Pooled testing of sputum with Xpert MTB/RIF and Xpert Ultra during tuberculosis active case finding campaigns in Lao People’s Democratic Republic

Abstract

IntroductionActive case finding (ACF) of individuals with tuberculosis (TB) is a key intervention to find the 30% of people missed every year. However, ACF requires screening large numbers of individuals who have a low probability of positive results, typically <5%, which makes using the recommended molecular tests expensive.MethodsWe conducted two ACF surveys (in 2020 and 2021) in high TB burden areas of Lao PDR. Participants were screened for TB symptoms and received a chest X-ray. Sputum samples of four consecutive individuals were pooled and tested with Xpert Mycobacterium tuberculosis (MTB)/rifampicin (RIF) (Xpert-MTB/RIF) (2020) or Xpert-Ultra (2021). The agreement of the individual and pooled samples was compared and the reasons for discrepant results and potential cartridge savings were assessed.ResultsEach survey included 436 participants, which were tested in 109 pools. In the Xpert-MTB/RIF survey, 25 (sensitivity 89%, 95% CI 72.8% to 96.3%) of 28 pools containing MTB-positive samples tested positive and 81 pools containing only MTB-negative samples tested negative (specificity 100%, 95% CI 95.5% to 100%). In the Xpert-Ultra survey, all 32 (sensitivity 100%, 95% CI 89.3% to 100%) pools containing MTB-positive samples tested positive and all 77 (specificity 100%, 95% CI 95.3% to 100%) containing only MTB-negative samples tested negative. Pooling with Xpert-MTB/RIF and Xpert-Ultra saved 52% and 46% (227/436 and 199/436, respectively) of cartridge costs alone.ConclusionTesting single and pooled specimens had a high level of agreement, with complete concordance when using Xpert-Ultra. Pooling samples could generate significant cartridge savings during ACF campaigns.

Implementation of large-scale pooled testing to increase rapid molecular diagnostic test coverage for tuberculosis: a retrospective evaluation

“…For the in silico analysis, we used the cycle threshold shift determined from Passing-Bablok regression; using either the difference in median cycle threshold values between pooled and individual tests or the bias from the Bland–Altman analysis would lead to similar estimates of the positive percent agreement. The positive percent agreement estimated using this approach was also similar to that reported in studies where all specimens were tested both individually and in pools on the Xpert or Ultra assays 36 , 37 , 39 .…”

“…type="uri"> https://www.chrisbilder.com/shiny/). 43 Previous studies have reported that pooled testing using the Xpert and Ultra assays would have enabled similarly high proportions of cartridge savings 36 , 37 , 39 . During testing, 4.6% of assays run had an invalid result, similar to what has been reported elsewhere for these assays, 28 which contributed to decreased testing efficiency as compared to the theoretical efficiency.…”

“…In a systematic review of studies where each specimen was tested both individually and in pools, Cuevas et al reported that the positive percent agreement for pools of four samples as compared with individual samples was 91% for the Xpert MTB/RIF assay and 98% for the Xpert MTB/RIF Ultra assay 39 . Subsequent studies have reported similarly small reductions in testing accuracy with large improvements in testing efficiency and significant cartridge and cost savings when using these assays for pooled testing for TB detection 36 , 37 , 40 . However, despite these results that highlight the good potential value of pooled testing to improve the detection of TB, pooled testing has not yet been widely adopted to increase molecular testing coverage for routine TB diagnosis.…”

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high burden countries

“…[31] The difference between the total actual number of individual tests performed and the theoretical number of tests per person when employing the pooling strategy represented the number of tests saved. For the primary analysis, we assumed pool size of four based on prior studies and that both individual and pooled testing were 100% sensitive and speci c. [32,33] We then modeled four ordinal screening and testing approaches with increasing complexity to estimate incremental savings compared to the previous approach (Fig. 1):…”

Dorfman pooling enhances SARS-CoV-2 large-scale community testing efficiency

“…Subsequently, pooled testing has been used successfully to screen large populations for infectious diseases. Pooled testing has been utilized in the laboratory testing of HIV, tuberculosis, hepatitis B and C, as well as the screening of blood donations to the American Red Cross [7][8][9]. Its utility has been demonstrated as a way to analyze large numbers of samples with greater efficiency than individual testing allows.…”