Cancers represent a heterogeneous group of diseases characterized by uncontrolled growth and spread of abnormal cells in the body. The disruptive behaviors of cancer cells reflect dynamic changes in their genomes and in gene expression that result in disruption of normal regulatory signaling circuits. Cancers vary on the basis of both the biologic features of the disease and the characteristics of the affected organism. The process by which normal cells are transformed into cancer cells is known as carcinogenesis.
Cancers are multifactorial diseases, with environmental and endogenous factors contributing at a different level in determining cancer risk. Epidemiology is the study of the distribution and determinants of diseases in populations. Cancer frequency is expressed by mean of measures of disease occurrence. Many sciences are aimed at the study of tumors, but in epidemiology the focus is on occurrence rather than natural history or any other aspect of the disease under investigation.
Incidence rate and prevalence represent the basic epidemiologic tools that allow us to quantify the disease occurrence. Incidence rate is the number of newly diagnosed cases of disease that occurs in a population during a specified period of time over person-year of observation. To define the incidence rate of a given disease, we indicate the population at risk for the disease of interest, the risk or event we are studying (e.g., disease occurrence), and the period over which we want to measure incidence. Every member of the population experiences a specific amount of time in the population over the risk period. Person-time represents the observational experience in which disease onset can be observed. The number of new cases of disease (incident number) divided by the person-time is the disease incidence rate in the considered population over the defined period:
Incidence rate = No. disease onset/ X persons time spent in population
The only events suitable to be counted in the numerator of an incidence rate are those that occur to persons who are contributing time to the denominator of the incidence rate at the time the disease onset occurs. The time contributed by each person to the denominator is known as the "time at risk," that is, time at risk of an event's occurring. People who contribute time to the denominator of an incidence rate are referred to as "the population at risk."
Prevalence may be defined as the ratio of number of cases of disease at a given time to the size of the population at that time. The population subset affected by the disease is known as the "prevalence pool." While incidence measures focus on events in a population at risk for the disease under investigation over a defined period of time, prevalence focuses on disease status in a prevalence pool at a specific point in time.
Given these definitions, disease prevalence and incidence rate appear to be related to each other. For a disease under investigation, a certain proportion of the population at risk of developing a specific cancer feeds the prevalence pool of persons affected by the cancer of interest at a specific point in time. The event occurrence (e.g., newly diagnosed breast cancer) influences the disease status at a population level.
An important role in the linkage between the measures of disease frequency is played by the mean duration of the disease under consideration. Diseases with large incidence rates may have low prevalence if they are rapidly fatal (e.g., SCLC
or small cell lung cancer). On the other hand, cancer may be characterized at the same time by a high incidence rate and a quite long natural history, having a large prevalence in the population under consideration (e.g., prostate cancer). In defining the relationship between incidence rate and prevalence of a disease of interest, many factors, not only the disease mean duration, should be taken into account, since, in the same population, subgroups of individuals might deeply differ in terms of measures of disease occurrence on the basis of parameters such as gender, age, ethnicity, education, income, social class, disability, geographic location.1
Cancer determinants, as well as cancer frequency, represent a major topic in cancer epidemiology. Cancer is a multifactorial disease. The final risk of developing a pathologic condition depends on interactions of different risk factors. A risk factor is anything that increases the chances of getting a disease such as cancer. Different cancers have different risk factors. The role of genetic and environmental interaction in the occurrence of several common malignancies has been clearly demonstrated in many recent epidemiologic studies, as reviewed by Caporaso and Goldstein2 and Strong and Amos.3
A small percentage of cancers (5 to 10%) can be attributed to the inheritance of one or more mutated genes that are carried in germ cells of parent and passed on to an offspring. As a result, all cells of the offspring show the same genetic defect, predisposing the individual to one or more specific cancer. Familial breast, ovarian, and prostatic cancers, linked to breast cancer susceptibility gene 1 (BRCA-1) and breast cancer susceptibility gene 2 (BRCA-2) gene mutations, and familial adenomatous polyposis predisposing to colon cancer, based on APC gene mutations, represent good examples of diseases caused by genetic factors.
A large proportion of cancers previously thought to be attributable to environmental factors alone are now considered the result of interaction between inherited susceptibility factors and environmental exposures. The study of gene-environment interaction has become one of the major topics in genetic epidemiology, a discipline integrating the principles and methodology of genetics and epidemiology.4
An understanding of disease etiology, supported by measures of disease occurrence at a population level, represents the basis of cancer therapy and prevention. Cancer epidemiology combines its interest in disease frequency and determinants in the elaboration and validation of hypotheses that can explain patterns of disease occurrence.
Even though scientific hypotheses are often posed as qualitative propositions, the testing of hypotheses is predicated on measurement. The importance of measurements has been reflected in the evolution of epidemiologic understanding. It was only when scientists began to measure the occurrence of diseases rather than merely reflect on what may have caused diseases that scientific knowledge about causation made impressive strides.1
Epidemiologic studies represent useful tools to collect data to elucidate the etiology of and risk factors for human diseases. Scientists design and conduct studies, which are critically important both in clinical medicine and in public health practice.
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