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Cancer Statistics
Cancer statistics are used for a variety of purposes. Researchers and =
cancer organizations (such as the National Cancer Institute) use =
statistics to track cancer trends. For example, if the incidence of any =
type cancer is seen to be increasing across several years, researchers =
will want to discover why and what can be done about it. Scientists also =
use statistics to determine how well a particular prevention or =
treatment method may be working: If a new chemotherapy drug increases =
the 5-year survival rate of patients with breast cancer, that shows =
scientists that the drug is a valuable addition to the treatment =
arsenal.=20
When it comes to the general public and cancer patients, the usefulness =
of cancer statistics depends on how they are interpreted and used. It =
has been widely reported that the lifetime risk of developing breast =
cancer is 1 in 8- a frightening thought for women who misinterpret that =
statistic to mean that at any time, they have a 1 in 8 chance of having =
breast cancer. The actual chances of developing breast cancer change =
throughout a woman's life, so that a 20-year-old woman has a current =
risk of only 1 in 2,500 of developing the disease within the next 10 =
years, and a 50-year-old woman has a current risk of about 1 in 39. =
Heredity, ethnicity, reproductive history, lifestyle factors and other =
risk factors all contribute to an individual's risk. So cancer =
statistics are useful when used for broad perspective but not for =
individual application.=20
The following definitions are provided to help you make sense of the =
sometimes confusing statistical terminology used when discussing cancer =
and its outcomes. Incidence describes the number of new cases of cancer =
developed by a specific population group within a set period of =
time-usually one year. For example, the total 2000 incidence of =
testicular cancer will be about 6,900 men. Incidence rate is the number =
of new cases in a population. The incidence is usually expressed in =
terms of the number of cases per 100,000 people. For example, the =
incidence rate for testicular cancer in the United States is =
approximately 3 new cases per 100,000 men, often stated simply as 3 per =
100,000.=20
Prevalence is the total number of people with cancer or with a =
particular risk factor for cancer at a particular moment in time in the =
entire population. For large groups of people, prevalence is estimated =
by collecting information from a smaller subset of people and then =
extrapolating that information to the general population. For example, =
by collecting DNA information from breast cancer patients, scientists =
have estimated that the prevalence of the BRCA-1 gene in the total =
population is between 0.04 percent and 0.2 percent, meaning that much =
less than 1 percent of the total population has this breast cancer =
susceptibility gene.=20
Morbidity is a state of illness; i.e., it is often said that smoking is =
a major cause of morbidity in the U.S.=20
Mortality means pertaining to death.=20
Mortality rate is the number of people in a population group who die of =
cancer within a set period of time, usually one year. Cancer mortality =
rate is usually expressed in terms of deaths per 100,000 people. For =
example, the mortality rate for stomach cancer in the U.S. in 1930 was =
28 (28 deaths per 100,000 people), but dropped to 4 by 1992, meaning =
that only 4 people out of every 100,000 in the U.S. died of stomach =
cancer in 1992.=20
Prognosis is the prediction or estimation of the course and outcome of =
the disease, usually including the chances for recovery. While =
physicians may base a prognosis on statistical precedents, each =
individual is different, with actual outcomes affected by many factors, =
including the patient's age and general health, the type and stage of =
cancer, and the effectiveness of the particular treatment used. =
Therefore, while a prognosis may be helpful for explaining the =
seriousness of a disorder or for guiding treatment decisions, it cannot =
be used to predict disease outcomes for an individual.=20
Survival rate is the measure of the number of people who develop cancer =
and survive over a period of time. Scientists commonly use five-year =
survival as the standard statistical basis for defining when a cancer =
has been successfully treated.=20
The 5-year survival rate includes anyone who is living five years after =
a cancer diagnosis including those who are cured, those in remission, =
and those who still have cancer and are undergoing treatment. For =
example, when colorectal cancers are detected early, the 5-year survival =
rate is 92 percent, meaning that 92 percent of all colorectal cancer =
patients live at least 5 years after diagnosis if the cancer is detected =
early.=20
The "overall" 5-year survival rates measure everyone who has ever been =
diagnosed with a particular cancer equally, which may lead to distorted =
statistics. For example, a 90-year-old man and a 30-year-old man who =
have the same cancer will be grouped together. The 90-year-old may die =
of other causes within the five-year period due to normal life =
expectancy, and this can skew the data. A more statistically accurate =
view of survival is the "relative" 5-year survival rate, which compares =
cancer patients' survival rate with the survival rate of the general =
population, taking into account differences in age, gender, race and =
other factors. In this case, the 30-year-old and the 90-year-old would =
be treated as statistically different.=20
Risk refers to the chance that an individual will contract a disease. =
High-risk is when the chance of developing cancer is greater than the =
chance for the general population. For example, people who smoke have a =
high risk of developing lung cancer compared with people who don't =
smoke.=20
Risk factor is anything that has been identified as increasing a =
person's chance of getting a disease. These can be controllable or =
uncontrollable, personal or environmental. For example, risk factors for =
developing colon cancer include having a hereditary predisposition to =
the disease (uncontrollable) and eating a high-fat, low-fiber diet =
(controllable).=20
Relative risk is a measure of how much a particular risk factor =
increases the risk of development of a specific cancer. For example, the =
risk for developing ovarian cancer increases by 300 percent for a woman =
with a close family history of the disease compared to a woman without a =
family history. In this example, the relative risk of developing ovarian =
cancer is 3 for those with a family history, meaning they have 3 times =
the risk.=20
Attributable risk is a measure of how much of the total incidence of =
disease is caused by that risk factor. For example, even thought the =
relative risk of developing breast cancer for a woman with the BRCA-1 =
gene is high, since the prevalence I of the BRCA-1 gene is low, most =
cases of breast cancer are not caused by the BRCA-1 gene.=20
Lifetime risk is the probability of developing or dying of cancer =
sometime during one's lifetime. A person has a lifetime risk of 2 in 5 =
of developing cancer, meaning that for every five people in the =
population, two will eventually develop cancer. The lifetime risk of =
dying of cancer in 1 in 5.=20
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