Design And Analysis Of Vaccine Studies

As well as being a reference for the design, analysis, and interpretation of vaccine studies, the text covers all design and analysis stages, from vaccine development to post-licensure surveillance, presenting likelihood, frequentists, and Bayesian approaches.

Vaccines are among the most safe and effective public health interventions to prevent serious disease and death. Because of the success of vaccines, most Americans today have no firsthand experience with such devastating illnesses as polio or diphtheria. Health care providers who vaccinate young children follow a schedule prepared by the U.S. Advisory Committee on Immunization Practices. Under the current schedule, children younger than six may receive as many as 24 immunizations by their second birthday. New vaccines undergo rigorous testing prior to receiving FDA approval; however, like all medicines and medical interventions, vaccines carry some risk. Driven largely by concerns about potential side effects, there has been a shift in some parents' attitudes toward the child immunization schedule. The Childhood Immunization Schedule and Safety identifies research approaches, methodologies, and study designs that could address questions about the safety of the current schedule. This report is the most comprehensive examination of the immunization schedule to date. The IOM authoring committee uncovered no evidence of major safety concerns associated with adherence to the childhood immunization schedule. Should signals arise that there may be need for investigation, however, the report offers a framework for conducting safety research using existing or new data collection systems.

Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.

Sequential Experimentation in Clinical Trials: Design and Analysis is developed from decades of work in research groups, statistical pedagogy, and workshop participation. Different parts of the book can be used for short courses on clinical trials, translational medical research, and sequential experimentation. The authors have successfully used the book to teach innovative clinical trial designs and statistical methods for Statistics Ph.D. students at Stanford University. There are additional online supplements for the book that include chapter-specific exercises and information. Sequential Experimentation in Clinical Trials: Design and Analysis covers the much broader subject of sequential experimentation that includes group sequential and adaptive designs of Phase II and III clinical trials, which have attracted much attention in the past three decades. In particular, the broad scope of design and analysis problems in sequential experimentation clearly requires a wide range of statistical methods and models from nonlinear regression analysis, experimental design, dynamic programming, survival analysis, resampling, and likelihood and Bayesian inference. The background material in these building blocks is summarized in Chapter 2 and Chapter 3 and certain sections in Chapter 6 and Chapter 7. Besides group sequential tests and adaptive designs, the book also introduces sequential change-point detection methods in Chapter 5 in connection with pharmacovigilance and public health surveillance. Together with dynamic programming and approximate dynamic programming in Chapter 3, the book therefore covers all basic topics for a graduate course in sequential analysis designs.

The Vaccine Safety Datalink (VSD) is a large, linked database of patient information that was developed jointly by CDC and several private managed care organizations in 1991. It includes data on vaccination histories, health outcomes, and characteristics of more than 7 million patients of eight participating health organizations. Researchers from CDC and the managed care groups have used VSD information to study whether health problems are associated with vaccinations. The subsequent VSD data sharing program was launched in 2002 to allow independent, external researchers access to information in the database. In this report, the committee that was asked to review aspects of this program recommends that two new oversight groups are needed to ensure that the policies and procedures of the VSD and its data sharing program are implemented as fairly and openly as possible.

The increased use of non-inferiority analysis has been accompanied by a proliferation of research on the design and analysis of non-inferiority studies. Using examples from real clinical trials, Design and Analysis of Non-Inferiority Trials brings together this body of research and confronts the issues involved in the design of a non-inferiority trial. Each chapter begins with a non-technical introduction, making the text easily understood by those without prior knowledge of this type of trial. Topics covered include: A variety of issues of non-inferiority trials, including multiple comparisons, missing data, analysis population, the use of safety margins, the internal consistency of non-inferiority inference, the use of surrogate endpoints, trial monitoring, and equivalence trials Specific issues and analysis methods when the data are binary, continuous, and time-to-event The history of non-inferiority trials and the design and conduct considerations for a non-inferiority trial The strength of evidence of an efficacy finding and how to evaluate the effect size of an active control therapy A comprehensive discussion on the purpose and issues involved with non-inferiority trials, Design and Analysis of Non-inferiority Trials will assist current and future scientists and statisticians on the optimal design of non-inferiority trials and in assessing the quality of non-inferiority comparisons done in practice.

Formulation, Development and Manufacturing of Vaccines: The Practical Aspects provides an industry perspective on vaccine product development and manufacture that covers their formulation development, manufacture and delivery/in-use considerations of vaccine production. With the increasing complexity of vaccine products in development, there is a need for a comprehensive review of the current state of the industry and its challenges. While formulation scientists working in biotherapeutic development may be familiar with proteins, vaccines present unique challenges, including the wide range of vaccine components that may comprise proteins, polysaccharides, protein-polysaccharide conjugates, adjuvants, etc. and the varying stability and behavior of solution- and suspension-based systems. This book is an essential resource for formulation scientists, researchers in vaccine development throughout medical and life sciences, and advanced students. Includes formulation considerations for various vaccine types, including proteins, polysaccharides, conjugates and live vaccines Considers process development for solution, suspension and lyophilized products Explores the future potential of vaccines, including multi-component vaccines and novel delivery mechanisms/devices