Introduction to Medical Research: Introduction
The goal of this text is to provide you with the tools and skills you need to be a smart user and consumer of medical statistics. This goal has guided us in the selection of material and in the presentation of information. This chapter outlines the reasons physicians, medical students, and others in the health care field should know biostatistics. It also describes how the book is organized, what you can expect to find in each chapter, and how you can use it most profitably.
The Scope of Biostatistics & Epidemiology
The word “statistics” has several meanings: data or numbers, the process of analyzing the data, and the description of a field of study. It derives from the Latin word status, meaning “manner of standing” or “position.” Statistics were first used by tax assessors to collect information for determining assets and assessing taxes—an unfortunate beginning and one the profession has not entirely lived down.
Everyone is familiar with the statistics used in baseball and other sports, such as a baseball player’s batting average, a bowler’s game point average, and a basketball player’s free-throw percentage. In medicine, some of the statistics most often encountered are called means, standard deviations, proportions, and rates. Working with statistics involves using statistical methods that summarize data (to obtain, for example, means and standard deviations) and using statistical procedures to reach certain conclusions that can be applied to patient care or public health planning. The subject area of statistics is the set of all the statistical methods and procedures used by those who work with statistics. The application of statistics is broad indeed and includes business, marketing, economics, agriculture, education, psychology, sociology, anthropology, and biology, in addition to our special interest, medicine and other health care disciplines. Here we use the terms biostatistics and biometrics to refer to the application of statistics in the health-related fields.
Although the focus of this text is biostatistics, some topics related to epidemiology are included as well. These topics and others specific to epidemiology are discussed in more detail in the companion book, Medical Epidemiology (Greenberg, 2000). The term “epidemiology” refers to the study of health and illness in human populations, or, more precisely, to the patterns of health or disease and the factors that influence these patterns; it is based on the Greek words for “upon” (epi) and “people” (demos). Once knowledge of the epidemiology of a disease is available, it is used to understand the cause of the disease, determine public health policy, and plan treatment. The application of population-based information to decision making about individual patients is often referred to as clinical epidemiology and, more recently, evidence-based medicine. The tools and methods of biostatistics are an integral part of these disciplines.
Biostatistics in Medicine
Clinicians must evaluate and use new information throughout their lives. The skills you learn in this text will assist in this process because they concern modern knowledge acquisition methods. In the following subsections, we list the most important reasons for learning biostatistics. (The most widely applicable reasons are mentioned first.)
Reading the literature begins early in the training of health professionals and continues throughout their careers. They must understand biostatistics to decide whether they can believe the results presented in the literature. Journal editors try to screen out articles that are improperly designed or analyzed, but few have formal statistical training and they naturally focus on the content of the research rather than the method. Investigators for large, expensive studies almost always consult statisticians for assistance in project design and data analysis, especially research funded by the National Institutes of Health and other national agencies and foundations. Even then it is important to be aware of possible shortcomings in the way a study is designed and carried out. In smaller research projects, investigators consult with statisticians less frequently, either because they are unaware of the need for statistical assistance or because the biostatistical resources are not readily available or affordable. The availability of easy-to-use computer programs to perform statistical analysis has been important in promoting the use of more complex methods. This same accessibility, however, enables people without the training or expertise in statistical methodology to report complicated analyses when they are not always appropriate.
The problems with studies in the medical literature have been amply documented, and we suggest you examine some of the following references for more information. One of the most comprehensive reports was by Williamson and colleagues (1992) who reviewed 28 articles that examined the scientific adequacy of study designs, data collection, and statistical methods in more than 4200 published medical studies. The reports assessed drug trials and surgical, therapeutic, and diagnostic procedures published in more than 30 journals, many of them well known and prestigious (eg, British Medical Journal, Journal of the American Medical Association, New England Journal of Medicine, Canadian Medical Association Journal, and Lancet). Williamson and colleagues determined that only about 20% of 4235 research reports met the assessors’ criteria for validity. Eight of the assessment articles had also looked at the relationship between the frequency of positive findings and the adequacy of the methods used in research reports and found that approximately 80% of inadequately designed studies reported positive findings, whereas only 25% of adequately designed studies had positive findings. Thus, evidence indicates that positive findings are reported more often in poorly conducted studies than in well-conducted ones.
Other articles indicate that the problems with reported studies have not improved substantially. Müllner and colleagues (2002) reviewed 34 commonly read medical journals and found inadequate reporting of methods to control for confounding (other factors that may affect the outcome). Moss and colleagues (2003) reported that 40% of pulmonary and critical care articles that used logistic regression (discussed in Chapter 10) may not have used the method appropriately. The problem is not limited to the English-speaking literature. As examples, Hayran (2002) reported that 56% of the articles in the Turkish literature used improper or inadequate statistics, and Skovlund (1998) evaluated cancer research articles published by Norwegian authors and found that 64% had unsuitable statistical methods. Several journals, including the New England Journal of Medicine, the Journal of the American Medical Association, the Canadian Medical Association Journal, and the British Medical Journal, have carried series of articles on study design and statistical methods. Some of the articles have been published in a separate monograph (eg, Bailar and Mosteller, 1992; Greenhalgh, 1997b).
Journals have also published a number of articles that suggest how practitioners could better report their research findings. We agree with many of these recommendations, but we firmly believe that we, as readers, must assume the responsibility for determining whether the results of a published study are valid. Our development of this book has been guided by the study designs and statistical methods found primarily in the medical literature, and we have selected topics to provide the skills needed to determine whether a study is valid and should be believed. Chapter 13 focuses specifically on how to read the medical literature and provides checklists for flaws in studies and problems in analysis.
Applying the results of research to patient care is the major reason practicing clinicians read the medical literature. They want to know which diagnostic procedures are best, which methods of treatment are optimal, and how the treatment regimen should be designed and implemented. Of course, they also read journals to stay aware and up to date in medicine in general as well as in their specific area of interest. Chapters 3 and 12 discuss the application of techniques of evidence-based medicine to decisions about the care of individual patients. Greenhalgh (2002) discusses ways to integrate qualitative research into evidence-based medicine.
Physicians must be able to interpret vital statistics in order to diagnose and treat patients effectively. Vital statistics are based on data collected from the ongoing recording of vital events, such as births and deaths. A basic understanding of how vital statistics are determined, what they mean, and how they are used facilitates their use. Chapter 3 provides information on these statistics.
Practitioners must understand epidemiologic problems because this information helps them make diagnoses and develop management plans for patients. Epidemiologic data reveal the prevalence of a disease, its variation by season of the year and by geographic location, and its relation to certain risk factors. In addition, epidemiology helps us understand how newly identified viruses and other infectious agents spread. This information helps society make informed decisions about the deployment of health resources, for example, whether a community should begin a surveillance program, whether a screening program is warranted and can be designed to be efficient and effective, and whether community resources should be used for specific health problems. Describing and using data in making decisions are highlighted in Chapters 3 and 12.
Physicians continually evaluate information about drugs and medical instruments and equipment. This material may be provided by company representatives, sent through the mail, or published in journals. Because of the high cost of developing drugs and medical instruments, companies do all they can to recoup their investments. To sell their products, a company must convince physicians that its products are better than those of its competitors. To make its points, it uses graphs, charts, and the results of studies comparing its products with others on the market. Every chapter in this text is related to the skills needed to evaluate these materials, but Chapters 2, 3, and 13 are especially relevant.
Identifying the correct diagnostic procedure to use is a necessity in making decisions about patient care. In addition to knowing the prevalence of a given disease, physicians must be aware of the sensitivity of a diagnostic test in detecting the disease when it is present and the frequency with which the test correctly indicates no disease in a well person. These characteristics are called the sensitivity and specificity of a diagnostic test. Information in Chapters 4 and 12 relates particularly to skills for interpreting diagnostic tests.
