Guide to the Application of Genotyping to Tuberculosis Prevention
Applying Genotyping Results to Tuberculosis
Data that is collected as part of a genotyping program can provide
new indicators of program performance. TB programs that institute
selective genotyping will not be able to take full advantage of
these indicators, but programs that implement universal genotyping
will be able to use them to better evaluate program performance.
Interventions aimed at reducing TB transmission are fundamentally
different from interventions aimed at reducing the risk of reactivation
of LTBI. Universal genotyping provides the ability to differentiate
cases that probably resulted from recent transmission from cases
that were probably the result of reactivation of LTBI, and this
ability provides TB program staff with a method to separately monitor
changes in these two parameters. The NTCA/CDC Advisory Group on
Genotyping is working to develop standardized definitions and data
collection forms to assist TB controllers to monitor these important
PCR Clustering Percentage
The most basic indicator is the percentage of cases that are clustered
compared to the percentage that are not clustered. As discussed
in Chapter 4, Combining Genotyping and Epidemiologic
Data to Improve Our Understanding of Tuberculosis Transmission,
isolates that have genotyping patterns that match at least one other
isolate in a jurisdiction’s database are much more likely to represent
recent transmission than isolates with nonmatching genotypes. The
percentage of cases that are clustered gives the TB program a rough
guide to the amount of recent transmission occurring in their jurisdiction.
The genotyping laboratory report will designate whether each isolate
belongs to a PCR cluster, which will make calculating the percentage
of isolates that cluster by PCR straightforward. Since IS6110-based
RFLP results will not be available for all isolates, the PCR/RFLP
cluster designation will not be useful in calculating the percentage
of isolates that cluster.
In addition to calculating the clustering percentage, a TB program
can also compare the incidence of clustered cases with the incidence
of unclustered cases by dividing the number of clustered or unclustered
cases in a year by the jurisdiction’s population. These incidence
figures are better than the clustering index when comparing one
jurisdiction’s TB epidemiology to another’s.
Limitations of the PCR Clustering Percentage
As discussed in Chapter 4, Combining Genotyping
and Epidemiologic Data to Improve Our Understanding of Tuberculosis
Transmission, the majority of TB cases that are clustered do
not have epidemiologic links identified even when cluster investigations
are conducted by skilled interviewers. Although some cases for whom
no epidemiologic links were identified may have been involved in
recent transmission (i.e., they were involved in recent casual transmission),
this is probably unusual. Similarly, not all unclustered cases represent
reactivation of previous infections. These uncertainties mean that
the clustering percentage will be an imprecise measure of recent
Some of the uncertainty involved in using the clustering percentage
to estimate the frequency of recent transmission is minimized when
it is used to monitor trends over time, since any bias that applies
to a particular TB program’s population will be relatively constant
over time, at least for a period of several years.
Epidemiologically Confirmed Recent Transmission Percentage
Although the percentage of cases that are clustered (or the incidence
of clustered cases) is a useful and easy-to-calculate estimate of
recent transmission, it does not take into account whether the clustered
cases were found to have epidemiologic links. If TB programs routinely
collect and enter into their database information on epidemiologic
links, the epidemiologically confirmed recent transmission percentage
can be calculated, which is defined as the percentage of cases that
are clustered by PCR and share known epidemiologic links. The confirmed
recent transmission incidence can also be calculated by dividing
the number of epidemiologically linked clustered cases each year
by the jurisdiction’s population.
Some TB programs have used an even more sophisticated approach
to defining whether a case represents recent transmission. For each
cluster, an attempt is made to identify the likely source case,
based on which case had the earliest date of symptom onset. Because
the time of TB acquisition for source cases is undefined, the source
case is not counted as representing recent transmission. Others
have used a shortcut to address the argument that the source case
should not be counted by simply reducing the number of cases in
each cluster by one. Another modification of the calculation of
the recent transmission index is to include all cases in children
less than 5 years of age, since they obviously acquired TB within
the previous 5 years.
Epidemiologically Confirmed Genotyping Cluster Surveillance
Universal genotyping will help identify clusters that represent
recent transmission at early stages and will provide TB programs
with a tool to monitor the number of epidemiologically confirmed
clusters that occur. To be useful, a standardized and easy-to-apply
definition of an epidemiologically confirmed cluster must be developed.
Identifying Source Cases
Once a cluster is determined to represent recent transmission and
the transmission dynamics that link the various cases are clarified,
it is often possible to identify the patient or patients with infectious
TB who were the sources of transmission. Information on source cases
should be gathered and analyzed in a systematic fashion to understand
the patient characteristics that are associated with recent transmission.
Also important is to identify active clusters for which no source
case is identified, since this might lead to a renewed search for
an undetected infectious case.
Added Value of Cluster Investigations
Epidemiologically confirmed recent transmission is defined as cases
that formed a genotyping cluster and shared epidemiologic links.
The percentage of cases that represent recent transmission where
the epidemiologic links were not identified during routine contact
investigations but only later during cluster investigations represents
the added value of cluster investigations. Data from NTGSN indicate
that this added value represented 38% of all epidemiologically confirmed
recent transmission (McNabb 2004). Both known and unknown source-secondary
patient relationships represent missed opportunities for TB prevention.
Findings from contact investigations, including identification of
settings where recent transmission occurred, can be useful for improving
contact investigations. Findings from contact investigations can
also point out ways to utilize social network analyses to improve
contact tracing, screening, and treatment for latent TB infection.
Frequency of False-Positive Cultures
Because universal genotyping should have an important impact on
recognizing episodes of false-positive cultures, it will be useful
for programs to monitor their occurrence. This will allow documentation
of how well the program can identify instances of false-positive
cultures and to demonstrate the benefit of doing so in terms of
averting unnecessary treatment.