Clinical Trials

❘❙❚■ Chapter 17 | Types of Data and Normal DistributionWhat are data and variables?In a clinical trial, a large amount of information is collected on variouscharacteristics of subjects at randomization, as well as on efficacy and safetyduring follow-up visits. Sometimes, information on the participating centers in amulticenter study is also collected.‘Data’ is a collective term for information gathered under various headings orvariables. Variables may be related to demographic characteristics, such as age,gender, height, weight, and so forth; or be disease specific, such as the presence ofa torn anterior cruciate ligament, coronary disease, or severity of breathlessness;or related to treatment response, such as reduction in pain, improvement ofdisease, return to work or sport, prolongation of life, or improvement in qualityof life.For example, in a clinical trial evaluating the effect of cardiac medications inpatients with heart failure there will be two types of variables (data) collected:• qualitative (or categorical) data; these characterize a certain quality of asubject (eg, gender, age group, or disease severity group)• quantitative (or continuous or numerical) data; these represent a specificmeasure or count (eg, heart size, blood pressure, or heart rate)Qualitative data can be classified further into three main groups:• binary: only two possible responses (eg, gender)• unordered: many equal responses (eg, race)• ordered: responses have some form of increasing value (eg, disease severity)To demonstrate some of the above concepts, let us consider data from ananonymized randomized clinical trial, conducted to assess physical exerciseintervention on reducing the risk of coronary artery disease (CAD) among peopleaged between 60 and 70 years. Table 1 provides baseline data for 10 participants,and the occurrence of CAD during the 5-year study period.In the table, there are three binary variables (gender, treatment, and CAD statusat 5 years), one unordered categorical variable (race), one ordered categoricalvariable (chest pain symptoms), and three numerical variables (age, systolic bloodpressure [SBP], and heart rate). Each row in the dataset represents the values ofall the variables for one subject – called an ‘observation’. Each column representsthe range of values for a specific variable. If the variable is quantitative, it can benumerically summarized by means, medians, modes, and standard deviations.168