Clinicians often communicate probabilities as words (e.g., usually, sometimes, rarely) rather than as numbers. Substituting words for numbers is convenient and avoids making a precise statement when one is uncertain about a probability. However, words are a poor substitute for numbers because there is little agreement about the meanings of commonly used adjectives describing probabilities.

Patients also assign widely varying probabilities to word descriptions. In another study, highly skilled and professional workers outside of medicine thought “usually” referred to probabilities of 35% to 100%; “rarely” meant to them a probability of 0% to 15% (3).

Thus, substituting words for numbers diminishes the information conveyed. We advocate using numbers whenever possible.

In general, clinically relevant measures of frequency are expressed as proportions, in which the numerator is the number of patients experiencing an event (cases) and the denominator is the number of people in whom the event could have occurred (population). The two basic measures of frequency are prevalence and incidence.

Anything that increases the duration of disease increases the chances that the patient will be identified in a prevalence study. Another look at Figure 2.1 will confirm this. Prevalent cases are those that remain affected, to the extent that patients are cured, die of their disease, or leave the population under study, they are no longer a case in a prevalence survey. As a result, diseases of brief duration will be more likely to be missed by a prevalence study. For example, 15% of all deaths from coronary heart disease occur outside the hospital within an hour of onset and without prior symptoms of heart disease. A prevalence
study would, therefore, miss nearly all these events and underestimate the true burden of coronary heart disease in the community. In contrast, diseases of long duration are well represented in prevalence surveys, even when their incidence is low. The incidence of inflammatory bowel disease in North America is only about 2 to 14 per 100,000/year, but its prevalence is much higher, 37 to 246/100,000, reflecting the chronic nature of the disease (4).

The relationship among incidence, prevalence and duration of disease in a steady state, in which none of the variables is changing much over time, is approximated by the following expression:

Prevalence = Incidence × Average

duration of the disease

Alternatively,

Prevalence/Incidence = Duration

Similarly, the prevalence of prostate cancer on autopsy is so much higher than its incidence that the majority of these cancers must never become symptomatic enough to be diagnosed during life.

Table 2.2 summarizes some rates used in health care. Most of them are expressions of events over time. For example, a case fatality rate (or alternatively, the survival rate) is the proportion of people having a disease who die of it (or who survive it). For acute diseases such as Ebola virus infection, follow-up time may be implicit, assuming that deaths are counted over a long enough period of time (in this case, a few weeks) to account for all of them that might have occurred. For chronic diseases such as cardiovascular disease or cancer, it is more usual to specify the period of observation (e.g., the 5-year survival rate). Similarly, complication rate, the proportion of people with a disease or treatment who experience complications, assumes that enough time has passed for the complications to have occurred. These kinds of measures can be underestimations if follow-up is not really long enough. For example, surgical site infection rates have been underreported because they have been counted up to the time of hospital discharge, whereas some wound infections are first apparent after discharge (6).

Other rates, such as infant mortality rate and perinatal mortality rate (defined in Table 2.2) are approximations of incidence because the children in the numerator are not necessarily those in the denominator. In the case of infant mortality rate for a given year, some of the children who die in that year were born in the previous year; similarly, the last children to be born in that year may die in the following year. These rates are constructed in this way to make measurement more feasible, while providing a useful approximation of a true rate in a given year.

Prevalence and incidence are measured by entirely different kinds of studies.