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Updated: Jul 29, 2025

Diagnosing Pulmonary Tuberculosis with the Xpert MTB/RIF Test
Published on: April 9, 2012
Pooling sputum testing to diagnose tuberculosis using xpert MTB/RIF and xpert ultra: a cost-effectiveness analysis
Vibol Iem1,2, John S Bimba3, Victor S Santos4,5
1National Tuberculosis Control Center, Lao People's Democratic Republic, Vientiane, Laos. vibol.iem@lstmed.ac.uk.
Background:
The World Health Organization (WHO) recommends the diagnosis of tuberculosis (TB) using molecular tests, such as Xpert MTB/RIF (MTB/RIF) or Xpert Ultra (Ultra). These tests are expensive and resource-consuming, and cost-effective approaches are needed for greater coverage.
Methods:
We evaluated the cost-effectiveness of pooling sputum samples for TB testing by using a fixed amount of 1,000 MTB/RIF or Ultra cartridges. We used the number of people with TB detected as the indicator for cost-effectiveness. Cost-minimization analysis was conducted from the healthcare system perspective and included the costs to the healthcare system using pooled and individual testing.
Results:
There was no significant difference in the overall performance of the pooled testing using MTB/RIF or Ultra (sensitivity, 93.9% vs. 97.6%, specificity 98% vs. 97%, p-value > 0.1 for both). The mean unit cost across all studies to test one person was 34.10 international dollars for the individual testing and 21.95 international dollars for the pooled testing, resulting in a savings of 12.15 international dollars per test performed (35.6% decrease). The mean unit cost per bacteriologically confirmed TB case was 249.64 international dollars for the individual testing and 162.44 international dollars for the pooled testing (34.9% decrease). Cost-minimization analysis indicates savings are directly associated with the proportion of samples that are positive. If the TB prevalence is ≥ 30%, pooled testing is not cost-effective.
Conclusion:
Pooled sputum testing can be a cost-effective strategy for diagnosis of TB, resulting in significant resource savings. This approach could increase testing capacity and affordability in resource-limited settings and support increased testing towards achievement of WHO End TB strategy.
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