Publications

RATIONALE

The clinical impact of Xpert MTB/RIF for tuberculosis (TB) diagnosis in high HIV-prevalence settings is unknown.

OBJECTIVE

To determine the diagnostic accuracy and impact of Xpert MTB/RIF among high-risk TB suspects.

METHODS

WE PROSPECTIVELY ENROLLED CONSECUTIVE, HOSPITALIZED, UGANDAN TB SUSPECTS IN TWO PHASES: baseline phase in which Xpert MTB/RIF results were not reported to clinicians and an implementation phase in which results were reported. We determined the diagnostic accuracy of Xpert MTB/RIF in reference to culture (solid and liquid) and compared patient outcomes by study phase.

RESULTS

477 patients were included (baseline phase 287, implementation phase 190). Xpert MTB/RIF had high sensitivity (187/237, 79%, 95% CI: 73-84%) and specificity (190/199, 96%, 95% CI: 92-98%) for culture-positive TB overall, but sensitivity was lower (34/81, 42%, 95% CI: 31-54%) among smear-negative TB cases. Xpert MTB/RIF reduced median days-to-TB detection for all TB cases (1 [IQR 0-26] vs. 0 [IQR 0-1], p<0.001), and for smear-negative TB (35 [IQR 22-55] vs. 22 [IQR 0-33], p=0.001). However, median days-to-TB treatment was similar for all TB cases (1 [IQR 0-5] vs. 0 [IQR 0-2], p=0.06) and for smear-negative TB (7 [IQR 3-53] vs. 6 [IQR 1-61], p=0.78). Two-month mortality was also similar between study phases among 252 TB cases (17% vs. 14%, difference +3%, 95% CI: -21% to +27%, p=0.80), and among 87 smear-negative TB cases (28% vs. 22%, difference +6%, 95% CI: -34 to +46%, p=0.77).

CONCLUSIONS

Xpert MTB/RIF facilitated more accurate and earlier TB diagnosis, leading to a higher proportion of TB suspects with a confirmed TB diagnosis prior to hospital discharge in a high HIV/low MDR TB prevalence setting. However, our study did not detect a decrease in two-month mortality following implementation of Xpert MTB/RIF possibly because of insufficient powering, differences in empiric TB treatment rates, and disease severity between study phases.

Human studies are one of the most valuable sources of knowledge in biomedical research, but data about their design and results are currently widely dispersed in siloed systems. Federation of these data is needed to facilitate large-scale data analysis to realize the goals of evidence-based medicine. The Human Studies Database project has developed an informatics infrastructure for federated query of human studies databases, using a generalizable approach to ontology-based data access. Our approach has three main components. First, the Ontology of Clinical Research (OCRe) provides the reference semantics. Second, a data model, automatically derived from OCRe into XSD, maintains semantic synchrony of the underlying representations while facilitating data acquisition using common XML technologies. Finally, the Query Integrator issues queries distributed over the data, OCRe, and other ontologies such as SNOMED in BioPortal. We report on a demonstration of this infrastructure on data acquired from institutional systems and from ClinicalTrials.gov.

An abstraction network is an auxiliary network of nodes and links that provides a compact, high-level view of an ontology. Such a view lends support to ontology orientation, comprehension, and quality-assurance efforts. A methodology is presented for deriving a kind of abstraction network, called a partial-area taxonomy, for the Ontology of Clinical Research (OCRe). OCRe was selected as a representative of ontologies implemented using the Web Ontology Language (OWL) based on shared domains. The derivation of the partial-area taxonomy for the Entity hierarchy of OCRe is described. Utilizing the visualization of the content and structure of the hierarchy provided by the taxonomy, the Entity hierarchy is audited, and several errors and inconsistencies in OCRe's modeling of its domain are exposed. After appropriate corrections are made to OCRe, a new partial-area taxonomy is derived. The generalizability of the paradigm of the derivation methodology to various families of biomedical ontologies is discussed.