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The absolute difference in rates of an outcome between treatment and control groups in a clinical trial.
For example, a clinical trial compares the effect of a new statin and placebo on the incidence of stroke. Over the course of the study, the incidence of stroke is 4% with the statin and 6% with placebo. The absolute risk reduction with the statin is 2%.
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.
The 95% CI is the range within which 95% of results would be expected to fall, based on the one experiment conducted, were the experiment to be replicated multiple times.
A third factor in a study that affects the statistical relationship between the other two factors. A confounding variable can make it appear that there is a direct relationship between two factors when, in reality, the confounder is responsible for the relationship.
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.
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.
In this study design, each patient receives both treatments. There is less variability in outcomes because the patient serves a his/her own control. Reduced variability means a smaller sample size is needed than for a parallel-group trial. The two phases of the study are usually separated by a washout period. Crossover studies are susceptible to period effects - differences in the effectiveness of a drug due to the passage of time. Period effects can be attributed to the development of tolerance or resistance, learning effects, or changes in the course of the disease being treated.
The outcome that is used to measure drug efficacy in a clinical trial.
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.
Health technology assessment considers the effectiveness, appropriateness and cost of technologies. It does this by asking four fundamental questions: Does the technology work, for whom, at what cost, and how does it compare with alternatives?
In a meta-analysis or systematic review, when the results of individual studies are compatible with one another they are considered to be homogenous. Heterogeneity occurs when there is more variation between the study results than would be expected to occur by chance alone. A test for heterogeneity helps determine if it's appropriate to combine studies.
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).
The number of patients treated with a specific therapy in order for one of them to have a bad outcome.
The number of patients needed to treat with a specified therapy in order for one patient to benefit from treatment. The NNT is the inverse of the absolute risk reduction (1/absolute risk reduction).
An odds ratio can be used to determine risk in case control studies, as well as prospective cohort studies. In case control studies, the odds ratio is the odds of exposure in cases divided by the odds of exposure in controls. In cohort studies, it is the ratio of the odds of the outcome in the treatment group compared to the odds of the outcome in the control group. Odds ratios and relative risk are comparable when the outcome is rare. But the odds ratio can make risk appear greater when the disease or outcome is more common. In case-control studies evaluating the risk of an adverse effect, an odds ratio of 1 indicates that exposure to the drug is equally likely in cases and controls. If the odds ratio is greater than 1, the risk of exposure is greater in cases than controls. If the odds ratio is less than 1, the risk of exposure is smaller in cases than controls.
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."
The level of statistical significance. A value of p<0.05 means that the probability that the result is due to chance is less than 1 in 20. The smaller the p-value, the greater the statistical significance. The p-value does not provide any information about the size of an effect. It only describes the strength of the result.
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.
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.
Proportion of people who actually have the disease when a diagnostic test is positive. 100 × true positive/true positive + false positive.
A prospective study in which patients are randomized into treatment or control goups. These groups are followed up for the variables/outcomes of interest.
The risk of an event in individuals with a particular characteristic compared with the risk of that event in individuals who don't have that characteristic. In a clinical trial, this is the probability of an event in the treatment group divided by the probability of that event in the placebo group.
The ability of a test to reliably detect the presence of a disease. The proportion of patients with the disease who have a positive test. Sensitivity = 100 × true negatives/true negatives + false positives.
The ability of a diagnostic test to reliably rule out a disease. The proportion of patients without the target disease who have a negative test. Specificity = 100 × true negatives/true negatives + false positives.
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.
The soundness of rigour of a study. A study is internally valid if the way it is designed and carried out means that the results are unbiased and it gives you an accurate estimate of the effect that is being measured. A study is externally valid if its results are applicable to people encountered in regular clinical practice.
