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HCET Home > On-line Training > RVIPP Self Study Manual: Chlamydia > 3. Intro to Lab Methods & Interpretation of Lab Results

Numerous laboratory tests exist for diagnosing Chlamydia trachomatis (CT) infections. Understanding a little about the various tests and how they work will enable you to submit the best specimens and properly interpret results. Based on performance and cost issues, laboratory methods for CT can be divided into the following categories listed below. A chart listing highlights and specific points of interest for each type of test can be found on pages 4-3 and 4-4. here and here

1. Culture: Isolation and propagation of chlamydial organisms using cell cultures was the first practical method for laboratory diagnosis and is still in use today though usually recommended only under special circumstances. No non-culture method can match the specificity of culture, which is considered to be virtually 100% specific; thus, almost every positive is a true positive. It is this unparalleled specificity and corresponding high positive predictive value (PPV) that makes culture desirable in cases such as suspected sexual abuse, where a false-positive result can be especially devastating. Unfortunately, culture can lack sensitivity which means it is often falsely negative. This lack of sensitivity combined with the expense, rigorous specimen handling requirements, long time to results and scarce availability of culture limits its usefulness in routine management of individuals at-risk.
2. Non-Culture, Non-Amplified Methods: This is the largest and most diverse group of CT tests and contains several subgroups, the largest of which is the Antigen Detection subgroup. This subgroup includes Enzyme Immunoassays of several different formats (micro-plate, automated, and rapid point-of-care tests) and Direct Fluorescent Antibody (DFA.) Nucleic acid probe (NAP) comprises the second subgroup. This subgroup is made up of only one test, the Gen Probe PACE and PACE2 assays, probably the most commonly used non-amplified CT test. Although NAP utilizes nucleic acid hybridization, it is not an amplified test, and performance and cost issues are similar to that of Antigen Detection methods. The third subgroup is also comprised of one test, the Digene Hybrid Capture assay, which incorporates “signal amplification” to enhance sensitivity over EIA and NAP type methods though it does not achieve the sensitivity of “target amplification” tests described below. This relatively new test is being touted as a less-expensive alternative to Nucleic Acid Amplification Test (NAAT), but it is not really considered a NAAT.
3. Nucleic Acid Amplification Tests: The newest and most rapidly expanding category of CT tests and by far the most sensitive, NAAT’s are rapidly becoming the chlamydia tests of choice in many settings. The improved performance does come at a price as NAAT’s are still significantly more expensive than other test methods. However, with the number of commercially-available NAAT’s increasing, competition is making these highly sensitive tests more widely available than ever (See Methods chart, page 4-4 for details). Each of the different methods is based on similar principles of building copies of target nucleic acid sequences using various enzymes and probes and detecting amplified products by several different techniques. Performance has been shown to be comparable among all of the assays. Most significant differences between NAAT methods lie in logistical issues and relative costs rather than performance.

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Interpretation of Laboratory Results

Definitions

1. Sensitivity

The ability of a test to detect infection if it is present. Another way to understand sensitivity is the ability of a test to correctly classify infected individuals as positive. Still another way to understand sensitivity is the percent of positive test results in a hypothetical population, all of whom have the infection. A perfectly sensitive test would be positive 100% of the time in such a population. Thus, a highly sensitive test gives few false negatives. The Sensitivity of a test is usually expressed as the percent of existing positives detected by the test.

	“True” Positive results
Sensitivity  =
	True Positives + False Negatives (positives missed)

2. Specificity

   The ability of a test to detect absence of infection if it is NOT present, in other words, to correctly identify uninfected individuals as negative. Still another way to understand specificity is the percent of test results that are negative in a hypothetical population, none of whom have the infection. Thus, a test with high specificity gives few false positives.

   	True Negatives
   Specificity  =
   	True Negatives + False Positives

3. Population Prevalence

   The proportion of individuals in a population who have the infection at a specific point in time. “Population” refers to a group of individuals with shared characteristics; risk of infection can vary significantly among individuals in a given population. However, since sensitivity and specificity are defined based on hypothetical populations who have 100% and 0% prevalence of the infection (respectively), and since real population have prevalence between 0% and 100% the predictive value of a test chances depending on the sensitivity and specificity of the test and the pre-test likelihood (i.e., population prevalence) of infection.

4. Pre-test Likelihood

   The likelihood, prior to testing, that a given individual has the infection. Pre-test likelihood is usually estimated based on known or predicted population prevalence for the population appropriate to the individual (e.g. age group), then adjusted up or down based on the individual’s risk factors and/or signs and symptoms.

5. Predictive Values

   The probability that a given result reflects the true status of the patient. “Positive Predictive Value” (PPV, PVP) is the probability that a positive result is a true positive, and is dependent on the specificity of the test and the prevalence of infection in the population. “Negative Predictive Value” (NPV, PVN) is the probability that a negative result is a true negative, and depends on the sensitivity of the test and the population prevalence.

   	True Positive Results
   PPV  =
   	True Positive Results + False Positives

   	True Negative Results
   NPV  =
   	True Negative Results + False Negatives

• Since the true prevalence is not known, predictive value estimates can be based on positivity/risk.
• PPV and NPV can be used to estimate the potential for false positive/negative results in a population and to assess the likelihood that an individual result accurately reflects a patient’s infection status.

Effect of Prevalence on Predictive Values:

• The lower the prevalence (positivity, risk), the lower the PPV for any assay with a specificity of less than 100%.
• Because of the much higher proportion of negative results seen, differences in prevalence typically do not have as much impact on NPV.

1. Each test has specific collection materials that must be used; always use the exact materials supplied or recommended by the laboratory for a particular test. Failure to do so may compromise results or lead to specimen rejection by the laboratory.

2. Each test has specific handling requirements including acceptable temperature and time between collection and testing; again, follow specific lab recommendations for specimen handling. Failure to do so may compromise results or lead to specimen rejection by the laboratory.

3. All swab specimens must contain columnar epithelial cells for maximum sensitivity for any CT method used. Excess mucus, exudate, pus, blood and fecal material should be avoided.

4. The sensitivity and specificity of an assay are determined by comparisons with results of other assays and clinical information in controlled studies. Accuracy of sensitivity and specificity estimates are highly dependent on the standards of comparison used. Performance of laboratory assays in “real life” can vary from lab to lab, among different populations, and over time.

5. No laboratory test for chlamydia is 100% sensitive, and none, with the exception of culture, are 100% specific. False-positive and false-negative results can and do occur. It is impossible to determine the exact proportion of positives that are “false”; however, the likelihood of such results can be estimated in order to assist with interpretation of individual results. Always consider the performance of the test (sensitivity, specificity) and the risk of infection (population prevalence) when interpreting any individual test result. Remember that confidence in the accuracy of positive results is highest when testing patients at highest risk of infection.

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 Last update: 03/05/08