Download WHAT DOES A POSITIVE TEST MEAN?

2014 ANZCVS Science Week
WHAT DOES A POSITIVE TEST MEAN?
Sue Foster BVSc MVetClinStud FANZCVS
Vetnostics, 60 Waterloo Rd, North Ryde, NSW 2113
Murdoch University, Murdoch, WA 6150
In order to get the most out of clinical pathology testing, one must a) request the correct tests and b) understand
the relevance of the reported results. This holds for infectious diseases, haematology and biochemistry.
It is important to maintain a reasonable level of scepticism about laboratory results. Do not believe all the
numbers. Unexpected results are common and may necessitate clinical re-evaluation. Alternatively, unexpected
results may be erroneous or misleading. Trends over several days are often more informative than single results.
Typically, not all test results that “should” be abnormal in a disease situation are present. Conversely, not all
results for a normal healthy animal will be within normal reference intervals. Reference intervals represent 95%
of normal animals, thus 5% of results will fall outside the reference intervals and, in a panel of 20 tests, only
36% of normal animals will have normal results for every test.
In addition to these factors, all tests have inherent error and variation. The error of a differential white cell count
may be 10-20% due to technique thus mild changes from one day to the next may reflect variation in the
procedure rather than actual changes in the patient.
Every test result needs to be evaluated carefully. Negative and positive predictive values should be assessed for
each result and that requires some basic statistical knowledge. It is worth considering a clinical example to put
predictive values into context.
Feline Leukaemia Virus (FeLV) testing
In order to interpret FeLV tests, it is necessary to quickly review the virus, its transmission, pathogenesis and
sequelae.
FeLV is a retrovirus containing single stranded RNA within a hexagonal capsid (made up of repeating units of
the major core protein p27) surrounded by an envelope. Core proteins like p27 are produced within infected
cells and may also circulate free in plasma; p27 can be detected by test kits. There are three subgroups: A (found
in all FeLV cats, least pathogenic, most likely to be latent or regressive), B (likely to cause malignancy), C
(causes fatal aplastic anaemia).
Transmission occurs primarily via saliva with most cats infected by oronasal exposure. Kittens are more likely
to be infected by maternal licking than transplacentally. Close contact is required for spread of infection from
shedding to susceptible cats.
The outcome of infection in any individual cat depends on strain of virus, exposure dose, exposure duration, age
and immune response. There are several potential outcomes:
- Progressive infection (cats have insufficient immunity and succumb to FeLV-associated diseases
within a few years)
- Regressive infection (infection is contained by the cat’s immune response prior to or at the time of
bone marrow infection and there is little risk of FeLV-associated disease and no shedding; FeLV is
integrated within the cat’s genome thus provirus (DNA) can be detected by PCR)
- Abortive exposure (no viraemia by any test method; rare)
- Focal infection (infection is restricted to certain tissues such as spleen, mammary gland, eye; FeLV is
integrated within cat’s genome thus provirus can be detected by PCR; rare).
Cats are p27 antigen positive 2-3 weeks post-infection in progressive, regressive, or focal infections but only
remain antigen positive if the infection is progressive. If infection is regressive or focal, p27 antigen will be
negative 2-8 weeks (sometimes months) post-infection but cats will be PCR positive.
Pathology induced includes tumours, myelosuppression, immunosuppression (e.g. lymphopenia and altered
lymphocyte function resulting in opportunistic infections), glomerulonephritis and reproductive losses.
Most FeLV cats die from infectious diseases not tumours. Veterinarians sometimes use FeLV tests to rule in or
rule out lymphosarcoma (lymphoma), the most common tumour induced by FeLV. Worldwide, the incidence of
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FeLV-related lymphosarcoma has decreased. In Australia, lymphosarcoma is more likely to be associated with
FIV than FeLV.
There are some other generalisations that can be made about lymphoma and FeLV:
i)
Alimentary lymphosarcoma is usually in older FeLV negative cats
ii)
Mediastinal lymphosarcoma in young cats is often FeLV positive (but not in young Siamese in
which it can be a curable disease)
iii)
Spinal lymphoma is often associated with FeLV
In general, FeLV positive cats are young cats. It is difficult experimentally to infect kittens older than 4 months
old as macrophage function matures with age. The highest prevalence of FeLV antigenaemia is found in cats
less than 6 years old and 80% of cats persistently positive on antigen testing, will die within three years.
Serologic diagnosis of FeLV is usually made by detection of viral proteins (antigens) in the cat’s blood and use
of enzyme-linked immunosorbent assay (ELISA) kits is common. Immunofluorescent antibody (IFA) tests can
be performed by some laboratories to detect cell-associated antigen in blood or bone marrow samples. However,
the availability of viral PCR to detect FeLV provirus (DNA) and free plasma virus (RNA) has significantly
enhanced understanding of the pathogenesis of FeLV and it has become apparent that antigen detection is a
relatively insensitive indicator of infection.
A positive ELISA test which detects p27 in the blood could indicate:
i)
progressive infection
ii)
regressive infection
iii)
focal infection
iv)
false positive in a cat that has no FeLV antigen (test specificity)
A negative ELISA FeLV test indicates:
i)
truly negative
ii)
insufficient time
iii)
regressive infection
iv)
focal infection
v)
abortive exposure
vi)
false negative in a viraemic cat (test sensitivity)
Thus, there are quite a few possible interpretations for both positive and negative results and in order to assess
the results further, statistics are required.
Simple and clinically useful statistics
Sensitivity of a test result = number of true positive tests
true positives and false negatives
-
the higher the sensitivity, the more likely an infection will be detected (decreased chance of false
negatives)
Specificity of a test result =
-
number of true negative tests
true negatives and false positives
the higher the specificity, the lower the chance of having false positives
Positive predictive value =
prevalence x sensitivity
prevalence x sensitivity + (1-prevalence) x (1-specificity)
Negative predictive value =
prevalence x specificity
(1-prevalence) x specificity + prevalence x (1-sensitivity)
Whilst these values can be calculated mathematically, they can also be estimated intuitively.
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If, for example, a test has 100% sensitivity (which means that every infection will be detected) but only 98%
specificity then there will be two false positive results in every 100 tests.
If the infection is present in 2% of cats (e.g. FeLV in Sydney), then in each 100 cats there will be two true
positives and two false positives, thus the chance of the test giving a correct positive result (positive predictive
value) is only 2/4 or 50%. Conversely, the negative predictive value for the test in this situation is very high.
If the infection is present in 30% cats (e.g. an infected cattery) then in each 100 cats there will be 30 true
positives and two false positives, thus the chance of a test giving a correct result (positive predictive value) is
30/32 or 94%.
As prevalence (or disease likelihood) decreases, the positive predictive value decreases and the chance of a true
positive is less likely. As prevalence decreases, the negative predictive value (likelihood of normality) increases
and the chance of a true negative is more likely.
What about serum biochemistry?
Similarly, both normal (“negative”) results and abnormal (“positive”) results need to be assessed in light of
predictive values. For example, the positive predictive value of mildly increased alanine aminotransferase
activity on a pre-anaesthetic screening of a healthy young cat prior to spaying has a much lower positive
predictive value than the same activity in a cat with hyperbilirubinaemia.
Conclusion
Every test should be assessed on the basis of the sensitivity and the specificity of the test and the prevalence (or
likelihood) of the disease in the cat being tested. For every test there must be an understanding of the inherent
weaknesses of the test methodology, disease pathogenesis and the prevalence or likelihood of a particular
disease or disease process.
References
Beatty JA, Tasker S, Jarrett O et al (2011). Markers of feline leukaemia virus infection or exposure in cats from
a region of low seroprevalence. J Fel Med Surg 13:927-933
Cotter SM (1998). Feline viral neoplasia. In: Greene CE (ed), Infectious diseases of the dog and cat. 2nd edn.
Saunders, Philadelphia pp 71-84
Levy J, Crawford C, Hartmann K et al. (2008). 2008 American Association of Feline Practitioners’ feline
retrovirus management guidelines. J Fel Med Surg 10:300-316
Malik R, Kendall K, Cridland J et al (1997). Prevalences of feline leukaemia virus and feline immunodeficiency
virus infections in cats in Sydney. Aust Vet J 75:323-327
Tvedten H. General laboratory concepts (1999). In: Willard MD, Tvedten H, Turnwald GH (eds). Small animal
clinical diagnosis by laboratory methods. Saunders, Philadelphia, pp1-10
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