Sensitivity And Specificity Understanding Example Questions Pdf

sensitivity and specificity understanding example questions pdf

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In this article, we have discussed the basic knowledge to calculate sensitivity, specificity, positive predictive value and negative predictive value.

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.

Understanding and using sensitivity, specificity and predictive values

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. It is, therefore, important to determine the extent to which these tests are able to identify the likely presence or absence of a condition of interest so that their findings encourage appropriate decision making.

If practitioners are confident when using screening tests, but their confidence is not justified, the consequences could be serious for both individuals and the healthcare system 1 , 2. It is important, therefore, that confusion should be avoided with regard to how the adequacy and usefulness of screening tests are determined and described. In this article, an attempt is made to identify why confusion can exist, how it might be resolved, and how, once resolved, improvements could be made with regard to the description and use of screening tests.

The focus is on the sensitivity, specificity, and predictive values of those tests. When the adequacy, also known as the predictive power or predictive validity, of a screening test is being established, the outcomes yielded by that screening test are initially inspected to see whether they correspond to what is regarded as a definitive indicator, often referred to as a gold standard, of the same target condition.

The analyses are typically characterized in the way shown in Figure 1. Because there can be concerns about the validity of these so-called gold standards 3 , 4 , they have increasingly been referred to less glowingly as reference standards 5 , thus removing what seemed to be unreserved endorsement. That wording i. Figure 1.

Diagram demonstrating the basis for deriving sensitivity, specificity, and positive and negative predictive values. Independent of the categorization established on the basis of the reference standard, people are also assessed on the screening test of interest. That test might comprise a natural dichotomy or it might be based on whether the test outcomes fall below or above a specified cutoff point on a continuum.

It might also comprise a battery of tests that, together, are regarded as a single test 6 — 8. Based on their reference standard and screening test results, people are assigned to one of the four cells labeled a through d in Figure 1 depending on whether they are definitely regarded as having or as not having the target condition based on the reference standard, and whether the screening test yielded a positive result the person appears to have the condition or a negative result the person appears not to have the condition.

What are referred to as sensitivity, specificity, and predictive values can then be calculated from the numbers of people in each of the four cells, and, if expressed as percentages, are based on the following formulas:. These are the metrics that are cited—i. The simplicity, and even familiarity, of these four metrics can mask the existence of a number of complexities that sometimes appear to be underappreciated, however.

Deficiencies in either the reference standard or the screening test, or in both, can exist. Furthermore, the four metrics should not be regarded as unquestionably valid and fixed attributes of a screening test: the values that are entered into the cells of Figure 1 depend on how stringent the screening test is and the prevalence of the target condition in the sample of people used in the analysis. Because of these complexities, it is sometimes necessary to examine the validity of measurement procedures within both the reference standard and the screening test 3 , 8.

It might also be necessary to question the stringency of the screening test and to ensure that there is a match between the samples that were used for assessing a screening test and the people subsequently being screened 2 , 3 , 9 — It is also important to recognize that there are sometimes noticeable tradeoffs between sensitivity and specificity, as well as between positive predictive values PPVs and negative predictive values NPVs.

This is demonstrated in the first four rows of entries in Table 1. Furthermore, as also illustrated in Table 1 , there is little or no consistency regarding either size or pattern of sensitivity, specificity, and predictive values in different contexts, so it is not possible to determine one of them merely from information about any of the others. In that sense, they are pliable in relation to each other. This indicates that it is necessary to appreciate the foundations of, distinctions between, and uses and misuses of each of these metrics, and that it is necessary to provide information about all of them, as well as the reference standard and the sample on which they are based, to characterize a screening test adequately.

Table 1. Five sets of sensitivity, specificity, and predictive values demonstrating differing patterns of results. Because sensitivity seems often to be confused with PPV, and specificity seems often to be confused with NPV, unambiguous definitions for each pair are necessary. These are provided below. Each of these definitions is incontestably accurate, but they can all be easily misinterpreted because none of them sufficiently emphasizes an important distinction between two essentially different contexts.

In the first context, only those people who obtain positive results on the reference standard are assessed in terms of whether they obtained positive or negative results on the screening test. In the second context, the focus changes from people who tested positive on the reference standard to people who tested positive on the screening test. Here, an attempt is made to establish whether people who tested positive on the screening test do or do not actually have the condition of interest.

Expressed differently, the first context is the screening test being assessed on the basis of its performance relative to a reference standard, which focuses on whether the foundations of the screening test are satisfactory; the second context is people being assessed on the basis of a screening test, which focuses on the practical usefulness of the test in clinical practice.

By way of further explanation, sensitivity is based solely on the cells labeled a and c in Figure 1 and, therefore, requires that all people in the analysis are diagnosed according to the reference standard as definitely having the target condition. The determination of sensitivity does not take into account any people who, according to the reference standard, do not have the condition of interest who are in cells b and d. Those cells do not include any people who, according to results from the screening test, do not have the condition who are in cells c and d.

Less elaborated, but perhaps also less helpfully explicit, definitions are possible, for example, that sensitivity is the proportion of people with a condition who are correctly identified by a screening test as indeed having that condition.

Expressed differently and more economically, PPV is the probability that people with a positive screening test result indeed do have the condition of interest. Inspection of Figure 1 supports the above definitions and those that are provided within the next subsection. As with the definitions often offered for sensitivity, these definitions are accurate but can easily be misinterpreted because they do not sufficiently indicate the distinction between two different contexts that parallel those identified for sensitivity.

Specificity is based on the cells labeled b and d in Figure 1 and, therefore, requires that all the people in the analysis are diagnosed, according to a reference standard, as not having the target condition. Specificity does not take into account any people who, according to the reference standard, do have the condition as pointed out above, those people, in the cells labeled a and c, were taken into account when determining sensitivity.

Those cells do not include any people who, according to the screening test, do have the condition who are located in cells a and b. Less elaborated, but perhaps also less helpfully explicit, definitions are possible, for example, that specificity is the proportion of people without a condition who are correctly identified by a screening test as indeed not having the condition.

Expressed differently and more economically, NPV is the probability that people with a negative screening test result indeed do not have the condition of interest. Sensitivity and specificity are concerned with the accuracy of a screening test relative to a reference standard.

Here, the screening test is being assessed. There are two main questions of relevance in that second situation.

Second, if the screening test yields a negative result, what is the probability that the person does not have the condition NPV? More precisely, sensitivity and specificity indicate the concordance of a test with respect to a chosen referent, while PPV and NPV, respectively, indicate the likelihood that a test can successfully identify whether people do or do not have a target condition, based on their test results. The two contexts i. Of particular importance, although it is desirable to have tests with high sensitivity and specificity, the values for those two metrics should not be relied on when making decisions about individual people in screening situations.

The lack of correspondence between sensitivity, specificity, and predictive values is illustrated by the inconsistent pattern of entries in Table 1 and should become more obvious in the next section. Because the pairs of categories into which people are placed when sensitivity and specificity values are calculated are not the same as the pairs of categories that pertain in a screening context, there are not only important distinctions between sensitivity and PPV, and between specificity and NPV, but there are also distinct limitations on sensitivity and specificity for screening purposes.

Akobeng [ 9 , p. Sensitivity does not provide the basis for informed decisions following positive screening test results because those positive test results could contain many false positive outcomes that appear in the cell labeled b in Figure 1.

Those outcomes are ignored in determining sensitivity cells a and c are used for determining sensitivity. Therefore, of itself a positive result on a screening test, even if that test has high sensitivity, is not at all useful for definitely regarding a condition as being present in a particular person.

Conversely, specificity does not provide an accurate indication about a negative screening test result because negative outcomes from a screening test could contain many false negative results that appear in the cell labeled c, which are ignored in determining specificity cells b and d are used for determining specificity. Therefore, of itself , a negative result on a screening test with high specificity is not at all useful for definitely ruling out disease in a particular person.

Failing to appreciate the above major constraints on sensitivity and specificity arises from what is known in formal logic as confusion of the inverse An example of this with regard to sensitivity, consciously chosen in a form that makes the problem clear, would be converting the logical proposition This animal is a dog; therefore it is likely to have four legs into the illogical proposition This animal has four legs; therefore it is likely to be a dog.

A parallel confusion of the inverse can occur with specificity. An example of this would be converting the logical proposition This person is not a young adult; therefore this person is not likely to be a university undergraduate into the illogical proposition This person is not a university undergraduate; therefore this person is not likely to be a young adult.

These examples demonstrate the flaws in believing that a positive result on a highly sensitive test indicates the presence of a condition and that a negative result on a highly specific test indicates the absence of a condition.

Instead, it should be emphasized that a highly sensitive test, when yielding a positive result, by no means indicates that a condition is present many animals with four legs are not dogs , and a highly specific test, when yielding a negative result, by no means indicates that a condition is absent many young people are not university undergraduates. Despite the above reservations concerning sensitivity and specificity in a screening situation, sensitivity and specificity can be useful in two circumstances but only if they are extremely high.

First, because a highly sensitive screening test is unlikely to produce false negative outcomes there will be few entries in cell c of Figure 1 , people who test negative on that kind of screening test i. Expressed differently, high sensitivity permits people to be confidently regarded as not having a condition if their screening test yields a negative result.

Second, because a highly specific screening test is unlikely to produce false positive results there will be few entries in cell b in Figure 1 , people are very unlikely to be categorized as having a condition if they indeed do not have it.

Expressed differently, high specificity permits people to be confidently regarded as having a condition if their diagnostic test yields a positive result. The mnemonics snout and spin , it must be emphasized, pertain only when sensitivity and specificity are high.

Their pliability, therefore, has some strong limitations. Furthermore, these mnemonics are applied in a way that might seem counterintuitive. In addition, Pewsner et al. As a consequence, both sensitivity and specificity remain unhelpful for making decisions about individual people in most screening contexts, and PPV and NPV should be retained as the metrics of choice in those contexts.

Considerations might also include over- versus under-application of diagnostic procedures as well as the possibility of premature versus inappropriately delayed application of diagnostic procedures. Input from clinicians and policymakers is likely to be particularly informative in any deliberations. Decisions about desirable PPVs and NPVs can be approached from two related and complementary, but different, directions.

One approach involves the extent to which true positive and true negative results are desirable on a screening test. The other approach involves the extent to which false positive and false negative results are tolerable or even acceptable. A high PPV is desirable, implying that false positive outcomes are minimized, under a variety of circumstances.

Some of these are when, relative to potential benefits, the costs including costs associated with finances, time, and personnel for health services, as well as inconvenience, discomfort, and anxiety for clients are high. A high PPV, with its concomitant few false positive screening test results, is also desirable when the risk of harm from follow-up diagnosis or therapy including hemorrhaging and infection is high despite the benefits from treatment also being high, or when the target condition is not life-threatening or progresses slowly.

Under these circumstances, false positive outcomes can be associated with overtreatment and unnecessary costs and prospect of iatrogenic complications.

False positive outcomes may also be annoying and distressing for both the providers and the recipients of health care. A moderate PPV with its greater proportion of false positive screening test outcomes might be acceptable under a number of circumstances, most of which are the opposite of the situations in which a high PPV is desirable.

For example, a certain percentage of false positive outcomes might not be objectionable if follow-up tests are inexpensive, easily and quickly performed, and not stressful for clients. In addition, false positive screening outcomes might be quite permissible if no harm is likely to be done to clients in protecting them against a target condition even if that condition is not present.

For example, people who are mistakenly told that they have peripheral artery disease, despite not actually having it, are likely to benefit from adopting advice to exercise appropriately, improve their diet, and discontinue smoking.

Sensitivity, Specificity, PPV and NPV

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. Sensitivity refers to a test's ability to designate an individual with disease as positive. A highly sensitive test means that there are few false negative results, and thus fewer cases of disease are missed.

When evaluating the feasibility or the success of a screening program, one should also consider the positive and negative predictive values. These are also computed from the same 2 x 2 contingency table, but the perspective is entirely different. One way to avoid confusing this with sensitivity and specificity is to imagine that you are a patient and you have just received the results of your screening test or imagine you are the physician telling a patient about their screening test results. If the test was positive, the patient will want to know the probability that they really have the disease, i. Conversely, if it is good news, and the screening test was negative, how reassured should the patient be?


AOCOPM. Assessment of test effectiveness. Is the test valid? • Sensitivity. • Specificity Prevalence – what is the probability of disease Example Cont'd.


Remembering the meanings of sensitivity, specificity, and predictive values

We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience, read our Cookie Policy. When developing diagnostic tests or evaluating results, it is important to understand how reliable those tests and therefore the results you are obtaining are.

As with all systematic reviews, the development of a clear, well-defined question is essential to maintaining transparency of the review process and to the quality and relevance of the findings. Some aspects of the question require particular consideration when planning a review of test accuracy. Both frequency and severity of the target condition would be expected to be greater in secondary care.

What does screening mean?

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.

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