Guide to the Application of Genotyping to Tuberculosis Prevention and Control
Applying Genotyping Results to Tuberculosis Control Practices
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 indicators.
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 transmission.
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.