PDF Download. What is the chance that the test will show that my patient has it? What is the chance that my patient actually has the disease? Next Article: Interpretation of confidence intervals. Therefore, as prevalence decreases , the NPV increases because there will be more true negatives for every false negative. This is because a false negative would mean that a person actually has the disease, which is unlikely because the disease is rare low prevalence.
The examples given should allow you to see how and why these vary as different factors change. Clinical Examination. An Introduction to the Arclight. Eye Drops Overview. Prescribing in Renal Impairment. Interpreting Hepatitis B Serology.
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Surgery Flashcard Collection. Anatomical Planes. Anatomy Flashcard Collection. The Inguinal Canal. A man with penile swelling. Previous Next. About the Author. Related guide articles How does prevalence affect the predictive value of a test? Explore Medmastery Liver Lab Essentials. Coronary Angiography Essentials Workshop. Pacemaker Essentials Workshop. Chest X-Ray Essentials Workshop. 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. A high NPV is desirable, implying that false negatives are minimized, under a different set of circumstances. Some of these are a condition being serious, largely asymptomatic, or contagious, or if treatment for a condition is advisable early in its course, particularly if the condition can be treated effectively and is likely to progress quickly.
Under these circumstances, it would be highly undesirable if a screening test indicated that people did not have a condition when in fact they did. A moderate NPV—with its greater proportion of false negative screening test outcomes—might be acceptable under other circumstances, however, and most of those circumstances are the opposite of those that make a high NPV desirable.
For example, the false negative outcomes associated with moderate NPVs might not be problematic if the target condition is not serious or contagious, or if a condition does not progress quickly or benefit from early treatment.
Moderate NPVs might also be acceptable if diagnosis at low levels of a condition is known to be ambiguous and subsequent screening tests can easily be scheduled and performed, or if, given time, a condition is likely to resolve itself satisfactorily without treatment.
If, for a variety of reasons, the PPVs and NPVs on a screening test were deemed to be either too high or too low, they could be adjusted by altering the stringency of the screening test for example, by raising or lowering cutpoints on a continuous variable or by changing the components that comprise a screening test , by altering the sample of people on whom the analyses were based for example, by identifying people who are regarded as having more pertinent demographic or health status variables , or by altering the nature of the reference standard.
Those strategies would almost inevitably result in changes to the sensitivity and specificity values, and those revised values would simply need to be reported as applying to the particular new level of stringency on the screening test, the applicable population, and the reference standard when that test was being described.
This reveals, yet again, that pliability can be associated with sensitivity, specificity, and predictive values. When describing screening tests, many researchers provide information about their reference standard; the prevalence of the target condition in their research sample s ; the criteria that had been used to indicate presence or absence of a condition according to the screening test; and the sensitivity, specificity, and predictive values they obtained 6 , 7 , 15 , 17 , The research results are not always impressive or what the researchers might have hoped for, but at least it is possible to draw informed conclusions from those results.
Sometimes only partial information is provided, and that limits the usefulness of research. For example, in a systematic review concerning the toe—brachial index in screening for peripheral artery disease, Tehan et al.
In one of the more informative articles reviewed by Tehan et al. However, they provided insufficient interpretation at times. For example, they reported an unusually low sensitivity value of Deficiencies in provision of information can be even more problematic. Although they reported a specificity of That these values are so high in a screening context raises suspicions. When following those suspicions through, it becomes evident that the researchers used the ABI as a component of the reference standard as well as being the sole variable that comprised the screening test.
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