understanding theoretical concepts related to methodologies. This can be appreciated after a little reflection on the difficulty of constructing novel questions in regression that test on concepts rather than mere calculations. Interdisciplinary collaborations can be fertile contexts for questions of this type. In this article, we offer a case study that students will find: (1) practical with respect to the question being addressed, (2) compelling in the way it shows how a solid understanding of theory helps answer the question, and (3) enlightening in the way it shows how statisticians contribute to problem solving in interdisciplinary environments. Supplementary materials for this article are available online.     

Web based resource for Statistical Consultants in the Pharmaceutical Industry

The intention of this article is to highlight sources of web-based reference material and software that will aid consulting statisticians when designing clinical trials. The article includes websites that provide links to explanation of statistical concepts for non-statisticians, regulatory guidelines, and free statistical study design software.     

Teaching Communication in a Statistical Collaboration Course: A Feasible,Project-Based,Multimodal Curriculum

Many schools offer a statistical collaboration curriculum using standard instructional methods such as lectures whereby students are taught to successfully apply their training. The process of building statisticians' collaborative skills and characteristics can be challenging due to logistical issues, time constraints, unstructured research problems, and resources. Instructors vary in their pedagogy and topics taught, and students' experiences vary. There is a dearth of literature describing how to implement a course integrating communication skills, critical thinking, collaboration, and the integration of team members in a learner-centered format. Few courses integrate behavior-based learning using role-playing, video demonstration and feedback, case-based teaching activities, and presentation of basic statistical concepts. We have developed and implemented a two-semester biostatistics collaboration course, of which the purpose is to develop the students' knowledge, skills, attitudes, and behaviors necessary to interact effectively with investigators. Our innovative curriculum uses a multimodal, project-based, experiential process to address real-world problems provided by real and/or simulated collaborators while minimizing usual challenges. Rubrics and peer evaluation forms are offered as online supplementary materials. This article describes how a collaboration curriculum focusing on communication and team practice is feasible, how it enhances skill and professionalism, and how it can be implemented at other institutions.     

Seeking useful contribution

This short communication is an attempt to define useful contribution in statistical consulting and to connect it to a collection of favorable attitudes and skills. It stresses the need for adequate education of beginning statisticians to render them capable of contributing effectively to society, business, and research. The communication ends with a list of related articles and publications.     

Preparing Statisticians for Careers in Industry: Report of the ASA Section on Statistical Education Committee on Training of Statisticians for Industry

This report provides guidelines for universities to consider in developing programs for training statisticians who will work in industry. Useful information for students who are considering industrial employment is also included. The recommended programs focus on real problems and the statistical theory and methodology that are useful in their solution. Technical competence is only one of many factors that industry considers when hiring and promoting statisticians. When a statistician leaves school, his or her skills and experiences should include statistical knowledge, practical problem solving, consulting practice, and the ability to communicate orally and in writing with nonstatisticians. There are many details that must be worked out (e.g., content of specific courses and organization of consulting internship programs), and it is hoped that the statistical societies and universities will form committees, hold conferences, and develop programs to address these issues further. Many of our recommendations apply more broadly to the training of all types of practicing statisticians.     

Dr Fisher's casebook

Regression to the mean is a classic statistical paradox and is a rare opportunity for statisticians to illustrate our uses to the general public.     

网络技术下统计的变革和统计教育面临的任务

网络经济的发展使现行的统计信息生产方式和统计制度发生深刻变革,使统计人才的知识结构发生重大变化,从而对统计教育的着力点和培养目标、培养方式提出了新的要求。如何培养大量优秀的复合型统计人才,极大地提高统计人员的素质,是统计教育面临的艰巨任务。     

大数据时代统计学的重构与创新

本文集中介绍了多位顶尖统计学家在大数据研究方面的新进展,内容涉及大数据背景下政府统计需求,统计设计,统计学理论框架的重构,统计学利用大数据在基因学、天文学、宇宙学、流行病学、经济金融学、生命科学和工程学等领域中的应用,以及大数据人才培养问题等。     

Adjusting overall survival for treatment switches: commonly used methods and practical application

In parallel group trials, long‐term efficacy endpoints may be affected if some patients switch or cross over to the alternative treatment arm prior to the event. In oncology trials, switch to the experimental treatment can occur in the control arm following disease progression and potentially impact overall survival. It may be a clinically relevant question to estimate the efficacy that would have been observed if no patients had switched, for example, to estimate ‘real‐life’ clinical effectiveness for a health technology assessment. Several commonly used statistical methods are available that try to adjust time‐to‐event data to account for treatment switching, ranging from naive exclusion and censoring approaches to more complex inverse probability of censoring weighting and rank‐preserving structural failure time models. These are described, along with their key assumptions, strengths, and limitations. Best practice guidance is provided for both trial design and analysis when switching is anticipated. Available statistical software is summarized, and examples are provided of the application of these methods in health technology assessments of oncology trials. Key considerations include having a clearly articulated rationale and research question and a well‐designed trial with sufficient good quality data collection to enable robust statistical analysis. No analysis method is universally suitable in all situations, and each makes strong untestable assumptions. There is a need for further research into new or improved techniques. This information should aid statisticians and their colleagues to improve the design and analysis of clinical trials where treatment switch is anticipated. Copyright © 2013 John Wiley & Sons, Ltd.     

The teaching of the concepts of statistical tests of hypotheses to non-statisticians

The logic underlying the formulation of statistical tests of hypothesis can be counterintuitive for the non-mathematician, e.g. to test whether two treatments are different, why suppose they are equal? When introducing the topic of hypothesis testing, it is easy to present the formal fiamework for the testing procedure without explaining the logic behind it. In courses for statisticians, one may often (unjustifiably) rely on the understanding of probability concepts as a foundation for understanding statistical inference, but in courses taught to non-statisticians where there is minimal discussion of probability, it is essential that explanations must be based on concepts the students can readily understand. The method proposed here for teaching the concept of hypothesis testing makes an analogy to the judicial system, whereby a person is assumed innocent until sufficient evidence warrants a verdict of guilty. Analogies for the different elements of statistical tests are presented and discussed, together with a classroom fiamework for discussion of statistical tests.     

Statisticians in European regulatory agencies

The UK body of statisticians in the pharmaceutical industry, PSI, has called on heads of European regulatory agencies responsible for assessing applications for marketing authorizations for new medicines in the EU to employ full time statisticians. In order to assess the present situation a survey has been conducted to identify the number of agencies employing one or more full time statisticians. Out of 29 responding agencies, 12 employed one or more statisticians on a full time basis, whereas 17 did not. Among these 17, 7 involved external experts on a regular basis, 5 involved external statisticians on a case‐by‐case basis, whereas 5 never involved external statistical expertise. Failure to involve statisticians in the assessment of efficacy and safety of medicines does not automatically lead to reports of low quality or invalid assessment of benefit‐risk. However, in depth knowledge of statistical methodology is often necessary to uncover weaknesses and potentially biased efficacy estimates. This might be of importance for the final opinion on granting a marketing authorization, and statistical review should therefore be conducted by those who are professionally expert in the area. A positive trend toward an increased involvement of statistical expertise in the European network of regulatory agencies is observed. Copyright © 2009 John Wiley & Sons, Ltd.     

Subgroup analyses of clinical effectiveness to support health technology assessments

Subgroup analysis is an integral part of access and reimbursement dossiers, in particular health technology assessment (HTA), and their HTA recommendations are often limited to subpopulations. HTA recommendations for subpopulations are not always clear and without controversies. In this paper, we review several HTA guidelines regarding subgroup analyses. We describe good statistical principles for subgroup analyses of clinical effectiveness to support HTAs and include case examples where HTA recommendations were given to subpopulations only. Unlike regulatory submissions, pharmaceutical statisticians in most companies have had limited involvement in the planning, design and preparation of HTA/payers submissions. We hope to change this by highlighting how pharmaceutical statisticians should contribute to payers' submissions. This includes early engagement in reimbursement strategy discussions to influence the design, analysis and interpretation of phase III randomized clinical trials as well as meta-analyses/network meta-analyses. The focus on this paper is on subgroup analyses relating to clinical effectiveness as we believe this is the first key step of statistical involvement and influence in the preparation of HTA and reimbursement submissions.     

Ideas of statistical experts on the choice of an analysis method

The process of data analysis can be divided into stages. The opinions of 20 statisticians on the considerations that are relevant to this decision have been studied. Nineteen concepts were identified which can be classijied into five groups:the analysis question; characteristics of the data collection; characteristics of the data; conditions for and influences on data analysis; conditions for and influences on statistical consultation. Economists mention considerations different to those mentioned by social scientists. Together the considerations form an exhaustive list of concepts that are relevant to the design of computerized support in statistics.     

Statistics for Quality and Productivity: A New Graduate-Level Statistics Course

The growing popular realization that American product quality and productivity are no longer without challenge for world leadership presents an opportunity for the American statistical community to make stronger contributions to sound industrial practice than it has in the past. Management consultants, such as Deming and Juran, are promoting philosophies that contain strong statistical components and are being heard by top U.S. executives. There are thus growing opportunities for industrial statisticians. Upon reviewing the content of typical graduate-level statistical quality control courses and books in the light of the present situation, we find them to be inadequate and in some cases to suffer from inappropriate emphases. In this article we discuss our perceptions of what is needed in the way of a new graduate-level course in statistics for quality and productivity (SQP). We further offer for discussion a syllabus for such a course (which is a modification of one used at Iowa State in the 1983 spring semester), some comments on how specific topics might be approached, and also a partially annotated list of references for material that we believe belongs in a modern SQP course.     

Leading beyond regulatory approval: Opportunities for statisticians to optimize evidence generation and impact clinical practice

The role and value of statistical contributions in drug development up to the point of health authority approval are well understood. But health authority approval is only a true ‘win’ if the evidence enables access and adoption into clinical practice. In today's complex and evolving healthcare environment, there is additional strategic evidence generation, communication, and decision support that can benefit from statistical contributions. In this article, we describe the history of medical affairs in the context of drug development, the factors driving post-approval evidence generation needs, and the opportunities for statisticians to optimize evidence generation for stakeholders beyond health authorities in order to ensure that new medicines reach appropriate patients.     

Professional development of statisticians in the pharmaceutical sector: evolution over the past decade and into the future

The adoption of The International Conference on Harmonization Tripartite Guideline: Statistical Principles for Clinical Trials (ICH-E9) has provided a foundation for the application of statistical principles in clinical research and raised awareness of the value of a statistical contribution to the wider pharmaceutical R&D process. In addition, over the past decade globalization of the pharmaceutical R&D process and the measures taken to address reduced productivity and spiralling costs have impacted on the roles and career opportunities for statisticians working in the pharmaceutical sector. This has enhanced the need for continuing professional development to equip statisticians with the skills to fully contribute to creating innovative solutions. In the future, key areas of focus are the establishment of professional standards for statistical work and increasing the collaboration between statisticians working in industry, regulatory agencies and academia. In addition, the diversity of roles and potential career paths for statisticians embarking on a career in the pharmaceutical sector emphasizes the importance of mentoring and coaching. For the more experienced statisticians, there are unprecedented opportunities to lead and innovate.     

Analogies for Helping Clinicians and Investigators Better Understand the Principles and Practice of Biostatistics

For the interaction between the biostatistician and the clinician or research investigator to be successful, it is important not only for the investigator to be able to explain biological and medical principles in a way that can be understood by the biostatistician, so, too, the biostatistician needs tools to help the investigator understand both the practice of statistics and specific statistical methods. In our practice, we have found it useful to draw analogies between statistical concepts and familiar medical or everyday ideas. These analogies help to stress a point or provide an understanding on the part of the investigator. For example, explaining the reason for using a nonparametric procedure (a general procedure used when the underlying distribution of the data is not known or cannot be assumed) by comparing it to using broad spectrum antibiotics (a general antibiotic used when the specific bacteria causing infection is unknown or cannot be assumed) can be an effective teaching tool. We present a variety of useful (and hopefully amusing) analogies that can be adopted by statisticians to help investigators at all levels of experience better understand principles and practice of statistics.