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## Revista de Saúde Pública

##
*On-line version* ISSN 1518-8787

*Print version* ISSN 0034-8910

### Rev. Saúde Pública vol.38 n.2 São Paulo Apr. 2004

#### http://dx.doi.org/10.1590/S0034-89102004000200023

**ORIGINAL ARTICLES**

**Estimate
of the validity of a new method for the isolation of rabies virus**

**Yeda
L Nogueira**

Serviço de Virologia do Instituto Adolfo Lutz. São Paulo, SP, Brasil

**ABSTRACT**

**OBJECTIVE:**
No population-based studies have been conducted to show the potential for the
use of virological diagnosis of the rabies virus. The objective of the present
study was to estimate accuracy parameters for the isolation of the rabies virus
in McCoy cells as an alternative method and to compare this with the use of
murine neuroblastoma (N2A) cells, which is considered to be a reference method.

**METHODS:** An evaluation was performed on 120 bats collected at random
in the Atlantic Forest of the State of São Paulo. The immunofluorescence
reaction was utilized for the detection of the rabies virus isolated from the
brain of these bats and the presence of the virus was tested in the two cell
culture systems. Two data sets were constructed with the results and the analysis
was performed using the computer methods for diagnosis tests (CMDT) software
by means of the two-graph receiver operating characteristic (TG-ROC) technique
to determine sensitivity and specificity parameters, as well as other indicators
such as efficacy, positive predictive value, negative predictive value and likelihood
ratio.

**RESULTS:** N2A cells presented 90% sensitivity and specificity, while McCoy
cells presented 95% sensitivity and specificity. These values were based on
cut-off points optimized for each cell type.

**CONCLUSIONS:** The study showed that McCoy cells allowed the obtaining
of accuracy estimates that were better than for N2A. The McCoy cell method is
therefore an effective method for the isolation of the rabies virus.

**Keywords:
**Rabies
virus, isolation. Rabies, diagnosis. Chiroptera. Sensitivity and specificity.
Predictive value.

**INTRODUCTION**

Murine neuroblastoma
cells derived from different clones were introduced for the isolation of the
rabies virus from 1978 onwards,^{19,23} and also for the study of the
pathogenesis of rabies.^{22} Cultured cells have also been utilized
to produce kits for serology use.^{16}

World Health
Organization (WHO) experts used to recommend the inoculation of the rabies virus
in young mice (up to 21 days old), known as the biological test, in which the
diagnostic examination was done after death. However, after successive studies
that compared inoculation in mice with isolation of the virus in murine neuroblastoma
cells, they accepted that this latter method could be utilized for diagnosing
the disease, in conformity with the methodology described in the laboratory
technique manuals for rabies.^{3,20}

The first
results from the isolation of the rabies virus in McCoy cells^{12} demonstrated
that these cells easily isolate the rabies virus. In studies comparing the results
obtained from titration in mice and McCoy cells (end point calculations),^{13}
excellent replication of the rabies virus in McCoy cells has been demonstrated,
thereby indicating the possible use of these cells in rabies virus assays.

McCoy cells
present the characteristic of great sensitivity for rabies virus isolation.
A clinically suspected rabies case was described,^{14} in which the
classic biological test did not detect the rabies virus. The virus was isolated
from the patient's spinal fluid and it was subsequently proven that this was
in fact a case of human rabies, after a long period without the occurrence of
autochthonous rabies in the State of São Paulo.

This capacity of McCoy cells for isolating the rabies virus, even at low concentrations (low viral load), makes this method a very useful tool in the study of the circulation of the rabies virus in natural forest reservoirs.

It must, however, be remembered that despite its efficacy, the rabies virus isolation method using McCoy cells has not yet been validated for use in disease diagnosis laboratories. Nonetheless, isolation of the rabies virus via these cells greatly facilitates the diagnosis, since the results from this method are compatible with the biological test. Moreover, these cells are easy to handle and have much lower maintenance costs than murine neuroblastoma cells (N2A) because, as well as requiring minimal nutritive medium, McCoy cells also only need half as much bovine fetal serum for supplementing the culturing medium. Nor can the costs be compared with the maintenance costs of a colony of mice.

Effectively,
what was missing was a population-based study for validating this alternative
methodology. The present study was therefore devised with the objective of validating
the McCoy cell methodology, utilizing N2A cell culturing as a reference method,
in accordance with the validation model proposed by Greiner & Gardner.^{8}
These authors attributed a utility value to receiver operating characteristic
(ROC) curves, since graphical analysis allows estimates of important parameters
to be made, thereby obtaining the best relationship between sensitivity and
specificity and optimizing the cutoff value for a given target population with
a known prevalence.

**METHODS**

The validation study was performed on a random sample of bats captured in the Intervales State Park, State of São Paulo, Brazil, and evaluations of the presence of rabies virus infection were made using the two cell culture systems.

Five collections were made over a 20-month period, in which adult bats of various species and both sexes were captured. This was therefore an epidemiological survey (screening) for assessing the presence of naturally circulating rabies virus.

The results
from the study were compared by means of indicative measures such as sensitivity,
specificity, positive predictive value, negative predictive value, efficiency,
Youden index,^{24} incorrect classification and positive and negative
likelihood ratio, utilizing the technique of Two Graph Receiver Operating Characteristic
(TG-ROC),^{7} by means of the Computational Methods for Diagnostic Tests
(CMDT) program.^{4}

The isolation
attempts were performed by means of inoculation of 2% solution of liquefied
brain from each captured bat (analysis unit), into the two different cell culture
strains: murine neuroblastoma cells (N2A; reference method) and McCoy cells^{12}
(method to be validated). Two consecutive runs of each brain solution were done
in each cell culture type. The second run was done on 96-well plates, with three
wells per analysis unit (brain). To preserve the conditions of a blind test,
each brain was numbered and coded, thereby making it impossible to recognize
the bat species that was being analyzed.

The laboratory diagnostic interpretation was based on reading the fluorescent foci observed directly from the wells after the direct immunofluorescence, using an inverted IM-35 microscope IM-35 (Zeiss).

The study variable was thus linked to the laboratory diagnosis, which ranged across a scale from zero to 4+. The reaction was considered to be positive for values of 1+, 2+, 3+ and 4+.

The bat
sample size calculation^{11} was based on the rabies prevalence that
was predicted and already known from isolation using murine neuroblastoma cells
(N2A),^{20} which was set at 10%. The precision was stipulated to be
5% and the confidence interval 95%. The minimum number of bats required was
estimated to be 138. Although 166 bats were captured, only 120 were analyzed,
due to losses and the exclusion of pregnant females. Thus, it was necessary
to adopt other parameters for finite populations, in accordance with the same
authors.^{11} It was therefore considered that, for a sample of 120,
the prevalence of the disease in a population in which the disease is not endemic
would range from 0.3 to 1.5% (representing the expected number with the desired
characteristic) and so the same 10% prevalence of infection expected via the
N2A method was maintained. The number of 120 bats was considered to be the minimum
sample size to be studied with a confidence interval of 95%.

A complementary sample of 19 bats from the Zoonosis Control Center of the Municipality of São Paulo was also utilized. The objective was to compare the results obtained from isolation in cell cultures (McCoy and N2A) with the biological test (inoculation in mice), to assess the degree of concordance between the three methodologies.

The results
from the diagnoses made on the 120 bats were placed in a databank supported
by the Epi Info 6.4 program,^{5} and were subsequently exported to other
statistical programs such as Medcalc^{18} and CMDT.^{4} These
programs enabled calculation of the sensitivity and specificity parameters and,
from these, other indicators: efficiency, Youden index,^{24} likelihood
ratios, incorrect classification and the positive and negative prediction values.

In addition
to obtaining the optimized values, i.e. with the least losses in the sensitivity
and specificity parameters, the best value for the cutoff point for the diagnostic
method was also determined. The Bland & Altman technique^{2} was
utilized for assessing the sampling bias, and the Passing-Bablok technique^{15}
for checking the linearity between the two methods. Wilcoxon^{17} statistics
were run to evaluate the differences between the averages for the two groups
(N2A and McCoy cell systems), and the Spearman correlation coefficient^{17}
was determined for checking the correlation between the two methods.

**RESULTS
AND DISCUSSION**

Via the
Wilcoxon test,^{17} the difference between the averages gave a p-value
of 0.046, with 15 positive differences and 23 negative differences between the
paired results, which represented a significant difference, albeit very close
to the significance limit of 0.05. The Spearman test,^{17} comparing
the same paired results from the two methods, detected that there was a statistically
significant correlation (p=0.0001) between the two methods, with r=0.614 (0.489-0.715).

Figure
1 shows the straight-line Passing-Bablok regression^{15} and demonstrates
linearity between the two methods, although significant proportional deviation
is presented (p<0.01). This analysis was performed by means of testing a
hypothesis, and this is presented in the Appendix.

From the
Bland & Altman analysis,^{2} the result observed also showed that
there was no bias in the sampling, even though the resultant average value from
the differences between the pairs of readings from the two cell systems was
-3.5, when the ideal average should be zero. Nonetheless, this value is within
the tolerance limits, i.e. within the limits of the average plus two standard
deviations, when considering a non-biased sample that is interpreted in the
light that one method could substitute for the other.

Figures 2A and 2B show the TG-ROC graphs for the two cell systems (N2A and McCoy), with the determination of the optimized values for the sensitivity and specificity parameters. Another important result obtained from the graphs was the cutoff point, because this enabled the minimization of the effects of false positives and false negatives.

Table 2 shows the indicators obtained using the most appropriate cutoff point from the graphical analysis that was performed using the TG-ROC technique to optimize the sensitivity and specificity parameter estimates. In the case of N2A cells, these estimates were 90% for both sensitivity and specificity, and the cutoff point that determined these indicators was 1+, i.e. 25% of the cells in the microscope field were infected. For this cutoff point, the estimates of other indicators also presented optimized values: the test efficiency indicator was 90%, while the probability of classifying the observed results wrongly was 9%. The positive likelihood ratio, defined as the chance that a positive result would diagnose true disease and not a false result, was 9, which is the same as saying that the chance of a positive result being diagnosed as a true disease is nine times greater than for this diagnosis to represent a false positive result. The negative likelihood ratio for the same cutoff point was 0.11, which implies that for a negative diagnosis there is a chance of 11:100 that this result is a false negative.

With regard to McCoy cells, the same indicators presented results that were better than those observed for N2A cells. The estimates of sensitivity and specificity were 95%, despite a cutoff level that was also within the 1+ band. However, the proportion of cells infected corresponded to 38% of the visual field observed under the microscope.

The positive likelihood ratio for McCoy cells was 19, thus demonstrating that the chance that a positive diagnosis in a healthy population would be true was 19 times greater than the chance that this was a false positive result, for this cutoff point of 38%. This chance was twice what was found using the N2A cell methodology. Meanwhile, the estimate of the negative likelihood ratio was 0.052, which represented a chance of 5% that the result would be a false negative. This was half of what was found for N2A cells. In other words, for McCoy cells, only 5:100 of the diagnoses could be false negative results.

The efficiency of the test using McCoy cells was 95%, thus demonstrating that McCoy cells presented superiority or greater facility for isolating the rabies virus in relation to N2A cells.

Nonetheless,
the method of reading at microscope crosshairs may be subjective and present
a few variations, depending on the observer. This differs from mechanical reading
of optical density or radioactivity, in which the results obtained are continuous
numbers. But even so, the immunofluorescence technique presents sensitivity
and specificity of 98%,^{4} which means that for a well-trained observer,
errors would be rare. However, in attributing limiting values it is indeed possible
for differences to occur between observers, especially in attributing values
between 1+ and 2+. Thus, some false positive or false negative results could
occur in this "gray zone", which is also the location where the cutoff point
is established. In this situation, the number of results considered to be false
positives or false negative could increase or decrease, depending on each observer.
It may happen that the cutoff point is decided arbitrarily, thus affecting the
definition of the sensitivity and specificity values. This point is therefore
a critical factor in laboratory tests.^{8}

In Figures
3A and 3B, the distributions of the results from reading
at microscope crosshairs can be seen. It is precisely between the values attributed
for 1+ and 2+ that there is the greatest difference between the methods. In
Figures 2A and 2B, the cutoff level
divides each figure into a left-hand side representing negative values and a
right-hand side representing positive values. It can be seen that the cutoff
values are above the 1+ value (25%) for N2A cells and at 37.5 % for McCoy cells,
thereby eliminating the possible false negative readings and giving a good safety
margin for the correct diagnosis. This can also be seen via the Youden index,^{24}
which has a value of 90% (Table 2).

It needs
to be remembered that the diagnostic tests are not perfect, but a correct diagnosis
is highly probable. A test would only be considered perfect when the sensitivity
and specificity were 100%, when the prevalence of the disease was correctly
ascertained and when compared with the gold standard, remembering that the latter
is the method that is capable of reproducing the disease or diagnosing the true
disease, for example biopsy.^{10}

In the case
of rabies, the method considered to be the gold standard, other than a postmortem
biopsy, could be the inoculation into mice of material collected from the patient
(the biological test). In this case, the isolation accomplished through the
test will detect the disease and not the infection, as occurs with the two cell
culturing methods. Thus, in Table 3 it can be seen that
the isolations performed on cell cultures show that only the 3+ results obtained
from McCoy cells concord with the positive results from the biological test.
This is equivalent to 75% of the infected cells observed in the visual field
of the microscope. For the three cases that were positive in the biological
test, the N2A cells presented two values of 2+ and only one of 3+. The Spearman
correlation test^{17} presented a strong correlation between the two
methods of cell culturing, with an *r* coefficient of 0.797 (0.536-0.918)
and a p-value of 0.0007, while the coefficients between the biological test
and the two cell methods presented moderate correlation values of *r*=0.647
(0.273-0.851) and *p*=0.006 for N2A and *r*=0.677 (0.536-0.918) and
*p*=0.004 for McCoy. The correlation value between the two cell culturing
methods for the second analysis (i.e. relating to the data set of Table
3) was greater than the correlation value for the first analysis (i.e. relating
to the data set of Table 1), but it must be remembered that
in the second analysis, the bats were collected from a location with a rabies
outbreak, i.e. a place where rabies cases had already been found in bats, thus
differing from the first analysis, in which the sample was collected randomly
and presupposed healthy animals.

In future work, this question of the cutoff point should be analyzed in more detail, to determine the true status of the disease and infection and to indicate whether the virus is circulating among the bat population.

In conclusion,
the isolation method utilizing McCoy cells presented accuracy indicators that
were all higher than those for N2A cells. Analysis via the TG-ROC technique
was very useful for estimating the indicators for this preliminary validation
of the two cell systems as diagnostic methods. The graphical analysis of the
TG-ROC performed using the CMDT computer program^{4} allowed the sensitivity
and specificity parameters to be visualized and from these, all the other indicators
could be estimated, thereby eliminating the non-parametric sample distribution
bias.

The receiver
operating characteristic (ROC)^{25} technique is considered to be a
valuable method for comparing alternative tests for a given diagnostic method.
It gives the best sensitivity and specificity parameters for results that present
normal distribution, and this is why TG-ROC analysis was the most appropriate
technique for estimating the validity parameters in the present study.

Another
question that must be analyzed relates to the reference standard utilized. Neuroblastoma
cells are an imperfect reference standard because, according to established
criteria,^{9} negative results from isolation in cells does not always
signify that the animal is not infected, since the specificity is not 100%.^{8}
Even in the test that is considered to be the gold standard in this case, the
biological test, it is only possible to obtain a positive diagnosis in situations
in which the viral titer presents sufficient lethality to kill 50% of the animals
inoculated. Thus, the viral particle concentration needed is greater than the
viral concentrations found in forest reservoirs or natural samples.^{10}
The virus circulating in reservoirs keeps to low concentrations so that infection
can take place and be maintained in the species that shelter it.^{1}

Isolations
performed using cell cultures consider the number of viral particles in the
inoculation that would be capable of infecting the cell while not being subject
to interference from the immune response. On the other hand, in mice the immune
response may interfere with and mask the infection, thus giving rise to asymptomatic
infected animals. In such cases, for the immune response to be overcome and
the animal to become sick, a greater viral load is needed. Even so, there is
no set viral load at which this will take place, and the viral load required
may be larger or smaller, depending on the mouse's own capacity to respond well
or not, i.e. animals with a good response require larger loads, while those
with a poor response require a lower viral concentration to sicken, since they
present low immunity. It must also be remembered that low concentrations of
live virus may, when inoculated, function as vaccines and induce an immune response.
Such theoretical considerations^{21} must therefore be taken into account
in the choice and analysis of the gold standard.

The validation
of diagnostic tests without a gold standard may run the risk of bias and overestimation
of the results.^{8} Study designs may also lead to biased analysis:
epidemiological surveys (screening) of infectious diseases, for example, are
very difficult to validate because, if the methodology utilized is inappropriate
for the diagnosis, there may be subpopulations with latent infection within
the sample population. Such factors may lead to biased results. Other validation
techniques must then be observed so as to better estimate the accuracy of a
new diagnostic method. These involve computed estimates utilizing the maximum
likelihood function from the point of view of Bayesian inference.^{6}
In a future study, an analysis of this type will be performed in order to define
the true status of the disease and its prevalence in the forest reservoir studied.

**ACKNOWLEDGEMENTS**

To Prof. Dra. Sabina L. D. Gotlieb for reading and making suggestions for this text.

**REFERÊNCIAS**

1. Anderson R, May R. Coevolution of hosts and parasites. *Parasitology* 1982;85:411-426. [ Links ]

2. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. *Lancet* 1986;8:307-11. [ Links ]

3. Bourhy H, Sureau P, Hirose JM. Comparaison des techniques de detection et d' isolament. In: Institute Pasteur. Methods de laboratoire pour le diagnostic de la rage*.* Paris; 1991. p. 78. [ Links ]

4 Briesofsky J. *Computer Methods for Diagnostic Tests* (CMDT). <URL:http://www1.vetmed.fu-berlin.de/~mgreiner/CMDT/poster.htm> [2004 Mar 8] [ Links ]

5. Dean AG, Dean AJ, Comlombier D, Burton AH, Brendel KA, Smith DC et al. Epi Info version 6: a word processing, data base, and statistics program for epidemiology on microcomputers. Atlanta: Center for Diseases Control and Prevention; 1994. [ Links ]

6. Enoe C, Georgiadis MP, Johnson WO. Estimation of sensitivity and specificity of dianostic tests and disease prevalence when the true diseade state is unknown. *Prevent Veterinary Med* 2000;45:61-81. [ Links ]

7. Greiner M. Two-graph receiver operating characteristics (TG-ROC): update version supports optimisation of cut-off vallues that minimise overall misclassification costs. *J Immunol Methods* 1996;191:93-4. [ Links ]

8 Greiner M, Gardner IA. Epidemiologic issues in the validation diagnostic tests. *Prevent Veterinary Med* 2000;45:3-22. [ Links ]

9. Greiner M, Pfeiffer D, Smith RD. Principles and practical application of receiver-operating characteristic analysis for diagnostic tests*. Prevent Veterinary Med* 2000;45:23-41. [ Links ]

10. Krammer HC. Evaluating medical tests- objective and quantitative guidelines. Newbury Park: Sage Publications; 1992. [ Links ]

11. Lwanga S, Lemeshow S. Sample size determination in health studies. Genève: WHO; 1991. [ Links ]

12. Nogueira YL. Rabies virus in McCoy cell line. Part I: Cytopathic effect and replication. *Rev Inst Adolfo Lutz* 1992;52:9-16. [ Links ]

13. Nogueira YL, Amaral CA. Rabies virus in McCoy cell line. Part II: Titration*. Rev Inst Adolfo Lutz* 1992;52:17-21. [ Links ]

14. Nogueira YL. Morphometric analysis of McCoy cells inoculated with cerebrospinal fluid from patient with rabies. *Mem Inst Oswaldo Cruz* 1998;93:509-14. [ Links ]

15. Passing W, Bablok H. A new biometrical procedure for testing the equality of measuraments from two different analytical methods. Aplication of linear regression procedures methods for comparison studies on clinical chemistry (Part I). *J Clin Chem Biochem* 1987;21:709-20. [ Links ]

16. Perrin E, Rolin PE, Sureau P. A rapid rabies enzyme immuno-diagnosis (RREID): a useful and simple technique for the routine diagnosis of rabies. *J Biol Stanrdization* 1986;14:217-22. [ Links ]

17. Sachs L. The comparation of independent data. In: Applied Statistics A Handbook of Techniques. 2nd ed. New York: Verlag Spring; 1984. p. 299-303. [ Links ]

18. Schoonjans F. MedCalc statistics for biomedical research. Belgium; 1998. [ Links ]

19. Smith A, Tignor G, Emmons R, Woodie J. Isolation of field rabies strains in CER and Murine Neuroblastom cell culture. *Intervirol* 1978;9:359-61. [ Links ]

20. Smith JS, King A. Monoclonal antibodies for identification of rabies and non-rabies lyssavirus: In: Meslin FX, Kaplan MM, Koprowski H, editors. Laboratory in rabies. 4th ed. Geneva: World Health Organization, 1996. p. 133-44. [ Links ]

21. Somoza E, Mossman D. Comparing and optimizing diagnostic tests: information-theoretical approach. *Med Decis Making* 1992;12:179-88. [ Links ]

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23. Webster W. A tissue culture infection test in routine rabies diagnosis. *Can J Vet Res* 1987;51:367-9. [ Links ]

24. Youden D. Index for rating diagnostic tests. *Cancer* 1950;3:32-5. [ Links ]

25. Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots- a fundamental evaluation tool clinical medicine. *Clin Chem* 1993;39:561-77. [Erratum in Clin Chem 1993;39(8):1589]. [ Links ]

**
Correspondence to
**Yeda
L Nogueira

Departamento de Epidemiologia Faculdade de Saúde Pública - USP

Av. Doutor Arnaldo, 715

01246 904 São Paulo, SP, Brasil

E-mail: ynogueir@usp.br

Received
on 27/1/2003

Reviewed on 28/7/2003

Approved on 13/10/2003

Based on a doctoral thesis presented to the School of Public Health, University of São Paulo, in 2001.

**APPENDIX**

**Passing-Bablok
regression**

The interpretation of the results depends on analysis of the Passing-Bablok regression equation, as follows, in which:

Variable X = N2A;

Variable Y = McCoy;

Sample =120.

*Regression
equation:*

Y = 0.0000 + 1.0000 X

Where:

Intercept A = 0.0000 (95% confidence interval = -1.0000 to 0.0000)

Slope B = 1.0000 (95% confidence interval = 1.0000 to 2.0000)

Linearity test:

Standard deviation of the linearity: (P<0.01)

This expression is understood in the following manner. The confidence interval of the intercept A can be used as a hypothesis test, in which:

• H0: the two methods are equal

• HA: the two methods are different

According to the Passing-Bablok technique (1983), the straight-line regression result is evaluated in the form of a hypothesis test, in which:

• A = 0; the hypothesis is accepted if the 0 is within the confidence interval

For the value of the straight-line slope (B), the confidence interval can again be used as a hypothesis test, in which:

• H0: the two methods present the same linearity

• HA: the two methods present different linearities.

To accept H0, the value of B needs to be 1 and this value must lie within the confidence interval. If the value of B differs from 1, H0 is then rejected and HA is accepted. This latter result indicates that there is linearity but it is proportionally different, since if p<0.01, this value defines the deviation of the linearity.

B = 1.0; confidence interval (1.0 2.0)