Clinical significance

Clinical significance is a measurement used in medicine and psychology to determine whether a treatment, disease, or disorder has noticeable effects for patients. Most often, clinical significance refers to the effect a drug or treatment has on a disease or disorder. If the drug or treatment has a clinical significance, it has a real, noticeable effect for patients using it. Clinical significance is often measured during a trial in which researchers collect data and monitor the effectiveness of a drug or treatment.

Background

Clinical significance is often used to measure the effectiveness of a particular drug or treatment that is being tested. Researchers conduct different studies to test the effectiveness of a certain drug or treatment. One type of study that medical researchers take part in is a clinical study. Clinical studies examine treatments and procedures in a specific population. Some clinical studies measure the effects of treatments. Researchers observe participants to track the effectiveness of the treatment and to watch for any side effects. During a clinical study, researchers will collect data. The researchers analyze the data and determine whether the drug or treatment is effective and safe. The researchers have to decide whether the results are significant enough to matter to patients. Researchers measure statistical and clinical significance to understand the effect of a particular treatment.

Overview

Once researchers have a set of data, they look at its statistical significance. The statistical significance shows researchers if the changes observed during a trial are due to random chance or due to the drug or treatment being tested. Researchers have to choose a value for the statistical significance before they begin the test and collect their data. For example, a group of researchers chooses 5 percent as their statistically significant value. The researchers' data show that a treatment was effective 15 percent of the time. Therefore, the researchers could say that the observed changes were most likely due to the treatment and not due to random chance. This means the findings are statistically significant.

Once researchers have decided if a treatment's effects are statistically significant, they have to determine if the effects are clinically significant. Just as researchers choose the value of statistical significance, they also choose the value of clinical significance. The value that researchers choose for clinical significance can vary. Researchers and doctors must decide how to measure the effect that they consider to be significant. To some researchers, clinical significance occurs when patients are cured. For example, researchers might measure clinical significance with the percentage of trial participants who were cured with a treatment. To some researchers, clinical significance can be achieved by reducing symptoms. For example, researchers might measure the percentage of trial participants who experienced a 50 percent reduction in symptoms with a treatment. Clinical significance can be measured in many different ways. Researchers and medical professionals have to decide what the threshold for clinical significance will be for a particular study.

One important aspect of determining clinical and statistical significance is the sample size of the trial. A very small sample size increases the likelihood that the results are due to chance. That happens because the results of a trial with a small sample size can be greatly skewed by one or two participants. Therefore, researchers conducting trials with small sample sizes should be aware that the statistical significance might be skewed by the sample size. However, if the same small-sample-size trial is conducted and shows a significant clinical significance (e.g., people in the trial saw dramatic improvement in their conditions), researchers should still take the clinical significance into account. These researchers might consider conducting a larger trial with more participants based on the clinical significance of the smaller trial. The larger trial will improve the conditions for accurately measuring statistical significance, and it will give the researchers another chance to track the clinical significance.

Although clinical significance is often used in the context of medical research, the term is also used to describe other measurements in medicine. A clinician or doctor can use the term to describe whether a particular treatment is effective enough to use on a particular patient. For example, a doctor might want to reduce a patient's pain. Treatment A could reduce the pain by 3 percent. The doctor and patient may decide that Treatment A does not have enough clinical significance to be administered. Treatment B could reduce the pain by 80 percent. The doctor and patient may decide that treatment is clinically significant enough to be administered. Medical professionals may also take into account side effects of treatments. For example, a patient who is at risk for a stroke could be treated with Drug A or Drug B. Drug A is safe but reduces strokes by only 20 percent. Drug B has a number of side effects but reduces strokes by 70 percent. If the patient is at very high risk for a stroke, the doctor may decide that Drug B is clinically significant, despite the risks. Doctors may also consider a treatment's effects on a person's quality of life when determining its clinical significance.

Clinical significance can also be used to measure the effect of a disease or impairment. For example, doctors involved in mental health may try to determine if a patient experiencing symptoms of mental illness requires medical intervention. Nearly all people experience symptoms of depression, insomnia, disorganized thinking, or anxiety at some point in their lives. A person who experiences insomnia for a short time may not require medical intervention. However, if a person experiences anxiety, insomnia, or depression for weeks or months, that person likely has a clinically significant mental illness and may require medical intervention. This is another example in which medical professionals and patients have to determine what is clinically significant. However, in this case the definition of clinical significance is based on experience and observations rather than on collected data.

Bibliography

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