Chapter 1: Concepts in Laboratory Medicine

An understanding of the principles set forth in this chapter is essential for the appropriate selection of laboratory tests and the accurate interpretation of the test results.

Ranges Used in the Interpretation of Test Results

In clinical practice, the laboratory test result is typically placed alongside a range of values for that test. In most cases, this is the reference range, which is often considered to be the normal range. It is important to understand that individuals with values inside the reference range may have subclinical disease, despite the presence of an apparently normal value. The reference range is dependent on the instrument and reagent used to perform the test. The reference ranges are ideally established inside the laboratory where the test is being performed. Reference ranges supplied by instrument and reagent manufacturers are not likely to correspond perfectly to ranges generated within an individual laboratory. This is because the population used to establish the range by the manufacturer and/or the instruments and reagents used by the manufacturer are likely to be different from those in an individual clinical laboratory.

The Reference Range

To obtain a reference range, individuals without disease and on no medications donate samples for testing. A distribution of these values, which should be numerous enough to be statistically reliable, is plotted. The data are not always distributed in a Gaussian pattern. Therefore, statistical methods that are nonparametric are used to identify the central 95% of values. This range, representing the middle 95% of results, is the reference range. As an indication that being outside the reference range does not always reflect the disease, 5% of normal healthy, nonmedicated individuals who donated samples for the reference range determination now fall outside of what has become the reference range for the test.

The Desirable Range

Several decades ago, the results for cholesterol testing demonstrated that individuals eating a high-fat diet showed high cholesterol levels that were associated with atherosclerotic vascular disease. When these apparently healthy, nonmedicated individuals provided samples for reference range determinations, the central 95% of values from this population provided an inappropriately high reference range. Therefore, the use of the classical reference range for selected laboratory tests in certain populations was not recommended. For that reason, desirable or prognosis-related ranges were developed. These are commonly established by groups of experts associating laboratory test results with clinical outcome.

Therapeutic Range

For certain medications, a therapeutic window exists to provide a target for a blood, plasma, or serum level for the medication. Values below the therapeutic range typically reflect an inadequate amount of medication, and values above the therapeutic range may be associated with a particular toxic effect. In some cases, the therapeutic range does not reflect the amount of medication in the blood, but instead reflects a therapeutic effect produced by the drug. For example, patients taking the drug warfarin are not monitored with warfarin levels in the blood. Instead, the warfarin decreases the level of coagulation factors, which results in a prolonged prothrombin time (PT), and a calculated value known as the international normalized ratio (INR). The therapeutic range of warfarin, therefore, is determined by its effect rather than its concentration in the blood.

Interpretations of Clinical Laboratory Test Results that Do Not Involve the Use of a Range

For certain laboratory tests, the presence of disease is associated with a value that is above a threshold. The use of troponin as a marker for myocardial infarction involves a threshold value, such that a level above the threshold is consistent with cardiac ischemia. Another prominent example is related to the detection of drugs of abuse. Any level above zero, as a threshold value, provides evidence for the ingestion of an illicit drug.

For laboratory tests that show too much variability to permit the use of a range or a threshold, an individual laboratory result for a specific patient can be compared with a result for that same patient that was generated previously. The longitudinal analysis of results over time can indicate the progression or regression of the disease.

The Need for a Diagnostic Cutoff

Figure 1–1 shows 2 populations of individuals and their results for a particular test. All of the individuals who do not have disease have a low value for the test, and all of the individuals with disease have a high value for the test. There is no overlap between groups in Figure 1–1. In Figure 1–2, a more commonly encountered situation is shown. There is overlap in laboratory values between individuals with disease and those without disease. This means that the diagnostic threshold will necessarily misclassify some patients to create false-positives, false-negatives, or both.

The Definition of Sensitivity of a Laboratory Test

The population of individuals who have disease is the focus of sensitivity. The sensitivity of a laboratory test is its capacity to identify all individuals with disease. The threshold used in Figure 1–2 maximizes sensitivity by placing all those with disease above the line. This placement of the diagnostic threshold would decrease the number of false-negatives (those with disease who fall below the line), because everybody with the disease would have a positive test result. However, there is a significant misclassification of individuals without disease. As the diagnostic threshold is lowered, an increasing number of patients without disease would be told they have a positive test result, and by implication, the disease in question. The formula for sensitivity is:

True-positives and false-negatives are groups with disease; as noted above, sensitivity focuses on those with disease.

The Definition of Specificity of a Laboratory Test

The population of individuals without disease is the focus of specificity. Specificity is a statistical term that indicates the effectiveness of a test to correctly identify those without disease. When used to describe a laboratory test, it does not refer to its ability to diagnose a “specific” disease among a group of related disorders. One could maximize specificity by raising the threshold shown in Figure 1–3 to place all those without disease below the line. This would decrease the number of false-positives because everyone without disease would have a negative test result. However, there would be a significant misclassification of the individuals with disease. As the diagnostic threshold is raised, an increasing number of patients with disease would be told they have a negative test result and, by implication, no disease. The formula for specificity is:

True-negatives and false-positives are the groups without disease; as noted above, specificity focuses on those without disease.

The Identification of the Appropriate Value for the Diagnostic Threshold

For diseases that are serious and treatable, and for which a second confirmatory laboratory test exists, it is important to maximize sensitivity as in Figure 1–2. For example, for diagnosis of AIDS, it is better to have a few false-positives that can be subsequently correctly identified with a confirmatory test than to fail to identify individuals with HIV infection who might unknowingly infect others. However, for diseases that are serious and not curable, a false-positive result is catastrophic for the patient. For such diseases, such as pancreatic cancer, it is better to use the threshold shown in Figure 1–3 for diagnosis because if individuals with disease are missed, it will have no effect on the treatment or outcome. When there are no compelling reasons to maximize either sensitivity or specificity, the threshold value should be established to minimize the total number of false-positives and false-negatives, as shown in Figure 1–4.

The Definition of Predictive Value of a Positive Test

The population of individuals with a positive test result is the focus of positive predictive value. The positive predictive value for a laboratory test indicates the likelihood that a positive test result identifies someone with disease. It should be noted that the predictive value of a positive test is greatly influenced by the prevalence of the disease in the area where testing is performed. As an example, a screening test for HIV infection is more likely to be confirmed as positive in an area where many individuals are infected with HIV, as opposed to a location where there is only a rare case of HIV infection. In the latter situation, most of the positive HIV tests in the initial evaluation of a patient are found to be false-positives by confirmatory tests. A high percentage of false-positives from a low prevalence disease, as shown in the following formula, decreases the predictive value of the positive test:

True-positives and false-positives are the groups with a positive test result; as noted above, positive predictive value focuses on those with a positive test.

The Definition of Predictive Value of a Negative Test

The population of individuals with a negative test result is the focus of the negative predictive value. The negative predictive value for a laboratory test indicates the likelihood that a negative test result identifies someone without disease. It is not greatly influenced by the prevalence of disease because false-positives are not included in the formula for negative predictive value. The formula for predictive value of a negative test result is:

True-negatives and false-negatives are the groups with a negative test result; as noted above, negative predictive value focuses on those with a negative test result.

The Difference Between Prevalence and Incidence

The prevalence of a disease reflects the number of existing cases in a population. It is usually expressed as a percentage of a certain population. Incidence refers to the number of new cases occurring within a period of time, usually 1 year. For example, in the United States, sore throat has a low prevalence because considering the size of the population there is a low percentage of individuals at a given time afflicted with sore throat. However, it has a high incidence because many new cases of sore throat appear each year.

Precision versus Accuracy

Precision refers to the ability to test 1 sample and repeatedly obtain results that are close to each other. This does not infer that the mean of these very similar numbers is the correct number (see Figure 1–5). Some analyses, which have great precision, are very inaccurate. The accuracy reflects the relationship between the number obtained and the true result. Thus, a sample could have high accuracy but low precision if it provides the correct answer but has substantial variability as the sample is repeatedly tested.

Analyzing Errors in Laboratory Performance

There are 3 phases of laboratory analysis. The first of these is the preanalytical phase. This time frame is from patient preparation for the laboratory test, through the time of sample collection, until the sample arrives in the laboratory. Most of the errors in laboratory test performance occur in this phase. Examples of preanalytical errors are: inappropriate preparation of the patient, such as not fasting for a particular test in which fasting is required; ingesting drugs that will interfere with the laboratory tests; collection of the specimen in the wrong tube; delayed transport of the specimen to the laboratory; storage of the sample at an incorrect temperature; and collection of an inadequate amount of blood in vacuum tubes containing a fixed amount of anticoagulants. All these errors occur before the sample arrives for analysis and make it impossible, no matter how great the analytical precision within the laboratory, to provide a test result that truly reflects the patient's condition. The second phase is the analytical phase, which is the time that the sample is being analyzed in the laboratory. Errors can occur during this process, but they are much less common now because of the high level of automation of many laboratory instruments. Examples of analytical errors are: incorrect use of the instrumentation and the use of expired reagents. The third phase of laboratory test performance is the postanalytical phase, which begins when the result is generated and ends when the result is reported to the physician. Example of errors in this phase, which are more common than analytical errors but less common than preanalytical errors, are: delay in time to enter a completed result into the laboratory information system and reporting results for the wrong patient.

Minimizing Errors in the Selection of Laboratory Tests

As the number of laboratory tests has increased in size, complexity, and cost, health care providers are highly challenged to select the correct tests, and only the correct tests, in pursuit of a diagnosis. One approach commonly implemented to assist physicians in correct test selection is the use of a reflex test algorithm. Tests are ordered by algorithm selection, such as selection of an algorithm to determine the cause of a prolonged PTT result. Using the algorithm, the clinical laboratory notes the results of the first test in the algorithm, and that result determines which test is performed next. For example, if the prolonged PTT is further evaluated with a PTT mixing study, a normal result would direct testing toward assays for factors VIII, IX, XI, and XII. An elevated result in the PTT mixing study, on the other hand, would direct testing toward an inhibitor in the PTT reaction, such as a lupus anticoagulant. Testing is continued within the algorithm until a diagnosis, which explains the prolonged PTT in this case, is identified.

Laboratory test selection is also made more difficult because many laboratory tests have synonyms, and many compounds have related forms. For example, the test most commonly known as the lupus anticoagulant is also called the lupus inhibitor, and the general term that includes the lupus anticoagulant and related entities is antiphospholipid antibody. Vitamin D has several isoforms that include 25-hydroxyvitamin D and 1,25-dihydroxyvitamin D. Incorrect laboratory test selection is a major source of medical error.

Minimizing Errors in the Interpretation of Laboratory Test Results

With thousands of tests on the clinical laboratory test menu, it is impossible for a health care provider to understand the clinical significance of an abnormality for each test. This has become particularly noteworthy with the introduction of tests for genetic alterations, because there are so many and the clinical significance of the alterations may not yet be well established. In some institutions, narrative interpretations of complex clinical laboratory evaluations are prepared by experts in the field. In most institutions, such narratives require a special request for completion, but an emerging concept is to provide narrative interpretations for all complex clinical laboratory evaluations automatically, as they are provided in radiology and in anatomic pathology. Misinterpretation of laboratory test results has been increasingly noted as a source of poor patient outcome.

The Effect of Age on Laboratory Tests

There are a number of laboratory tests that have different normal ranges for patients of different ages. This is particularly important in pediatrics. Newborns especially have many different normal ranges than adults or older children for substances in blood and other bodily fluids. For example, several of the coagulation factors do not reach adult levels for many months after birth. As a second well-known example, the cholesterol level rises with age.

The Effect of Gender on Laboratory Tests

Gender has a significant bearing on many laboratory tests. Testosterone and estradiol are obvious examples. In addition, among women there are variations in the serum concentration of various hormones throughout the menstrual cycle.

The Effect of Body Mass on Laboratory Tests

Muscle mass can affect the level of certain compounds, such as creatine kinase, in the blood. It is also known that there is an increase in the serum cholesterol level with obesity, because the cholesterol level is related to the amount of body fat.

Preparation of the Patient for Laboratory Testing

For certain laboratory tests, there are a number of special preparations of the patient that are necessary to provide the most clinically useful, accurate, and precise result. One of the most commonly encountered patient preparations is fasting, usually for 8 to 12 hours, depending on the test. The serum triglyceride level can be significantly affected by eating, and fasting is absolutely required. Another test for which fasting is required is the fasting blood glucose used in the evaluation of a patient for diabetes.

Patient Posture for Blood Collection

Patient posture may affect the result for certain tests. There is a lower plasma volume when the patient is upright because there is pooling of fluid in the dependent parts of the body when standing. When the patient is supine, there is a movement of fluid back into the circulation from the tissues. The extra volume in the circulation can dilute certain compounds in the blood. It is best to monitor the patient in the same postural position if the test result is affected by posture and if the values need to be compared with one another over time.

Differences in Test Results Between Samples of Venous, Arterial, and Capillary Blood

Venous blood may have a different concentration of a compound than arterial blood. The best examples are the blood gases that show marked differences between arterial and venous blood because of the exchange of gases in the lungs. There may also be a difference between capillary blood and arterial and venous blood. Blood glucose values may differ significantly in capillary (finger-stick) samples from venous or arterial blood.

Analytical Interferences in Laboratory Testing

Interferences may result in falsely high or falsely low values, depending on the interfering substance and the particular test. Although there are many compounds that can interfere with the accurate and precise quantitation of a compound, there are 3 major interferences that must be considered when selecting and interpreting results of laboratory tests. These are hemolysis that makes plasma and serum red; elevated bilirubin that makes plasma and serum shades of orange, green, or brown; and lipemia that makes plasma and serum milky white. There are many drugs, particularly those that color the plasma and serum, that can produce significant analytical interference. Many automated laboratory tests are spectrophotometric, and therefore depend on measurable changes in the color of plasma or serum after a chemical reaction. This is why alterations in the color of the serum or plasma often interfere with laboratory test performance.

Impact of Drugs on Laboratory Test Results

Drugs can affect laboratory tests in 2 ways—as an interfering substance in the laboratory test only and by producing an effect in the body that alters a laboratory test result. For example, there are many drugs that will increase the PT in patients receiving warfarin (coumadin) by an in vivo potentiation or diminution of warfarin-induced anticoagulation. There are a number of drug effects, however, that alter the result of a particular test strictly in vitro, and do not change anything in vivo.

The Use of Screening Tests Before Esoteric Tests

Screening laboratory tests are typically inexpensive, easy-to-perform assays that indicate whether additional tests need to be performed to reach a diagnosis. Whenever possible, if a screening test is available, it should be used before the more expensive or time-consuming tests are performed. An example of the use of a screening test is the partial thromboplastin time (result within minutes/hours and at low cost) to assess a major portion of the coagulation cascade. Only if this value is elevated should tests be performed for PTT-related coagulation factor deficiencies (results within several hours and at high cost).

The Danger of Ordering Too Many Laboratory Tests

As noted in the discussion of the normal range, 5% of individuals who have no disease can fall outside of the reference range established by the central 95% of healthy individuals. Thus, if an individual without disease has 20 different tests, it is likely on a statistical basis that he/she will have 1 abnormal value (5% = 1 of 20). In medical practice, the abnormal test result for the normal patient often leads to further evaluation and raises suspicion for a disease that does not exist. Thus, by limiting the number of tests ordered for a patient to those relevant to the clinical presentation of the patient, one is less likely to encounter false-positive or false-negative results.

The Importance of Turnaround Time

An accurate and precise laboratory test result provided after a decision has been made regarding patient management is of no value. Since results for all laboratory tests cannot be provided immediately, the physicians and laboratory personnel must decide on clinically relevant turnaround times for each laboratory test. In addition, if a patient is not discharged from the hospital because of a delay in laboratory testing, this may have a significant financial impact from unnecessary length of stay. All steps related to turnaround time, from ordering of the test to the reporting of the result, must be carefully analyzed and shortened as much as possible.

Tubes for Blood Collection

There are a number of different tubes into which blood may be collected. The tubes used for the vast majority of collections contain a vacuum to help draw the blood into the tube. The tops of the tubes have a different color depending on the contents of the tube prior to blood collection (Table 1–1). Several of the tubes contain anticoagulants to prevent the clotting of the blood in the tube. Clotted blood that is centrifuged to remove the clot and any cells is known as serum. Blood that has not been clotted and is then centrifuged to remove any cells is known as plasma. For many laboratory tests, the same result is obtained in an assay if serum or plasma is used. However, this is often not the case. The clotting of the blood, for example, makes blood cell counts and coagulation tests impossible because the clotting factors are consumed in the clot and the blood cells become trapped in it. If the clotting of the blood to form serum is not absolutely necessary, tests can be performed with a shorter turnaround time using plasma because there is no requisite time to wait for the blood clot to form. The amount of anticoagulant in the light blue-top tube must be in a specific proportion to the blood volume in the tube, usually 9 parts blood to 1 part citrate solution. When an inadequate amount of blood is collected into a blue-top tube, the ratio of blood to anticoagulant is less than 9:1. This can result in spuriously high values for the PT and PTT tests. Thus, light blue-top tubes must be filled appropriately to obtain accurate results for clotting tests.

Timing of Blood Collection

Patients may have a need to present for phlebotomy at a certain time of the day if the parameter being measured has a diurnal variation in its concentration.

Dynamic tests involve the measurement of a patient response to a treatment or stimulus, and timing of collection is important in these studies. The oral glucose tolerance test, in which plasma glucose levels are measured after the oral ingestion of a glucose solution, is an example of such a test.

A third situation in which timing of sample collection is important is in therapeutic drug monitoring. The serum level of certain drugs is measured to determine if the concentration is within the therapeutic window. The serum level of a drug varies greatly as the drug is absorbed, distributed, and metabolized, so the timing of collection must be consistent. For the monitoring of many drugs, a “trough” level is obtained just before the next dose of the drug is administered.

The Release of Plasma Markers of Organ Damage from Injured Cells

When cells are injured, components of the cells can leak out of the damaged or dead cells and make their way into the systemic circulation. This permits the measurement of these “marker” compounds in the serum or plasma as a test for injury to the organ. The most important features of plasma markers of cell injury are that: 1) they are not rapidly removed from the circulation; 2) they are relatively organ specific so that the damaged organ is identified; and 3) the compound is precisely and accurately measured in the clinical laboratory. A well-known example includes the release of the creatine kinase-MB fraction and troponin from myocardial cells injured by ischemia in myocardial infarction.

Markers of Inflammation and the Acute-phase Response

The concentration of many plasma proteins changes significantly in patients with inflammation. Infections (even minor viral illnesses), autoimmune disorders, and many other conditions result in an increased concentration of proteins known as acute-phase reactants. Commonly used tests to assess the severity of inflammation, from whatever cause, are the erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP). Examples of acute-phase reactant proteins include fibrinogen, which can rise as much as 10-fold over baseline, and von Willebrand factor, which can rise 2- to 3-fold over baseline. The rise in von Willebrand factor with inflammation can mask a deficiency of von Willebrand factor in patients with von Willebrand disease, and this highlights the need to obtain baseline values after an acute-phase response subsides for accurate diagnosis.

The Serologic Diagnosis of Infectious Disease

It is not uncommon to suffer an infection with an organism that is not identifiable by Gram staining or other microscopic analysis and is not readily cultured. For these infections, the diagnosis is often made by identifying and measuring the amount of antibody produced in response to an antigen derived from the infectious agent. The antibody response typically takes several days to a week or 2 (dependent on past exposure) to emerge, and the appearance of IgM antibody before IgG occurs in most infections. This is why the presence of IgM antibody in a serologic test is likely to reflect an acute infection rather than past exposure. Serologic tests may also be designed to detect and measure an antigen associated with the infectious agent. This obviates the inherent delay in diagnosis of the infection of up to approximately 2 weeks while waiting for the antibody response to occur.