- Also called:
- incidence proportion
- Related Topics:
- epidemiology
- incidence
cumulative incidence
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What is cumulative incidence in epidemiology?
In epidemiology, cumulative incidence estimates the risk of an individual developing a disease during a specified time. It is calculated by dividing the number of new cases by the total number of individuals at risk during a specific period.
Researchers use cumulative incidence to predict disease risk over short or long periods. For example, it can be used to assess the risk of developing influenza among vaccinated seniors, the proportion of cruise passengers who develop gastroenteritis, or the proportion of patients who develop complications after surgery.
Cumulative incidence helps public health professionals and clinicians personalize the risk of developing a disease over a meaningful time. It can be estimated in studies with long follow-up periods by calculating the incidence rate and estimating the cumulative incidence from that rate.
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How is cumulative incidence different from incidence rate?
Both cumulative incidence and incidence rate are measures of disease occurrence, but they quantify risk differently. Cumulative incidence is an estimate of the risk that an individual will experience an event or develop a disease during a specified period. It is calculated by dividing the number of new events or cases of disease by the total number of individuals in the population at risk for a specific time interval.
Incidence rate quantifies the number of new cases in a population over time. The numerator is the number of new cases, while the denominator is the total person-time, or the amount of time that all at-risk persons were observed. Cumulative incidence is helpful to public health professionals and clinicians because it can personalize the risk of developing a disease or condition over a period of time that is meaningful to the patient.
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How do you calculate cumulative incidence?
Cumulative incidence estimates the risk of an individual developing a disease during a specified time. It is calculated by dividing the number of new cases of a disease by the total number of individuals at risk in the population during a specific time interval.
For example, cumulative incidence can be used to predict the risk of developing influenza among vaccinated seniors or the proportion of cruise passengers who develop gastroenteritis during a week-long vacation.
Cumulative incidence is helpful to clinicians and public health professionals because it can personalize the risk of developing a disease over a period meaningful to the patient. For studies with longer follow-up periods, cumulative incidence can be estimated by calculating incidence rates.
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What does the numerator and denominator represent in cumulative incidence?
Cumulative incidence is an estimate of the risk an individual will experience an event or develop a disease during a specified time. It is calculated by dividing the number of new events or cases of disease by the total number of individuals in the population at risk for a specific time interval.
- Numerator The numerator is the number of new cases of a disease or condition that occur during a given time period.
- Denominator The denominator is the total population at risk during the defined study period.
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Why is cumulative incidence important for studying diseases in populations?
Cumulative incidence is an important measure in epidemiology because it estimates the risk of developing a disease or experiencing an event within a specific time period. It is calculated by dividing the number of new cases by the total number of individuals at risk in a population during a specified time interval.
Cumulative incidence helps predict the risk of disease over short or long periods. It is useful to public health professionals and clinicians because it can personalize the risk of developing a condition over a period of time that is meaningful to the patient.
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How can differences in follow-up time affect the accuracy of cumulative incidence?
Cumulative incidence estimates the risk of an event or disease within a specified time period.
When a group is monitored for a short time, cumulative incidence can be computed directly. However, longer follow-up periods require incidence rates to address the question, since cumulative incidence characterizes accumulated risk over time. Public health professionals and clinicians find cumulative incidence helpful because it can personalize the risk of developing a disease or condition over a period of time that is meaningful to the patient.
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cumulative incidence, in epidemiology, estimate of the risk that an individual will experience an event or develop a disease during a specified period of time. Cumulative incidence is calculated as the number of new events or cases of disease divided by the total number of individuals in the population at risk for a specific time interval. Researchers can use cumulative incidence to predict risk of a disease or event over short or long periods of time.
An example of cumulative incidence is the risk of developing influenza among seniors vaccinated against the disease. Another example is the proportion of passengers who develop gastroenteritis while vacationing on a commercial cruise ship for a week. A third example is the proportion of patients who develop postoperative complications within one month of surgery. Individuals in each of these examples meet both of the following criteria: (1) they are free of the outcome (influenza, gastroenteritis, or postoperative complications) at the beginning of the study period, and (2) they have the potential to develop the outcome of interest during the study time period.
In the influenza example, seniors in a study are vaccinated at the beginning of flu season, before any influenza cases arise in the region. There are two ways for the investigators to define the flu season: as a time period (e.g., November to April) or by a combination of a time period and observed events. For instance, in the United States, the flu season is the time period between the first influenza case in the area and the last influenza case in the area during one continuous period of time between September and June. Regardless of how the study period is defined, it is the same for all participants in the study, and they all have the same opportunity to be identified as infected with influenza in the event that they contract the disease.
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In studies where a group is followed for a short period of time, it is possible to compute cumulative incidence directly. For studies where longer follow-up periods are needed, such as in cohort studies of diet and the risk of diabetes mellitus, it is not usually possible to estimate cumulative incidence directly. Rather, the question is addressed through the computation of incidence rates. Rates, however, characterize disease incidence for a group, whereas cumulative incidence characterizes the accumulated risk over time.
From a clinical perspective, cumulative incidence is helpful to public health professionals and clinicians because it can personalize the risk of developing a disease or condition over a period of time that is meaningful to the patient. For instance, a pediatrician might describe an overweight child’s likelihood of developing type 2 diabetes in the context of the next 10 years, or by adolescence. While cumulative incidence cannot be computed directly in studies with long follow-up periods due to losses in patient follow-up, it can be estimated in such studies by first calculating the incidence rate and then estimating the cumulative incidence from the rate. In this case, rates should be constant throughout the course of the study, and if they are not, distinct rates must be calculated for discrete time periods and then aggregated to obtain the best estimate of the cumulative incidence.