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Glossary Terms



Absolute Risk

The probability or chance that a person will have a medical event. Absolute risk is expressed as a percentage.  It is the ratio of the number of people who have a medical event divided by all of the people who could have the event because of their medical condition.


For example, research studies have found that among 10,000 people age 75 and over who take a drug like ibuprofen for osteoarthritis pain, 15 of them will die from stomach bleeding.  The absolute risk of dying from stomach bleeding is 15 out of 10,000, or 0.15 percent of people taking ibuprofen.


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Adverse Drug Reaction

A bad or harmful reaction to a drug that is used to treat or prevent a disease.


For example, a small number of people may develop a skin rash when they start a medication. The skin rash is an adverse drug reaction.



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Adverse Effect

Anything that a person might feel is a negative or harmful result of a treatment or test.


For example, sleepiness is a common occurrence when people take certain allergy medications. Sleepiness is an adverse effect.


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Adverse Event (Adverse Reaction)

Any negative or unwanted effect from any drug, device, or medical test.


For example, some people might experience dizziness when they start a medication. The dizziness is an adverse event.


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Adverse Reaction (Adverse Event)

Any negative or unwanted effect from a drug, device, or medical test.


For example, some people might experience dizziness when they start a medication. The dizziness is an adverse reaction.


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Analysis (Statistical Analysis)

The process of preparing the results or conclusions of a study.  An analysis usually is performed by doing mathematical calculations known as statistics.


For example, in a research study to find out whether a drug works to increase bone density, the analysis would look at the data for each group of people in the study and compare the results.  It might examine whether the people taking the drug had fewer broken bones than people who had not taken the drug. 


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Association

A relationship.  In research studies, association means that two characteristics (sometimes also called variables or factors) are related so that if one changes, the other changes in a predictable way.  An association does not necessarily mean that one variable causes the other.


For example, a research study could be conducted to determine whether there is an association between high blood pressure (one variable) and high salt consumption (other variable).


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Bias

Any factor, recognized or not, that distorts the findings of a study.  In research studies, bias can influence the observations, results, and conclusions of the study and make them less accurate or believable.


For example, in studies of new drugs, it often was customary to record adverse events only when they occurred in more than 5 or 10 percent of the people taking the drugs.  Since information about rare adverse events was not reported, this led to conclusions that the drugs caused fewer side effects than was actually the case. This led to a bias in the number of reported side effects.


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Black Box Warning

An advisory from the U.S. Food and Drug Administration (FDA) that tells health care professionals and consumers that a drug might be very dangerous for some people.  The FDA is the U.S. Government agency that regulates and monitors drugs and medical devices to make sure they are safe and effective.

Every prescription drug comes with a package insert.  The insert contains information about the drug, including the name, manufacturer, drug class, purpose, benefits, and risks.  The Black Box Warning gets its name from the black border around the warning that indicates that the drug sometimes causes serious adverse events.


Here is an example of a Black Box Warning:
FDA Alert <4/11/2005>: Increased Mortality in Patients with Dementia-Related Psychosis
FDA has determined that patients with dementia-related psychosis treated with atypical (second generation) antipsychotic medications are at an increased risk of death compared to placebo.  Based on currently available data, FDA has requested that the package insert for each atypical antipsychotic be revised to include a Black Box Warning describing this risk and noting that this drug is not approved for this indication.



Blinding (Masking)

A way of making sure that the people involved in a research study — participants, clinicians, or researchers — do not know which participants are assigned to each study group.  Blinding usually is used in research studies that compare two or more types of treatment for an illness.  Blinding is used to make sure that knowing the type of treatment does not affect a participant’s response to the treatment, a health care provider’s behavior, or assessment of the treatment effects. 


For example, blinding is usually done in a type of study known as a randomized controlled trial. The participants are considered “blinded” if they do not know whether they are taking the drug being researched or a placebo.  When neither the participants nor the researchers know who is taking the drug, the study is called “double-blinded.”


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Clinical Research

The branch of medical science devoted to finding information that improves people’s health.  It includes research studies that examine the safety and effectiveness of medications, medical devices, diagnostic tests, and treatment regimens intended for human use.  Usually, more than one person with the same disease is studied.


For example, the Women’s Health Initiative (WHI) is a national clinical research study composed of several study components.  The WHI includes:
  1. A randomized controlled clinical trial of promising but unproven approaches to prevention;
  2. An observational study to identify predictors of disease; and
  3. A study of community approaches to developing healthful behaviors.


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Clinical Trial

A carefully conducted research study that compares the effects of drugs, treatments, or diagnostic tests.


For example, in a randomized controlled clinical trial to understand whether calcium tablets work to prevent broken bones in women with low bone density, women with low bone density in one group are randomly assigned to receive calcium and women with low bone density in another group are randomly assigned to the control group and receive a placebo (inactive substance).  The numbers of women who suffer fractures in each group are compared to find out whether calcium works.


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Cohort

A group of people with some characteristic in common.  The characteristic can be:

  • Where people live.
  • Where they work.
  • Where they go to school.
  • People of the same age.
  • People with the same medical condition.
  • People receiving the same medical treatment.


For example, the Women’s Health Initiative was a large study that collected information from a group of older women (a cohort) who were followed over several years.


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Cohort Study (Prospective Observational Study)

A clinical research study in which people who presently have a certain condition or receive a particular treatment are followed over time and compared with another group of people who are not affected by the condition.

In a cohort study (also known as a prospective observational study), the researchers take measurements of the people who belong to a cohort at several points in time.  The measurements can be symptoms, blood tests, X-rays, or whether the disease has caused the person to die.


For example, the Women’s Health Initiative is a cohort study that collects information from a group of older women who are followed over several years.


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Comparative Effectiveness

A type of health care research that compares the results of one approach for managing a disease to the results of other approaches. Comparative effectiveness usually compares two or more types of treatment, such as different drugs, for the same disease.  Comparative effectiveness also can compare types of surgery or other kinds of medical procedures and tests. The results often are summarized in a systematic review.

The kinds of results that are studied to compare drugs or procedures include relief of symptoms, length of life, or whether people need to go to the hopital.  These results are called outcomes.  Many other kinds of outcomes can also be compared.


Researchers examined the comparative effectiveness of drugs used to treat depression.  They examined all the studies about using drugs known as antidepressants.  The studies looked at how well people’s symptoms improved after taking an antidepressant and also examined the occurrence of side effects.  The researchers summarized their findings in a systematic review. 



Confidence Interval

The range in which a particular result (such as a laboratory test) is likely to occur for everyone who has a disease.  “Likely” usually means 95 percent of the time.


Clinical research studies are conducted on only a certain number of people with a disease rather than all the people who have the disease.  The study’s results are true for the people who were in the study but not necessarily for everyone who has the disease.

The confidence interval is a statistical estimate of how much the study findings would vary if other different people participated in the study.  A confidence interval is defined by two numbers, one lower than the result found in the study and the other higher than the study’s result.  The size of the confidence interval is the difference between these two numbers.


For example, a study shows that the risk of heart attack from a drug is 3 percent (0.03).  The confidence interval is shown as “95% CI: 0.015, 0.04.” This means that if you conduct this study on 100 different samples of people, the risk of heart attack in 95 of the samples will fall between 1.5 percent and 4 percent.  We are 95 percent confident that the true risk is between .015 and .04.


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Control Group

In a research study, the group of people who do not receive the treatment being tested. The control group might receive a placebo, a different treatment for the disease, or no treatment at all.


For example, in an osteoarthritis study that found glucosamine was better than placebo in controlling pain and improving function, glucosamine was the treatment being tested, and an inactive substance (placebo) was the control.  The people taking placebo were the control group.


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Controlled Clinical Trial

A type of clinical trial comparing the effectiveness of one medication or treatment with the effectiveness of another medication or treatment.  In many controlled trials, the other treatment is a placebo (inactive substance) and is considered the “control.”


An example of a controlled clinical trial is one in which people who took glucosamine were compared with people who did not take glucosamine to determine its effectiveness in relieving pain and improving function for people with osteoarthritis.


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Cost-Benefit Analysis

A type of analysis that compares the financial costs with the benefits of two or more health care treatments or programs.  Health care interventions that have the same or better benefit at a lower cost are better values than treatments or programs that are more expensive. 


For example, cost-benefit analyses have been conducted to compare vaccinating people against a certain disease versus treating those people who get sick from the disease when no one is vaccinated.


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Cost-Effectiveness Analysis

A type of analysis that is similar to a cost-benefit analysis but is used when the benefits cannot be measured in financial terms or dollars.  It would be hard to put a price-tag on living an extra year of life. 


For example, a cost-effectiveness analysis might compare the costs of two health care interventions that both helped people to live an extra year.


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Data

In clinical research, the information recorded about a participant in a study.  There are many different kinds of data.


Some types of data are:
  • Baseline — Information that describes the condition of people at the beginning of the study.
  • Demographic — Information about the person’s age, sex, race, geographic background, etc.
  • Objective — Information that can be measured.  For example, blood or laboratory test results or X-ray findings.
  • Subjective — Severity of symptoms or how people feel about their health.
  • Quality-of-Life — Subjective and objective information about a person’s feelings and ability to perform certain routine, daily activities.  For example, if a person has arthritis, how much pain does that person have? How easy is it to move or hold something?


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Diagnostic Test

A procedure to provide information about a person’s condition that helps health care providers to make a diagnosis.  Diagnostic tests provide information about whether a person does or does not have a particular disease. 


For example, diagnostic tests include chemical analyses of a body substance (such as blood, urine, or saliva), imaging (such as an X-ray or ultrasound), electrocardiograms (to monitor heart conditions), and biopsies (looking at cells under a microscope).  Hearing tests and vision tests are other examples of diagnostic tests.



Drug

A medicine (chemical compound) used to prevent, diagnose, or treat conditions.  Some drugs need a prescription from a physician or nurse practitioner and other drugs do not need a prescription.


For example, antibiotics, such as penicillin or tetracycline, are common drugs that are used to treat infections caused by bacteria.


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Drug Product

A manufactured product that contains a drug.  There are many forms of drug products, including tablets (pills), capsules, creams, or liquids.  A drug product often includes other chemicals that are not harmful to most people.  They are included in the product for such reasons as making a liquid taste better or binding a tablet together so that it does not crumble in the bottle.


For example, a cream containing capsaicin that can be put on the skin to reduce osteoarthritis pain is a drug product.


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Effect Size (Treatment Effect)

The amount of change in a condition or symptom because of a treatment (compared to not receiving the treatment).  It is commonly expressed as a risk ratio (relative risk), odds ratio, or difference in risk.


For example, in studies about side effects of antipsychotic drugs, researchers found that these drugs were three times more likely to cause drowsiness than a placebo. The odds ratio was 3.0, meaning the effect size was “three times as likely.”


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Effective Dose

The amount of a drug most people need to take to control a disease or the symptoms of a disease.  A dose lower than the effective dose would not bring about the outcome (such as relieving symptoms).


For example, the effective dose of ibuprofen for osteoarthritis pain relief is a 400 milligram tablet.


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Effectiveness

Whether a drug or other treatment works in real life.  Effectiveness studies of drugs look at whether they work when they are used the way that most people take them. Effectiveness means that most people who have the disease would improve if they used the treatment.


For example, antidepressant drugs are considered to be effective for the treatment of depression.  These drugs have been examined in many clinical trials and other types of research studies.


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Efficacy

Whether a drug or other treatment works under the best possible conditions.  In a research study about efficacy, the study participants are carefully selected, and the researchers can make sure the drug is taken properly and stored properly.  The study participants may differ from other people in the general public who have the disease.  A treatment that has efficacy under the best conditions may not work as well in a different group of people with the same disease.


For example, a recent clinical trial compared people treated with insulin to people treated with oral medicine for diabetes.  Only people with no other medical problems were enrolled in the study, and most were under age 65.  The people treated with insulin had better improvement in their blood glucose than the people treated with oral medicines.  This study is considered an efficacy study, because only younger people without any other health problems were included.  Many people who have diabetes are over age 65 and have other problems such as heart disease.  It is not known whether the same results would be found in these people.


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Epidemiology

The field of science that studies the factors causing diseases, illnesses, or injuries in populations or community groups.

Epidemiology includes:

  • Collecting information about how, where, and how often a disease or injury might occur.
  • Analyzing patterns and occurrences of illnesses or injuries.
  • Performing tests.
  • Using statistical methods to determine trends.
Epidemiology examines the natural history of a disease, the causes of disease, and ways to monitor disease in a community.  Clinical epidemiology evaluates diagnostic tests and factors that affect prognosis (the probable progression and outcome of an illness).


An example of clinical epidemiology is a study that evaluates the usefulness and accuracy of tests to find breast cancer.



Evidence Table

A summary of the most important information from a group of research studies.  An evidence table can include information on the number of participants in the research trials and the type and frequency of adverse events that participants had while taking the drugs being studied.


For example, evidence tables that contain information on the efficacy and safety of different treatments are included in systematic reviews.


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Evidence-Based Practice

Applying the best available research results (evidence) when making decisions about health care.  Health care professionals who perform evidence-based practice use research evidence along with clinical expertise and patient preferences. Systematic reviews (summaries of health care research results) provide information that aids in the process of evidence-based practice.


For example, a health care provider recommends acetaminophen to treat arthritis pain in a patient who has recently had stomach bleeding. The health care provider makes this recommendation because research shows that acetaminophen is associated with less risk for stomach bleeds than other common pain relievers. The health care provider’s recommendation is an example of evidenced-based practice.


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Exclusion Criteria

The criteria, or standards, set out before a study or review. Exclusion criteria are used to determine whether a person should participate in a research study or whether an individual study should be excluded in a systematic review. Exclusion criteria may include age, previous treatments, and other medical conditions. Criteria help identify suitable participants.


For example, researchers in a study of high blood pressure medicines might exclude pregnant women because of possible harms. Pregnancy would be an exclusion criterion for that study.


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External Validity

The extent to which clinical research studies apply to broader populations.  A research study has external validity if its results can be generalized to the larger population.


For example, researchers analyzed a group of studies to determine the effectiveness of diagnostic tests for breast cancer.  In general, the prevalence of breast cancer for women who undergo these tests is 20 percent.  The prevalence of breast cancer in most of the studies the researchers analyzed was 50 percent or higher.  These high prevalences suggested that the women studied were not typical of the general population.  Therefore the studies lacked external validity.


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Gold Standard Test

The diagnostic test that is considered the most accurate test for a particular condition.  If the gold standard test is positive, it is highly likely that the person has the disease.  If the gold standard test is negative, it is highly likely that the person does not have the disease. 


For example, a breast biopsy is considered the “gold standard” in breast cancer diagnosis. If a research study is trying to evaluate how accurate a test is for diagnosing breast cancer, results from the other test will be compared to the same person’s biopsy result.  The accuracy or inaccuracy of the other test is determined by whether or not it matches the result of the gold standard test.


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Head-to-Head Trial

A study of two drugs or treatments that compares the effects of one treatment with the other.  In a head-to-head trial, two groups of people with the same disease are compared.  One group receives one treatment, and the second group receives the other.


For example, a clinical trial that compares people treated with aspirin to people treated with salsalate for osteoarthritis pain is a head-to-head trial. 


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Health Care Intervention

Any type of treatment, preventive care, or test that a person could take or undergo to improve health or to help with a particular problem.  Health care interventions include drugs (either prescription drugs or drugs that can be bought without a prescription), foods, supplements (such as vitamins), vaccinations, screening tests (to rule out a certain disease), exercises (to improve fitness), hospital treatment, and certain kinds of care (such as physical therapy). 


For example, health care interventions for people with depression include the many different drugs that are available for the treatment of depression.  Counseling (without prescribing drugs) would also be a health care intervention for treating depression.



Heterogeneity

Differences among research studies.  Heterogeneity can apply to either the way the studies were conducted, the methodologies used in the studies, or differences in the way people respond to the treatment.  Research reports may describe different types of heterogeneity:

  • Statistical Heterogeneity — Differences in the effects of the treatment or intervention.
  • Methodological Heterogeneity — Differences in study design.
  • Clinical Heterogeneity — Differences in the characteristics of the participants, interventions, or outcome measures.


For example, if three clinical trials of a new drug were performed and only one of the trials found that the drug had efficacy, the results would show heterogeneity.  Careful review of the three studies would show whether the heterogeneity was probably caused by statistical heterogeneity, methodological heterogeneity, or clinical heterogeneity.



Human Subject

A person who participates in a research study or clinical trial. The person agrees to take part in the study and has been told about the possible dangers and benefits of participation. The participation can include different activities, depending on the goals of the study. 


For example, if a clinical trial is trying to determine the efficacy of different treatments for people with high blood pressure, the participants enrolled in the trial (human subjects) might be given medication, undergo blood tests or other medical procedures, or be given no treatment at all.


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Hypothesis

A scientific idea that can be tested in a research study.  The hypothesis is the scientific idea that led to the research study.


For example, the National Institutes of Health (NIH) sponsored a large study that tested the hypothesis that the combination of glucosamine and chondroitin brings better pain relief for people with arthritis of the knee than other common treatments for arthritis.



Inclusion Criteria

The criteria, or standards, set out before a study or review. Inclusion criteria are used to determine whether a person can participate in a research study or whether an individual study can be included in a systematic review. Inclusion criteria may include gender, age, type of disease being treated, previous treatments, and other medical conditions.  Inclusion criteria help identify suitable participants.


For example, researchers in a study of medicines for high blood pressure would enroll only people who have high blood pressure.  An inclusion criterion for this study would be having the diagnosis of high blood pressure.


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Informed Consent

An agreement to receive a treatment or medical procedure. Before a person receives a proposed treatment or medical procedure, he or she must give informed consent. This means that the person must not only agree to the treatment, but also understand what he or she is agreeing to.

Informed consent applies to routine health care, as well as to participation in a clinical research study.  Informed consent should always be received before a person undergoes a surgical procedure or before the use of dangerous treatments, such as chemotherapy for the treatment of cancer.

An informed consent form provides a record of the discussion that was held between the person and the doctor or researcher.  The person signs the informed consent form before a treatment or procedure is started and before any data are collected for people enrolled in a clinical research study.

Informed consent involves a discussion between a person who would receive the treatment and a professional person who explains the treatment, provides information about possible benefits and risks, and answers questions.  Informed consent involves the process of discussion about a treatment.  Signing the informed consent form provides a record of the discussion but does not take the place of the discussion.


For example, before a person gives ”informed consent” to participate in a clinical trial, the researcher must provide detailed information about the clinical trial. The purpose of the trial is explained, as well as:
  • The procedures involved, including how it will be decided what treatment the person will receive.
  • The risks and potential benefits.
  • The participant’s rights.


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Internal Validity

The extent to which the results of a clinical research study are not biased.  Several characteristics of a study affect its internal validity.  Are the two groups of people being compared similar in all the important characteristics that may affect the measurements of data?  Are the data collected being measured using accurate methods?


For example, a study was performed comparing people receiving a new type of surgical treatment to people who had received a different treatment in an earlier year.  The researchers concluded that the people who received the new treatment had less pain.  However, the method used to measure how much pain they had was different for the earlier year than for the new treatment.  This study was felt to have poor internal validity because of the difference in the method of measuring pain.


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Life Expectancy

The average amount of time a person will live after a certain starting point, like birth or the diagnosis of a disease.  The calculation is based on statistical information comparing people with similar characteristics, such as age, gender, race/ethnicity, and health.


For example, in the United States the life expectancy from birth for men and women combined is 78.1 years.  In England, it is 78.7, and in China it is 72.9 years.



Likelihood Ratio

A measure of the accuracy of a diagnostic test.  It is used to determine how likely it is that a person has a specific disease based on test results. When the test result is positive, the likelihood ratio is known as a positive likelihood ratio (LR+).  When the test result is negative, the likelihood ratio is known as a negative likelihood ratio (LR-).  The likelihood ratio is a way of comparing the probability that the test result would occur in people with the disease as opposed to occurring in people without the disease.

A positive likelihood ratio greater than 10 (>10) or a negative likelihood ratio less than 0.1 (<0.1) would be considered clinically useful in helping guide health care decision making.


For example, a diagnostic test called a large core needle biopsy, when used to diagnose breast cancer, has a positive likelihood ratio (LR+) of 16.2 and a negative likelihood ratio (LR-) of 0.03.


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Masking (Blinding)

A way of making sure that the people involved in a research study — participants, clinicians, or researchers — do not know which participants are assigned to each study group. Masking usually is used in research studies that compare two or more types of treatment for an illness. Masking is used to make sure that knowing the type of treatment does not affect a participant’s response to the treatment, a health care provider’s behavior, or assessment of the treatment effects.


For example, masking is usually done in a type of study known as a randomized controlled trial. The participants are considered “blinded” if they do not know whether they are taking the drug being researched or a placebo.  When neither the participants nor the researchers know who is taking the drug, the study is called “double-blinded.”


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Meta-Analysis

A way of combining data from many different research studies.  A meta-analysis is a statistical process that combines the findings from individual studies. 


For example, researchers wanted to know about the risk of stomach bleeding in people taking aspirin.  They did a meta-analysis of data from 24 clinical trials with nearly 66,000 participants and found that the risk of stomach bleeding was 2.47 percent with aspirin compared to 1.42 percent with placebo (inactive substance).


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Mortality

The number of people who die.  Mortality is usually measured for people who have something in common, such as having a particular disease or being of a certain age. 

Mortality for a group of people is often reported as the number of people who died and the causes of the deaths.  Even people who have the same medical problem do not always have the same cause of death.  A person may die from a disease or from another cause, such as an automobile crash. 


Researchers studied the mortality of men who had their prostate gland removed as treatment for prostate cancer.  After 10 years, 27 percent of all the men had died, but only 10 percent had died because of prostate cancer instead of some other cause.


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Negative Predictive Value

Indicates the likelihood that people with a negative test result would not have a condition.  The higher the value of the negative predictive value (for example, 99 percent would usually be considered a high value), the more useful the test is for predicting that people do not have the condition.


For example, the negative predictive value (PV-) of a normal Prostate Specific Antigen (PSA) test in prostate cancer screening is about 98 percent. It is very unlikely that men with a normal PSA test result on routine screening have the disease.



Number Needed to Harm

The number of people who would need to be treated over a specific period of time before one bad outcome of the treatment will occur.  The number needed to harm (NNH) for a treatment can be known only if clinical trials of the treatment have been performed.


For example, a meta-analysis looked at the risk of death for people with Alzheimer’s disease who were taking atypical antipsychotic medication.  The researchers found that for every 100 people with Alzheimer’s disease using atypical antipsychotic medication, there was one additional death compared to 100 people with Alzheimer’s disease using placebo (Number Needed to Harm=100).


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Number Needed to Treat

The number of people who need to be treated over a specific period of time to promote one additional good outcome (or prevent one additional bad outcome). The number needed to treat (NNT) for a treatment can be known only if clinical trials of the treatment have been performed. 


For example, a clinical research study compared two anti-ulcer drugs for treating gastroesophageal reflux disease (GERD).  It found that for every 10 people treated with drug A, 9 had relief of their symptoms.  For every 10 people treated with drug B, 8 had relief of their symptoms.  The study concluded that, if 10 people were switched from drug B to drug A, the number who had relief of symptoms would increase from 8 to 9.  This means that one more person would obtain relief for every 10 who had the medicine switched (Number Needed to Treat = 10). 


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Odds Ratio

The chance of an event occurring in one group compared to the chance of it occurring in another group. The odds ratio (OR) is a measure of effect size and is commonly used to compare results in clinical trials.


For example, a research study compared two groups of women who developed diabetes during their pregnancies.  One group was treated with metformin, and the other group was treated with insulin.  The researchers recorded how many of the mothers delivered their babies earlier than expected (less than 37 weeks after becoming pregnant).  When they calculated the odds of an early delivery, the odds ratio (OR) for metformin was 1.06.  This means that the women taking metformin had a small increase (1.06 times) in the odds of having an early delivery compared to the women taking insulin.


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Off-Label Use

The practice of prescribing a drug for a condition not listed on the U.S. Food and Drug Administration (FDA) label.  The label lists the medical conditions for which the FDA has approved the drug.  Off-label uses may be supported by clinical evidence not available or not submitted to the FDA.  Accepted medical practice often includes off-label use.


For example, a group of drugs known as atypical antipsychotic agents is approved by the FDA for the treatment of schizophrenia.  Clinical research studies have shown that these drugs can improve symptoms of another psychiatric disorder known as obsessive-compulsive disorder (OCD).  Using an atypical antipsychotic drug to treat OCD is considered an off-label use of the drug. 


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Open-Label Study

A clinical research study in which the participant, health care professional, and others know the drug and dose being given.  The research study is not “blinded.”


For example, during the very early testing of drugs or devices, studies are usually open label.  These tests are conducted on a small number of persons to determine whether the drug appears to have acceptable safety and effectiveness for the medical condition being studied.


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OTC (Over-the-Counter)

A term used to describe drugs you can buy without a prescription.


For example, nonprescription (OTC) pain relievers include acetaminophen, aspirin, ibuprofen, supplements (glucosamine and chondroitin), and topical capsaicin cream.


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Outcome

The end result of health care practices.  There are many kinds of outcomes.  How long people live following a health care treatment is one kind of outcome, known as survival. Other outcomes measure the effects a treatment has on people’s lives, such as changes in their ability to function or changes in their quality of life. Outcomes also include undesirable events such as side effects of drugs.  Another type of outcome is whether people needed to change to another kind of treatment.


Researchers studied the outcomes of treatment for coronary artery disease.  They examined how long people lived after the treatments.  They also examined how many people had chest pain or heart attacks after the treatments.



Over-the-Counter (OTC)

A term used to describe drugs you can buy without a prescription.


For example, nonprescription (over-the-counter) pain relievers include acetaminophen, aspirin, ibuprofen, supplements (glucosamine and chondroitin), and topical capsaicin cream.


See Also






Patient

An individual seeking or receiving medical care. 


Anyone who is provided treatment or advice by a health care professional is considered a patient.



Placebo

An inactive substance commonly called a “sugar pill.” In a clinical trial, a placebo is designed to look like the drug being tested and is used as a control.  It does not contain anything that could harm a person. 

It is not necessarily true that a placebo has no effect on the person taking it.  See placebo effect.


For example, a group of studies showed that 54 percent of people using topical capsaicin for arthritis pain relief had skin irritation, compared to 15 percent of people using placebo.  The placebo was a cream that looked identical to topical capsaicin but was made with inactive ingredients that had no potential for producing irritation. 


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Placebo Controlled Study

A study in which the effect of a drug is compared with the effect of a placebo (an inactive substance designed to resemble the drug).  In placebo controlled clinical trials, participants receive either the drug being studied or a placebo.  The results of the drug and placebo groups are then compared to see if the drug is more effective in treating the condition than the placebo is.


For example, two placebo controlled studies have compared the drug risperidone with a placebo for treating behavioral problems in children having the diagnosis of autism.  Both studies found that the children given risperidone had fewer behavioral problems than the children given a placebo.


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Placebo Effect

A physical or emotional change that occurs after a participant in a research study takes a placebo.  The change, which may include the lessening of symptoms, is not the result of chemical effects of the placebo because the placebo does not contain any active ingredients.  The change is often based on the participant’s or researcher’s expectation that a change will occur.


In a large research study of people with arthritis of the knee, one group of participants took a placebo pill.  Sixty percent of these people reported improvement in their pain and functioning while taking the pill.  This clinical improvement was considered to be a placebo effect.


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Pooled Odds Ratio

When the data on odds ratios from multiple studies are combined, the result is a pooled odds ratio (POR). An odds ratio (OR) is the comparison of the chance of an event occurring in one group to the chance of it occurring in another group. The odds ratio is a measure of effect size and is commonly used to compare results in clinical trials.


For example, researchers looked at the results of five different studies that compared using a particular drug for treating depression with using a placebo (inactive substance) to treat depression.  They looked at the amount of weight gain in the people taking the drug compared to the people taking a placebo.  When they calculated the odds of weight gain from each of the studies, the pooled odds ratio (POR) for this particular drug was 11.16.  This means that the people taking the drug had more than 11 times the odds of gaining weight compared to the people who were taking a placebo.


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Positive Predictive Value

Indicates the likelihood that a person with a positive test result would actually have the condition for which the test is used. The higher the value of the positive predictive value (for example, 90 percent would be considered a high value), the more useful the test is for predicting that the person has the condition.


For example, the positive predictive value (PV+) of mammography in breast cancer screening has been estimated to be less than 30 percent. For every 100 people who have something discovered on their mammogram that looks like cancer, it will turn out actually to be cancer in less than 30 of those people.


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Pretest Probability (Prior Probability)

The probability that a person has a particular disease before any test results are obtained.  The pretest probability for large groups of people (such as the population of a city) is the same as the prevalence of the disease in that group.

Pretest probability is also known as prior probability.


For example, breast biopsy is a highly accurate test for finding out whether a breast lump is breast cancer.  The pretest probability of breast cancer in a group of women who have been referred for breast biopsy is estimated to be 20 percent.  This means that a person who has a biopsy because of a suspicious breast lump has a 20 percent chance that the breast lump will be cancerous even before the test is performed.


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Prevalence

How often or how frequently a disease or condition occurs in a group of people. Prevalence is calculated by dividing the number of people who have the disease or condition by the total number of people in the group.


For example, health leaders in a community were concerned that some women were not receiving health care and therefore did not know they had serious problems.  The health leaders began a breast cancer screening program.  Women were encouraged to come into a community clinic and have breast examinations.  In this example, out of 1,000 women, 20 had breast cancer.  Therefore, the prevalence of breast cancer in women who undergo screening for breast cancer is 20/1000, or 2 percent.



Prior Probability (Pretest Probability)

The probability that a person has a particular disease before any test results are obtained.  The prior probability for large groups of people (such as the population of a city) is the same as the prevalence of the disease in that group.

Prior probability is also known as pretest probability.


For example, breast biopsy is a highly accurate test for finding out whether a breast lump is breast cancer.  The prior probability of breast cancer in a group of women who have been referred for breast biopsy is estimated to be 20 percent.  This means that a person who has a biopsy because of a suspicious breast lump has a 20 percent chance that the breast lump will be cancerous even before the test is performed.


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Probability

The likelihood (or chance) that an event will occur.  In a clinical research study, it is the number of times a condition or event occurs in a study group divided by the number of people being studied. 


For example, a group of adult men who had chest pain when they walked had diagnostic tests to find the cause of the pain.  Eighty-five percent were found to have a type of heart disease known as coronary artery disease.  The probability of coronary artery disease in men who have chest pain with walking is 85 percent. 



Prognosis

The way a health situation is likely to turn out. Prognosis refers to the usual progression and outcome of a condition.


For example, breast cancer mortality rates can be significantly reduced by identifying cancers at earlier stages.  Early detection and treatment of breast cancer gives a better chance of a full recovery or cure.  The prognosis of breast cancer that is detected and treated early is better than the prognosis of breast cancer that is detected late.



Prospective Observational Study

A clinical research study in which people who presently have a certain condition or receive a particular treatment are followed over time and compared with another group of people who are not affected by the condition.

In a prospective observational study (also called a cohort study), the researchers take measurements of the people who belong to a cohort at several points in time.  The measurements can be symptoms, blood tests, X-rays, or whether the disease has caused the person to die.


For example, the Women’s Health Initiative is a prospective observational study that collects information from a group of older women who are followed over several years.


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Publication Bias

The tendency of researchers to publish experimental findings that have a positive result, while not publishing the findings when the results are negative or inconclusive.  The effect of publication bias is that published studies may be misleading.  When information that differs from that of the published study is not known, people are able to draw conclusions using only information from the published studies.


For example, two research studies of a new drug are being conducted.  One study finds that people with a certain disease improve while taking the drug.  The second study finds that people with the same disease do not improve while taking the drug.  If the first study is published but the second is not, then publication bias has occurred.  If both studies are published, then publication bias has not occurred. 



Randomization

A method of assigning participants in clinical trials into two or more groups randomly (by chance).  One group receives the treatment or drug being researched, and one group receives either no treatment, a placebo (inactive substance), or another drug.  Participants are assigned to a group by various methods. 


For example, researchers wanted to use randomization in a new study.  The researchers decided to flip a coin for each new study participant and assign the person to the first group if the coin is heads and to the second group if the coin is tails.
Researchers usually use other techniques than a coin flip.  A method called a random numbers table is often used.



Randomized Controlled Trial

A controlled clinical trial that randomly (by chance) assigns participants to two or more groups. There are various methods to randomize study participants to their groups.


An example is a randomized controlled trial (RCT) to understand whether calcium tablets work to prevent broken bones in women with low bone density. Women with low bone density are randomly assigned to one of two groups. One group receives calcium and the control group receives a placebo (inactive substance).  The numbers of women who suffer fractures in each group are compared to find out whether calcium works.


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Relative Risk

A comparison of the risk of a particular event for different groups of people.  Relative risk (RR) is usually used to estimate exposure to something that could affect health. In a clinical research study, the experimental group is exposed to a particular drug or treatment. The control group is not.  The number of events in each group is compared to determine relative risk. 


For example, researchers analyzed information from a group of different studies that looked at the number of people who had stomach bleeding when taking the drug ibuprofen.  They found that people who took ibuprofen had stomach bleeds 2½ times more often than those who did not take ibuprofen.  The relative risk of having stomach bleeding while taking ibuprofen was 2.5 (RR 2.5) in these studies.


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Risk

A way of expressing the chance that something will happen.  It is a measure of the association between exposure to something and what happens (the outcome).  Risk is the same as probability, but it usually is used to describe the probability of an adverse event.  It is the rate of events (such as breast cancer) in the total population of people who could have the event (such as women of a certain age).


For example, the risk of a woman developing invasive breast cancer at some time in her life is about 1 in 8, or 13 percent.


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Risk Factor

A characteristic of a person that affects that person’s chance of having a disease.  A risk factor may be an inherent trait, such as gender or genetic make-up, or a factor under the person’s control, such as using tobacco.  A risk factor does not usually cause the disease.  It changes a person’s chance (or risk) of getting the disease. 


For example, among people taking non-steroidal anti-inflammatory drugs (NSAIDs), the risk for stomach bleeding increases with age.  This means that higher age is a risk factor.  Other risk factors for stomach bleeding with NSAIDs include use of anticoagulant medicines ("blood thinners") and having had stomach bleeding in the past. 


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Risk/Benefit Ratio

A method for comparing a treatment’s benefits and risks, such as curing a disease (benefit) versus having a serious side effect from the treatment (risk).  The risk/benefit ratio of a treatment is different depending on the disease or condition being treated. 


For example, some types of pneumonia often are fatal if not treated but can be cured with antibiotic medications.  Antibiotics have a low rate of adverse events.  The risk/benefit ratio of antibiotic treatment for serious pneumonia is low.  This means that the risk of an adverse event is low compared to the probability of improvement from the treatment.



Sample Size

The number of people included in a study.  In research reports, sample size is usually expressed as “n.” In general, studies with larger sample sizes have a broader range of participants.  This increases the chance that the study’s findings apply to the general population.  Larger sample sizes also increase the chance that rare events (such as adverse effects of drugs) will be detected. 


For example, for an analysis of the side effects of atypical antipsychotic drugs, the researchers decided to include only studies with a sample size of 1,000 or more people (n > 1,000).


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Screening

Using tests or other methods of diagnosis to find out whether or not a person has a specific disease or condition before it causes any symptoms.  For many diseases (for example, cancers), starting treatment earlier leads to better results.  The purpose of screening is to find the disease so that treatment can be started as early as possible.


For example, a breast exam and a mammogram are both screening tests used to find small breast cancers.


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Selection Bias

A type of bias caused by an error in the way people are assigned to groups in a clinical research study. This can occur when the study and control groups are chosen so that they differ from each other in ways that may affect the outcome of the study.


For example, a research study compared rates of side effects in men who received surgical removal of the prostate with rates in men who received radiation therapy for prostate cancer.  The men in the two groups differed in their age and the rates of other medical problems.  Because of this selection bias, differences in the side effect rates may not be due just to the effects of the type of treatment. 


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Sensitivity (True-Positive Rate)

The ability of a test to identify correctly people with a condition. A test with high sensitivity will nearly always be positive for people who have the condition (the test has a low rate of false-negative results).  Sensitivity is also known as the true-positive rate.


For example, researchers looked at 10 studies that evaluated the sensitivity of MRI (magnetic resonance imaging) for diagnosing cancer in people who had suspicious breast lumps.  Out of every 100 people whose breast lumps were eventually found to be cancerous, 92 had positive MRI tests.  In these studies, the sensitivity of MRI was 92 percent.


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Side Effects

Any effects of a drug or treatment that are not wanted. Side effects may be temporary and go away when the drug is stopped.  Sometimes they continue for a longer time, even when the drug is no longer being taken. 


For example, headache, nausea, hair loss, and skin irritation are side effects that commonly occur with drugs.


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Specificity (True-Negative Rate)

The ability of a test to identify correctly people without a condition. A test with high specificity will rarely be wrong about who does NOT have the condition (the test has a low rate of false-positive results).  Specificity is also known as the true-negative rate.


For example, researchers looked at 10 studies that evaluated the specificity of MRI (magnetic resonance imaging) for diagnosing cancer in people who had suspicious breast lumps. Out of every 100 people whose breast lumps were eventually found not to cancerous, 72 had negative MRI tests. In these studies, the specificity of MRI was 72 percent.


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Standard Treatment

The treatment or procedure that is most commonly used to treat a disease or condition.  In clinical trials, new or experimental treatments sometimes are compared to standard treatments to measure whether the new treatment is better.


For example, the standard treatment for anemia (low blood iron) is iron pills.



Statistical Analysis (Analysis)

The process of preparing the results or conclusion of a study.  A statistical analysis usually is performed by doing mathematical calculations known as statistics.


For example, in a research study to find out whether a drug works to increase bone density, the statistical analysis would look at the data for each group of people in the study and compare the results.  It might examine whether the people taking the drug had fewer broken bones than people who had not taken the drug. 


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Statistical Significance

A mathematical technique to measure whether the results of a study are likely to be true.  Statistical significance is calculated as the probability that an effect observed in a research study is occurring because of chance.  Statistical significance is usually expressed as a P-value.  The smaller the P-value, the less likely it is that the results are due to chance (and more likely that the results are true).  Researchers generally believe the results are probably true if the statistical significance is a P-value less than 0.05 (p<.05).


For example, results from a research study indicated that people who had dementia with agitation had a slightly lower rate of blood pressure problems when they took Drug A compared to when they took Drug B.  In the study analysis, these results were not considered to be statistically significant because p=0.2.  The probability that the results were due to chance was high enough to conclude that the two drugs probably did not differ in causing blood pressure problems.


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Study

A research process in which information is recorded for a group of people. The information is known as data.  The data are used to answer questions about a health care problem.


For example, a clinical trial is one type of a study.


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Study Population

The group of people participating in a clinical research study.  The study population often includes people with a particular problem or disease.  It may also include people who have no known diseases. 


For example, to compare the effectiveness of different treatments for gastroesophageal reflux disease (GERD), researchers analyzed how the treatments affected rates of heartburn.  The study population was adults with chronic acid reflux (GERD).



Survival

The length of time people live.  Survival can show whether treatments for a disease can prevent or delay death. Survival is usually expressed in terms of how long the people in a group remain alive.  It sometimes is summarized by calculating an average.  Survival also can be summarized by the number of people who are still alive after a certain length of time, such as 5 years later.


Researchers examined the survival of people who had treatment for coronary artery disease.  Of those people who also had diabetes, 87 percent were still alive after 3 years.  Of those who did not have diabetes, 95 percent were still alive after 3 years.


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Systematic Review

A summary of the clinical literature.  A systematic review is a critical assessment and evaluation of all research studies that address a particular clinical issue.  The researchers use an organized method of locating, assembling, and evaluating a body of literature on a particular topic using a set of specific criteria.  A systematic review typically includes a description of the findings of the collection of research studies.  The systematic review may also include a quantitative pooling of data, called a meta-analysis.

A comparative effectiveness review is a type of systematic review in which all the available evidence about particular treatments for a disease is reviewed and compared.


Scientists collected all the published studies that compared types of treatment for prostate cancer that had not spread beyond the prostate gland.  They compiled the results of these studies in a comparative effectiveness review, which is a type of systematic review.


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Treatment Effect (Effect Size)

The amount of change in a condition or symptom because of a treatment (compared to not receiving the treatment).  It is commonly expressed as a risk ratio (relative risk), odds ratio, or difference in risk.


For example, in studies about side effects for antipsychotic drugs, researchers found that these drugs were three times more likely to cause drowsiness than a placebo. The odds ratio was 3.0, meaning the treatment effect was “three times as likely.”


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True-Negative Rate (Specificity)

The ability of a test to identify correctly people without the condition. A test with a high true-negative rate will rarely be wrong about who does NOT have the condition (the test has a low rate of false-positive results). The true-negative rate is also known as specificity .


For example, researchers looked at 10 studies that evaluated the specificity of MRI (magnetic resonance imaging) for diagnosing cancer in people who had suspicious breast lumps.  Out of every 100 people whose breast lumps were eventually found not to cancerous, 72 had negative MRI tests.  In these studies, the true-negative rate of MRI was 72 percent.


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True-Positive Rate (Sensitivity)

The ability of a test to identify correctly people with a condition. A test with a high true-positive rate will will nearly always be positive for people who have the condition (the test has a low rate of false-negative results).  The true-positive rate is also known as sensitivity.


For example, researchers looked at 10 studies that evaluated the sensitivity of MRI (magnetic resonance imaging) for diagnosing cancer in people who had suspicious breast lumps.  Out of every 100 people whose breast lumps were eventually found to be cancerous, 92 had positive MRI tests.  In these studies, the true-positive rate of MRI was 92 percent.


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Validity

Whether a test or technique actually measures what it is intended to measure. Validity can refer to an individual measurement or to the design and approach taken in a clinical research study. When referring to a single measurement, validity means the accuracy of the measurement. 


For example, obtaining a blood pressure measurement has validity if the blood pressure device works correctly and the person using the device knows how to use it properly.


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Variable

Any characteristic that can be measured in different individuals.  A variable is also any factor that can affect the outcome of an experiment or study.

Research studies have both independent and dependent variables. A dependent variable is the change or outcome that results from an independent variable. Independent variables, such as receiving an experimental treatment, can be changed by the researchers. 


For example, a clinical trial found that a nonsteroidal anti-inflammatory (NSAID) drug is better than acetaminophen for osteoarthritis pain relief.  In this study, whether a study participant received the NSAID drug or acetaminophen is an independent variable, and the amount of pain relief is a dependent variable.