Validated methods for identifying tuberculosis patients in health administrative databases: systematic review.

BACKGROUND: An increasing number of studies are using health administrative databases for tuberculosis (TB) research. However, there are limitations to using such databases for identifying patients with TB. OBJECTIVE: To summarise validated methods for identifying TB in health administrative databases. METHODS: We conducted a systematic literature search in two databases (Ovid Medline and Embase, January 1980-January 2016). We limited the search to diagnostic accuracy studies assessing algorithms derived from drug prescription, International Classification of Diseases (ICD) diagnostic code and/or laboratory data for identifying patients with TB in health administrative databases. RESULTS: The search identified 2413 unique citations. Of the 40 full-text articles reviewed, we included 14 in our review. Algorithms and diagnostic accuracy outcomes to identify TB varied widely across studies, with positive predictive value ranging from 1.3% to 100% and sensitivity ranging from 20% to 100%. CONCLUSIONS: Diagnostic accuracy measures of algorithms using out-patient, in-patient and/or laboratory data to identify patients with TB in health administrative databases vary widely across studies. Use solely of ICD diagnostic codes to identify TB, particularly when using out-patient records, is likely to lead to incorrect estimates of case numbers, given the current limitations of ICD systems in coding TB.

Are interferon-γ release assays useful for diagnosing active tuberculosis in a high-burden setting?

Although interferon-γ release assays (IGRAs) are intended for diagnosing latent tuberculosis (TB), we hypothesised that in a high-burden setting: 1) the magnitude of the response when using IGRAs can distinguish active TB from other diagnoses; 2) IGRAs may aid in the diagnosis of smear-negative TB; and 3) IGRAs could be useful as rule-out tests for active TB. We evaluated the accuracy of two IGRAs (QuantiFERON®-TB Gold In-tube (QFT-GIT) and T-SPOT®.TB) in 395 patients (27% HIV-infected) with suspected TB in Cape Town, South Africa. IGRA sensitivity and specificity (95% CI) were 76% (68-83%) and 42% (36-49%) for QFT-GIT and 84% (77-90%) and 47% (40-53%) for T-SPOT®.TB, respectively. Although interferon-γ responses were significantly higher in the TB versus non-TB groups (p<0.0001), varying the cut-offs did not improve discriminatory ability. In culture-negative patients, depending on whether those with clinically diagnosed TB were included or excluded from the analysis, the negative predictive value (NPV) of QFT-GIT, T-SPOT®.TB and chest radiograph in smear-negative patients varied between 85 and 89, 87 and 92, and 98% (for chest radiograph), respectively. Overall accuracy was independent of HIV status and CD4 count. In a high-burden setting, IGRAs alone do not have value as rule-in or -out tests for active TB. In smear-negative patients, chest radiography had better NPV even in HIV-infected patients.

GenoType MTBDR assays for the diagnosis of multidrug-resistant tuberculosis: a meta-analysis.

The global extensively drug-resistant tuberculosis (TB) response plan calls for implementation of rapid tests to screen patients at risk of drug-resistant TB. Currently, two line probe assays exist, the INNO-LiPA(R)Rif.TB assay (Innogenetics, Ghent, Belgium) and the GenoType MTBDR assay (Hain LifeScience GmbH, Nehren, Germany). While LiPA studies have been reviewed, the accuracy of GenoType assays has not been systematically reviewed. The present authors carried out a systematic review and used meta-analysis methods appropriate for diagnostic accuracy. After the literature searches, 14 comparisons for rifampicin and 15 comparisons for isoniazid were identified in 10 articles that used GenoType MTBDR assays. Accuracy results were summarised in forest plots and pooled using bivariate random-effects regression. The pooled sensitivity (98.1%, 95% confidence interval (CI) 95.9-99.1) and specificity (98.7%, 95% CI 97.3-99.4) estimates for rifampicin resistance were very high and consistent across all subgroups, assay versions and specimen types. The accuracy for isoniazid was variable, with lower sensitivity (84.3%, 95% CI 76.6-89.8) and more inconsistent than specificity (99.5%, 95% CI 97.5-99.9). GenoType MDTBR assays demonstrate excellent accuracy for rifampicin resistance, even when used on clinical specimens. While specificity is excellent for isoniazid, sensitivity estimates were modest and variable. Together with data from demonstration projects, the meta-analysis provides evidence for policy making and clinical practice.