When a cancer patient receives information or predictions about the outcome of his or her disease, this is a prognosis (the probability a patient recovers or has a recurrence of the cancer).
The prognosis is based on research and experience regarding the disease that has been collected over time on other cancer patients. The oncologist makes the prognosis and relies on his own experience and knowledge, advice and counsel of his co-workers, and the opinion of the larger medical community as expressed in medical literature and associations.
Statisticians can study populations to determine how vulnerable they are to a disease; the measure of population risk is the study of epidemiology. Epidemiological statistics are used to attempt to forecast an individual patient’s chances of survival as well as to help choose a treatment plan to increase probability of a more favorable outcome.
A basic understanding of cancer statistics can help reduce fear, stress, and anxiety for the patient and family. Even though it is important to learn about cancer statistics, a patient should be aware that each individual is different and although predictions can be made based on past patients and treatment regimens, outcomes can sometimes differ. A patient should also know that an initial prognosis can change throughout the treatment process based on changes in the disease and the effectiveness of the treatment plan.
Basis of Cancer Statistics
Cancer statistics are based on data collected that include cancer type, age, gender, ethnic, geographic, socioeconomic, education, mortality, morbidity, and other vital statistics. Data is collected on large numbers of patients that have the same cancer type and this information is used to estimate outcomes for cancer patients diagnosed with the same types of the disease.
The following statistical terms are used to describe cancer statistics.
Incidence is a term used to define the number of patients “newly” diagnosed with a particular type of cancer that occurs in a certain population within a specific period of time. This is normally defined as the number of cancers per 100,000 in the “at risk” population.
Newly diagnosed cancers may include more than one primary cancer in an individual. Incidence rate refers to reports regarding the primary site, not metastatic site of a cancer. Normally, incidence rate does not refer to recurrent cancers. In cases of cancers that occur in one sex such as cervical cancer or prostate cancer, the “population” is defined as “sex specific”.
The following is used to calculate incidence rate:
Incidence Rate = (Number of New Cancers / Population) × 100,000
Prevalence is the percentage of individuals alive on a particular date within a population that was previously diagnosed with cancer. This may include new incidences or pre-existing incidences of cancer, and deals with past incidences and survival.
This data may be used for estimating cancer survival, treatment planning, and distribution of resources.
Morbidity is the rate at which a disease occurs. It is calculated by dividing the number of people that have the disease within a particular population by the total number of people within that particular population.
Mortality is the number of cancer deaths within a particular population over a one year period. This is expressed as the number of deaths as a result of cancer per 100,000 in a population.
The following is used to calculate mortality rate:
Mortality Rate = (Deaths from Cancer / Population) × 100,000
The numerator defines the number of cancer deaths and the denominator defines the size of the particular population.
In cases of cancers that occur in one sex such as cervical cancer or prostate cancer, the “population” is defined as “sex specific”. Mortality rate can refer to one cancer site or a combination of multiple cancers.
Prognosis is the expected outcome of the cancer or any disease. This may include the probability that a patient recovers from cancer, or experiences a recurrence of the cancer.
Survival rate is the percentage of patients with a particular cancer type, and within a particular cancer stage, that survive for a specific period of time after being diagnosed with the disease. An example may be that 45 patients out of 100 survive a particular cancer and live for at least 2 years (the remaining other 55 patients do not live for at least 2 years). Additionally, the survival rates may differentiate patients that die from the cancer from those that die from other unrelated reasons.
Types of Risk
Relative risk is a term used to define the probability an individual in an exposed group will develop a disease compared to an individual in a non-exposed group; a measure of the comparative risk of developing a disease.
Attributable risk (also called, attributable proportion) is a term used to define the measure of the proportion of overall risk attributable to a particular “risk factor” that is under examination.
Lifetime risk is a term used to define the chances or probability that an individual has of developing or dying from a cancer during his or her lifetime. Lifetime risk provides data of current risk and how it compares to the risk of a population from earlier time periods. It helps in promoting early detection of cancer, treatment planning, and increases cancer awareness efforts.