Performance of the Xpert® MTB/RIF assay in an active case-finding strategy: a pilot study from Tanzania.

In this pilot study, we evaluated the Xpert® MTB/RIF assay in an active case-finding strategy, using two spot sputum samples collected within a 1-hour interval from household contacts of smear-positive TB index cases. Tuberculosis (TB) confirmed by culture served as the reference standard. Among 219 enrolled contacts, the yield of active TB was 2.3%. While the sensitivity of smear microscopy was 60% (95%CI 14.7-94.7), Xpert MTB/RIF achieved a sensitivity of 100% (95%CI 47.81-100.0). All culture-confirmed cases tested positive by Xpert MTB/RIF on the first submitted sample, suggesting that the evaluation of only one sample could be sufficient for TB diagnosis in this context.

A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools.

Efforts to stimulate technological innovation in the diagnosis of tuberculosis (TB) have resulted in the recent introduction of several novel diagnostic tools. As these products come to market, policy makers must make difficult decisions about which of the available tools to implement. This choice should depend not only on the test characteristics (e.g., sensitivity and specificity) of the tools, but also on how they will be used within the existing health care infrastructure. Accordingly, policy makers choosing between diagnostic strategies must decide: 1) What is the best combination of tools to select? 2)Who should be tested with the new tools? and 3)Will these tools complement or replace existing diagnostics? The best choice of diagnostic strategy will likely vary between settings with different epidemiology (e.g., levels of TB incidence, human immunodeficiency virus co-infection and drug-resistant TB) and structural and resource constraints (e.g., existing diagnostic pathways, human resources and laboratory capacity). We propose a joint modelling framework that includes a tuberculosis (TB) transmission component (a dynamic epidemiological model) and a health system component (an operational systems model) to support diagnostic strategy decisions. This modelling approach captures the complex feedback loops in this system: new diagnostic strategies alter the demands on and performance of health systems that impact TB transmission dynamics which, in turn, result in further changes to demands on the health system. We demonstrate the use of a simplified model to support the rational choice of a diagnostic strategy based on health systems requirements, patient outcomes and population-level TB impact.

Making innovations accessible to the poor through implementation research.

Within countries, poorer populations have greater health needs and less access to good medical care than better-off populations. This is particularly true for tuberculosis (TB), the archetypal disease of poverty. Innovations also tend to become available to better-off populations well before they become available to those who need them the most. In a new era of innovations for TB diagnosis and treatment, it is increasingly important not only to be sure that these innovations can work in terms of accuracy and efficacy, but also that they will work, especially for the poor. We argue that after an innovation or a group of innovations has been endorsed, based on demonstrated accuracy and/or efficacy, introduction into routine practice should proceed through implementation by research. Cluster-randomised pragmatic trials are suited to this approach, and permit the prospective collection of evidence needed for full impact assessment according to a previously published framework. The novel approach of linking transmission modelling with operational modelling provides a methodology for expanding and enhancing the range of evidence, and can be used alongside evidence from pragmatic implementation trials. This evidence from routine practice should then be used to ensure that innovations in TB control are used for positive action for all, and particularly the poor.

Recent advances in diagnostic technology: applications in autoimmune and infectious diseases.

Biomarkers are used ubiquitously as indicators of biological health. The development of genomic and proteomic multiplex technologies have enormously amplified biomarker discovery and application to diagnostic and therapeutic decisions in clinical practice. New technologies are now available that simultaneously identify a wide spectrum of biomarkers and save time and costs. Multiplexed assays can be coupled to other disease specific indicators (i.e., cytokines, single nucleotide polymorphisms) in order to get more powerful information. However, there is an urgent need for validation/standardization of the new assays before they are adopted into clinical diagnostics. It is worthy to note a new assay, T cell interferon gamma release (TIGRAs), which has recently been introduced in the diagnosis of latent tuberculosis infection. It seems to perform better than tuberculin skin test in patients with inflammatory rheumatic diseases. In this review, we focus on advantages and limits of novel approaches to the detection of autoantibody profiles in autoimmune diseases or pathogen signatures in microbiology.