Diagnostic Testing and Imaging

Key concepts

Mistakes in ordering and interpreting diagnostic tests can lead to misdiagnosis and inappropriate therapy.
Diagnostic tests, including laboratory tests and imaging studies, should be ordered to narrow down the differential diagnosis.
Clinicians must know the sensitivity and specificity of the diagnostic test to avoid misinterpretation of the results.
A few diagnostic tests are both highly sensitive and highly specific and may therefore be useful as screening tests for patients with many forms of uveitis. The fluorescent treponemal antibody absorption (FTA-ABS) test for syphilis is an example of a diagnostic test often used as a general screening test in patients with uveitis.
Assessing the likelihood of disease before the diagnostic test is crucial in determining the likelihood of disease after either a positive or a negative diagnostic test.
New diagnostic tests for a number of infectious diseases have improved the diagnosis and treatment of infectious uveitis.
Some tests, including fluorescein angiography and ocular coherence tomography (OCT), are helpful in assessing response to therapy.
Advances in OCT, including OCT angiography, have improved the diagnosis and management of patients with uveitis and are now discussed in a separate chapter ( Chapter 6 ).
Some diagnostic tests, such as bone mineral density studies, help limit the side effects of therapy and are now part of the standard care of patients on systemic anti-inflammatory therapy.

What diagnostic tests should you order in the evaluation of the patient with uveitis? This is one of the most difficult questions we are asked. It is clear, however, that a nonselective approach to testing is costly and inefficient and provides information that is often irrelevant or, worse yet, that may lead to an incorrect diagnosis and inappropriate therapy. It is important to understand how to interpret diagnostic data because this information will help the clinician to order the appropriate tests. This chapter will discuss the approach to ordering and interpreting diagnostic tests. In addition, some of the more commonly ordered tests will also be reviewed here. Other tests will be reviewed in specific chapters on the relevant diseases.

Why does the clinician order diagnostic tests? Usually, diagnostic tests are ordered to help make the correct diagnosis. Unfortunately, many clinicians are overly influenced when positive or negative results of diagnostic tests come back from the laboratory. A clinical example will serve to illustrate this point. A 34-year-old African American woman from Texas presents with an intermediate uveitis in both eyes that has been present for the past 7 months. There is no history of rash, arthritis, or fever, but the patient does complain of wheezing and shortness of breath on exertion. The ophthalmologist orders a battery of diagnostic tests, including a serologic test for Lyme disease, which yields a positive result. Of course, the ophthalmologist is pleased to diagnose the patient’s condition and treats her with a 2-week course of ceftriaxone. There are only three problems with this scenario: The patient probably does not have Lyme disease, does not need the expensive 2-week course of intravenous antibiotics, and more likely has sarcoidosis that is not being treated.

Before one can appropriately interpret the results of a diagnostic test, three pieces of information are needed. First, one needs to know the sensitivity of the diagnostic test ( Fig. 5.1 ). This is calculated by dividing the number of patients who actually have the disease and who, upon being tested, have a positive result by the total number of patients with the disease who are tested. Another name given to patients who have a disease and have a positive test result is true positives : These patients have a positive test result and actually have the disease. Patients who have the disease but have a negative test result are called false negatives. Many of the commonly used serologic tests for Lyme disease have sensitivity of approximately 90%. What does that mean? It means that if 100 patients with Lyme disease were tested, 90 would have a positive result (true positives), but 10 would have a negative result (false negatives). Furthermore, many diagnostic tests have varying sensitivities, depending on the stage of the disease. For example, Lyme disease serologies are less sensitive during the acute stage of the disease.

The second piece of information you need to have to interpret a diagnostic test result is the specificity (see Fig. 5.1 ). The specificity of a diagnostic test is calculated by dividing the number of patients who do not have the disease in question and have had an appropriately negative test result by the total number of people without the disease who are tested. People who do not have the disease and have a negative test result are called true negatives. Similarly, people who do not have the disease but have a positive test result anyway are called false positives. In the case of the serologic test for Lyme disease, the specificity is also 90%. This means that if 100 patients without Lyme disease undergo this test, 90 will have an appropriately negative result, but 10 will have a misleading positive result.

Pretest likelihood of disease

The third and critical piece of information needed for test interpretation is often ignored by many doctors. This piece of information is called the pretest likelihood of the disease and is defined as the chance that the patient has a particular disease before the diagnostic test is ordered. The pretest likelihood can be based on a number of factors, such as the patient’s history and physical examination findings and the incidence of a particular disease in that area. This is the figure that most depends on the clinician’s prowess and ability: The more accurate the physician’s calculation of the pretest likelihood of disease, the more accurate will be the subsequent interpretation of the test result.

What is the pretest likelihood of Lyme disease in the case of the 34-year-old woman from San Antonio who has intermediate uveitis but no other symptoms and signs of Lyme disease and who does not live in an area endemic for the disease? The prevalence of Lyme disease in San Antonio, Texas, is probably less than 1 in 1000, and with no other evidence of the disease, the pretest likelihood of the disease would probably be less than this. But let us be generous and say that the pretest likelihood of this patient having Lyme disease is 1 in 1000 or 0.1%. How do we interpret her positive test result for Lyme disease?

The likelihood that the diagnosis of Lyme disease is correct in this patient can be calculated because we now have the sensitivity of the test (90%), the specificity of the test (90%), and the pretest likelihood of the disease (0.1%). This calculation of what is called the posttest likelihood of disease is carried out with the use of a formula derived by the mathematician Bayes and is called Bayes’ theorem. The standard form of Bayes’ theorem states the following:

\begin{matrix} Posttest probability = \\ \frac{Pretest probability \times sensitivity}{(Pretest probability \times sensitivity) + (1 - Pretest probability) (1 - specificity)} \end{matrix}

$\begin{matrix} Posttest probability = \\ \frac{Pretest probability \times sensitivity}{(Pretest probability \times sensitivity) + (1 - Pretest probability) (1 - specificity)} \end{matrix}$

Bayes’ theorem has been understood for two centuries but has only been applied to clinical reasoning over the past 30 years. Although formulas may appear daunting to some clinicians, computer programs and nomograms have been developed to help the clinician interpret the data. ^, So what is the likelihood that our patient has Lyme disease, given her positive laboratory test result? With Bayes’ theorem, the chance that she has Lyme disease is still only 0.9%, or a chance of 9 out of 1000. Although this represents an almost 10-fold increase in likelihood compared with the pretest likelihood because there was a very small chance that she had Lyme disease before the test, she still probably does not have the disease. Knowing that the posttest likelihood of the patient having Lyme disease is less than 1%, the clinician probably would not opt to treat her with antibiotics.

Diagnostic tests are also not as useful if there is a very strong likelihood that a patient has the disease before the test is ordered. If this same patient came from Lyme, Connecticut; had a history of a tick bite followed by an erythematous, round rash; and now presented with intermediate uveitis and arthritis, she would probably have a greater than 99% chance of having the disease, even without testing. Even if the result of her serologic test for Lyme disease was negative, on application of Bayes’ theorem, the patient would still have about a 99% chance of having the disease.

Diagnostic tests are most helpful when the pretest likelihood of the disease is about 50%. For our patient with intermediate uveitis, if after our initial assessment we thought that her chance of having Lyme disease was 50%, a positive serologic test result would increase the posttest likelihood of the disease to 90%. So in this case, we start with a 50:50 chance of Lyme disease but end up with Lyme disease being, by far, the most likely diagnosis.

Receiver Operating Characteristic Curve

Many diagnostic tests involve establishing a numerical cut-off, above which a patient is felt to have a “positive” test result and hence is more likely to have the disease. Where you set that cut-off affects the sensitivity and the specificity of the test and determines the number of false-positive and false-negative test results. Unless a test is 100% sensitive and 100% specific, the more sensitive it is, the more likely you are to get false-positive results. The sensitivity of a test can be graphed against the 1-specificity of the test to obtain what is called the receiver operating characteristic (ROC) curve ( Fig. 5.2 ). The performance of a diagnostic test can be quantified by calculating the area under the ROC curve. Importantly, the ability of two continuous variables to diagnose a disease can be distinguished by comparing the two ROC curves and the area under these curves and determining whether this difference is statistically significant. ^, If so, the test with the greater area under the ROC curve may be more discriminating.

Fig. 5.2, Receiver operating characteristic (ROC) curve for the requirement for each additional number of ocular features required to make a diagnosis of ocular sarcoidosis. The area under the ROC curve is greatest (0.84) for requiring a minimum of two ocular features to make the diagnosis, with sensitivity of 84% and specificity of 83%.

It is also important to critically assess the quality of the data underlying the sensitivity and the specificity numbers you use. Data usually come from a number of clinical trials that have used the given test. A meta-analysis of these studies can be used to assess diagnostic test accuracy by graphing the results on the ROC curve.

So now that you have the knowledge to analyze data, it should be easy to interpret your patients’ test data, right? Unfortunately, it is not that easy. It is difficult to obtain the sensitivities and the specificities of many of the common diagnostic tests we order. Many laboratories are considering providing a nomogram listing the posttest likelihood of a disease for differing pretest likelihoods because they already know the current sensitivity and specificity for that test. But how do we know the sensitivity or the specificity of chest x-ray for the diagnosis of sarcoidosis or that of diagnostic vitrectomy for intraocular lymphoma? These figures are difficult to obtain and may vary tremendously from institution to institution. More and more, however, articles are being published on the sensitivity and the specificity of diagnostic procedures and tests. In addition, the clinician can do the calculations on the basis of hypothetical numbers. For example, one might ask this question: Given 95% sensitivity and 95% specificity for a test in a patient with a 10% chance of having the disease, what is the posttest likelihood of the disease? It is surprising how much such calculations can help you to determine the diagnostic or therapeutic approach to patients with complicated conditions. Rosenbaum and Wernick have published a review on how to apply Bayes’ theorem to the evaluation of patients with uveitis, and this should be useful to many clinicians.

Diagnostic tests for uveitis

After the initial differential diagnosis is generated, diagnostic tests that help discern among the most likely disorders should be ordered. Remember that diagnostic tests will have the most utility in confirming or rejecting diagnoses that start with about a 50% chance of being correct. Table 5.1 and Box 5.1 list the common diagnostic tests useful for the evaluation of patients with uveitis. In addition to helping the clinician make the correct diagnosis, diagnostic tests are ordered in two other clinical settings. The first of these involves ordering tests that help the practitioner exclude diagnoses of tumor and infection because these disorders require specific therapy and would be exacerbated by anti-inflammatory treatment. The second is to determine why a patient’s vision has decreased and whether this change is reversible. In eyes with complicated uveitis, the reasons for poor vision may be multifactorial, and the clinician needs as much information as possible.

TABLE 5.1

Laboratory Tests Commonly Ordered In Patients With Uveitis

Tests	Conditions/Comments
Angiotensin-converting enzyme	Sarcoidosis; may be elevated in children without sarcoidosis
Antiphospholipid Ab (lupus anticoagulant and anticardiolipin Ab) Anti-CCP Antihistone Anti-RNP Anti–double-stranded DNA (dsDNA) Anti-SS-A(Ro) Anti-SS-B(La) Anti-Smith (Sm)	Thrombosis, CNS disease, and spontaneous abortions in patients with systemic lupus erythematosus Rheumatoid arthritis (60%–70% patients with RA, associated with erosive disease) Specific for drug induced SLE and present in 50%–70% of SLE SLE or other connective tissue diseases Relatively specific for SLE 60%–70% of patients with Sjögren syndrome and 30%–40% with SLE 50%–60% with Sjögren syndrome and 10%–15% with SLE Relatively specific for SLE
ANA	Systemic lupus erythematosus and other rheumatic diseases
Antifungal Ab	Fungal disease
ANCA	Wegener granulomatosis cytoplasmic pattern ANCA (cANCA)
Peripheral pattern ANCA pANCA	Polyarteritis nodosa
Antitoxoplasma Ab	Toxoplasmosis
Antiviral Ab Bartonella antibody	Viral infection Bartonellosis
Calcium	Sarcoidosis
Complete blood count	Underlying systemic disease, such as malignancy or infection
Cross-reactive protein Creatinine	Underlying inflammatory disease, such as rheumatic disease Renal disease associated with autoimmune diseases, such as SLE
Cultures	Bacterial, fungal, mycobacterial, and viral diseases
Erythrocyte sedimentation rate	Underlying systemic diseases (such as rheumatic disease or malignancy)
FTA-ABS	Treponemal test for syphilis
HIV ELISA	HIV
HTLV-1	HTLV-1 infection
HLA typing	Specific HLA types associated with specific diseases (HLA-B27, HLA-A29, and HLA-B51)
Immune complexes	Rarely useful
Liver function tests	Sarcoidosis, hepatitis
Lumbar function for cell count	Infection, malignancy, VKH, APMPPE
Lumbar puncture for CSF VDRL	Syphilis
Lumbar puncture for culture and Gram stain	Infection
Lumbar puncture for cytology Lupus antibody	CNS lymphoma Lupus
Lyme antibody Lysozyme QuantiFERON test	Lyme disease (be aware of false-positive results) Sarcoidosis Tuberculosis
Rheumatoid factor (RF)	Rheumatoid arthritis; girls with JRA and uveitis often RF negative but ANA positive
Stool for ova and parasites	Parasitic disease
T-cell subsets	Low CD4+ count predisposes patient for opportunistic infections
Thyroid function tests Toxocara antibody	Increased incidence of thyroid disease in patients with uveitis Toxocariasis
Urinalysis	(Blood suggests rheumatic disease)
VDRL/RPR West Nile antibody	Nontreponemal tests for syphilis West Nile disease (serum or CSF)

Ab, Antibody; ANA, antinuclear antibody; ANCA, antineutrophil cytoplasmic antibody; APMPPE, acute posterior multifocal placoid pigment epitheliopathy; Anti-CCP, anti-cyclic citrullinated peptide; anti-RNP, antiribonucleoprotein; CNS, central nervous system; CSF, cerebrospinal fluid; ELISA, enzyme-linked immunosorbent assay; HIV, human immunodeficiency virus; HTLV, human T-cell leukemia/lymphoma virus; JRA, juvenile rheumatoid arthritis; VDRL, Venereal Disease Research Laboratory; VKH, Vogt-Koyanagi-Harada syndrome.

BOX 5.1

Other Diagnostic Tests In Uveitis

Imaging Tests

Computed tomography (CT) of the head
Magnetic resonance imaging (MRI) of the head
CT of sinuses
Gallium scan
Hand radiography
Sacroiliac radiography

Skin Testing

Allergy testing
Anergy testing
Histoplasmin
Pathergy
Purified protein derivative (PPD)

Ancillary Ophthalmic Testing

Color vision testing
Contrast sensitivity
Electroretinography
Electro-oculography
Fluorescein angiography
Indocyanine green angiography
Laser interferometry
Laser flare photometry
Manifest refraction
Optical coherence tomography
Optical coherence tomography angiography
Ultrasonography of the orbit
Ultrasonography of the retina
Visual evoked potentials
Visual field testing

Biopsy Specimens

Conjunctiva
Lacrimal gland
Aqueous humor
Vitreous
Choroid and retina
Skin

Should all patients with uveitis undergo a standard set of diagnostic tests regardless of the presentation? Uveitis specialists have a high rate of use of laboratory testing in evaluating new patients. When presented with 13 patient scenarios, a group of uveitis specialists almost always ordered some testing for all scenarios, with an average cost of $282.80 per scenario. It makes more sense to try to develop an initial differential diagnosis first; however, there are some tests with relatively low cost that can help rule out treatable diseases with potential adverse outcomes. Many uveitis specialists have a low threshold for ordering a complete blood count (CBC), chest radiography, and syphilis serology in many uveitis patients.

In this chapter, we will review some of the more commonly ordered diagnostic tests that may be useful in the diagnosis of uveitis. The number of diagnostic tests available to the ophthalmologist has increased tremendously over the past decade. Many tests are expensive and yet yield little useful information; others are critical for the appropriate management of patients. These tests can be arbitrarily grouped into laboratory tests, imaging techniques, skin testing, surgical specimens, and ancillary ophthalmic tests. Many of the tests listed in Table 5.1 and Box 5.1 are more thoroughly discussed in later chapters on specific diseases; however, several points for each group of diagnostic tests deserve comment here.

Laboratory Tests

Laboratory tests usually are the first diagnostic tests that most physicians order (see Table 5.1 ). Although we have emphasized that laboratory tests should not be routinely used to screen patients with uveitis for that disease and that tests should be ordered only to discern among likely diagnoses, there are exceptions. As stated previously, practically all patients with idiopathic uveitis should be tested for syphilis. There are many factors that support the use of laboratory tests to screen for syphilis in most patients with uveitis. Syphilis remains a common cause of uveitis and is easily treatable. Patients with untreated ocular syphilis often have devastating visual outcomes. Importantly, the fluorescent treponemal antibody absorption (FTA-ABS) test for syphilis is both extremely sensitive and specific. In patients with late syphilis, the stage of disease associated with uveitis, both sensitivity and specificity of the FTA-ABS test are 99%. With the combined presence of a treatable, common disease; poor outcome in untreated patients; and a highly sensitive and specific diagnostic test with little risk and moderate cost, screening becomes useful. Previous reports stated that the Venereal Disease Research Laboratory (VDRL) test has a sensitivity of only 70% for late syphilis. Therefore many uveitis specialists recommended a FTA-ABS test for evaluation of the patient with uveitis. More recently, the sensitivity of nontreponemal tests, including the VDRL and rapid plasma reagin (RPR) tests, is estimated to be 78% to 86% for detecting primary syphilis infection, 100% for detecting secondary syphilis infection, and 95% to 98% for detecting latent syphilis infection with specificity ranges between 85% and 99%. A two-step process has been recommended with an initial nontreponemal test, followed by a treponemal test, such as FTA-ABS. However, because the sensitivity and specificity of nontreponemal tests may be less in patients with underlying autoimmune diseases and coinfection with human immunodeficiency virus (HIV), we believe it may be prudent to screen patients with uveitis for syphilis with both nontreponemal and treponemal tests. Additionally, the incidence of syphilis in patients with acquired immunodeficiency syndrome (AIDS) is increasing. ^, As a result, all patients who have syphilis and uveitis should also be tested for HIV infection, and vice versa.

A number of tests are primarily used for research purposes but are commercially available. Many practitioners order these tests but do not know what to do with the results when they come back. One example is testing for circulating immune complexes. Circulating immune complexes were first thought to be the mechanism underlying the destruction of the eye in various forms of uveitis. In the past, tests for circulating immune complexes were ordered, and if these complexes were present, they were assumed to be the cause of the disease. However, it is no longer clear whether immune complexes are the cause in many cases of uveitis.

Numerous laboratory tests can be useful in evaluating patients with possible rheumatologic disease. Acute-phase reactants include a number of proteins produced by the liver in response to stress and signal underlying inflammation. The most commonly used tests for acute-phase reactants are the erythrocyte sedimentation rate (ESR) and cross-reactive protein (CRP). Rheumatoid factor (RF) is an autoantibody against the Fc portion of human immunoglobulin G (IgG). The test is relatively sensitive for rheumatoid arthritis (RA) and may also be positive in patients with other rheumatic diseases, including Sjögren syndrome and systemic lupus erythematosus (SLE). However, RF may also be positive in patients with chronic inflammatory diseases or malignancy and is seen in normal subjects as well. The antinuclear antibody (ANA) test is another test that can help detect underlying connective tissue diseases. These antibodies are extremely sensitive for SLE, and depending on the immunofluorescence pattern of the test, can indicate specific disorders, such as polymyositis, dermatomyositis, or CREST (calcinosis, Raynaud phenomenon, esophageal dysmotility, sclerodactyly, and telangiectasis) syndrome.

Rheumatologic Tests

Because rheumatologic and autoimmune disorders are common causes of uveitis, many patients undergo laboratory evaluation for these diseases. Again, these laboratory tests are most useful to confirm a clinically suspected diagnosis, rather than to screen for a less likely disease. Some of the common laboratory tests ordered in the evaluation of rheumatologic diseases are discussed here.

Acute-phase Proteins

Inflammation is a core feature of the rheumatologic diseases, and acute-phase proteins are a class of proteins that can increase in response to the inflammatory response and can be detected in serum. As a result of increases in inflammatory proteins, such as fibrogen, the ESR is often increased in rheumatologic diseases (RA, SLE, and systemic vasculitis). However, the ESR can be elevated in a number of other nonrheumatologic conditions, including pregnancy, cancer, and infection. The levels of CRP can also increase during inflammation associated with rheumatologic diseases and can help differentiate osteoarthritis from RA. In addition, polymyalgia rheumatica is often accompanied by high levels of CRP.

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