File Name: sensitivity and specificity example questions .zip
- Sensitivity, Specificity, and Relatives
- Estimating Prevalence Using an Imperfect Test
- Remembering the meanings of sensitivity, specificity, and predictive values
A comprehensive collection of clinical examination OSCE guides that include step-by-step images of key steps, video demonstrations and PDF mark schemes. A comprehensive collection of OSCE guides to common clinical procedures, including step-by-step images of key steps, video demonstrations and PDF mark schemes. A collection of communication skills guides, for common OSCE scenarios, including history taking and information giving. A collection of data interpretation guides to help you learn how to interpret various laboratory and radiology investigations.
Sensitivity, Specificity, and Relatives
Within the context of screening tests, it is important to avoid misconceptions about sensitivity, specificity, and predictive values. In this article, therefore, foundations are first established concerning these metrics along with the first of several aspects of pliability that should be recognized in relation to those metrics. Clarification is then provided about the definitions of sensitivity, specificity, and predictive values and why researchers and clinicians can misunderstand and misrepresent them. Diagnostic tests are regarded as providing definitive information about the presence or absence of a target disease or condition. By contrast, screening tests—which are the focus of this article—typically have advantages over diagnostic tests such as placing fewer demands on the healthcare system and being more accessible as well as less invasive, less dangerous, less expensive, less time-consuming, and less physically and psychologically discomforting for clients. Screening tests are also, however, well-known for being imperfect and they are sometimes ambiguous.
Screening refers to the application of a medical procedure or test to people who as yet have no symptoms of a particular disease, for the purpose of determining their likelihood of having the disease. The screening procedure itself does not diagnose the illness. Those who have a positive result from the screening test will need further evaluation with subsequent diagnostic tests or procedures. The goal of screening is to reduce morbidity or mortality from the disease by detecting diseases in their earliest stages, when treatment is usually more successful. Sensitivity and specificity are measures of a test's ability to correctly classify a person as having a disease or not having a disease.
Example: Cascell's Problem. We want to know how likely it is that the individual with a positive test result will actually suffer from the disease. In other words, we want to know the positive predictive value of the test:. It is important to be able to quantify how a test result increases the diagnostic ability of a test i. The best way to demonstrate this is through a past exam question:.
Estimating Prevalence Using an Imperfect Test
Margaret, Pittsburgh, Pa. The 2 x 2 tables from which these terms are derived are familiar to some physicians Table. Sensitivity and specificity are fixed for a particular type of test. For example, though current screening tests for HIV have high sensitivity and specificity, the low prevalence of HIV in the general population cannot justify universal screening since the majority of positive tests would be falsely positive ie, low PPV. Begin by assuming that you have 4 patients. For the first 2 you know only their disease status; for the last 2 patients you know only their test result. Keeping these 4 questions in mind as you run across these frequently used terms will help you interpret diagnostic tests accurately and efficiently, without having to think about more awkward 2 x 2 tables.
The table below shows the results from looking at the diagnostic accuracy of a new rapid test for HIV in , subjects, compared to the Reference standard ELISA test. The rows of the table represent the test result and the columns the true disease status as confirmed by ELISA. Please remember to click the Submit button for each separate question, and read the feedback comments! What is the Sensitivity of the new rapid test for HIV? Report the answer to 3 decimal places. The answer is 0. What is the Specificity of the new rapid test for HIV?
In this article, we have discussed the basic knowledge to calculate sensitivity, specificity, positive predictive value and negative predictive value. We have discussed the advantage and limitations of these measures and have provided how we should use these measures in our day-to-day clinical practice. We also have illustrated how to calculate sensitivity and specificity while combining two tests and how to use these results for our patients in day-to-day practice. Modern ophthalmology has experienced a dramatic increase in knowledge and an exponential increase in technology. Regrettably, there is sometimes a tendency to use tests just because they are available; or because they are hi-tech. The basic idea of performing a diagnostic test is to increase or decrease our suspicion that a patient has a particular disease, to the extent that we can make management decisions.
PDF. Multiple-choice questions. Multiple choice questions in evidence based medicine Applying to a patient seen in general practice with a positive test: Sensitivity and specificity are characteristics of a diagnostic test and do not change.
Remembering the meanings of sensitivity, specificity, and predictive values
Peter J. The standard estimate of prevalence is the proportion of positive results obtained from the application of a diagnostic test to a random sample of individuals drawn from the population of interest. When the diagnostic test is imperfect, this estimate is biased.
Statistics for Bioengineering Sciences pp Cite as. This chapter introduces several notions fundamental for disease or device testing. Unable to display preview. Download preview PDF. Skip to main content.
RIS file. Properties of diagnostic tests have traditionally been described using sensitivity, specificity, and positive and negative predictive values. These measures, however, reflect population characteristics and do not easily translate to individual patients.
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