Xpert testing - rationalise with chest X-ray or HIV pre-screening?

Implementation research to inform the use of Xpert MTB/RIF in primary health care facilities in high TB and HIV settings in resource constrained settings.

Muyoyeta M, Moyo M, Kasese N, Ndhlovu M, Milimo D, Mwanza W, Kapata N, Schaap A, Godfrey Faussett P, Ayles H. PLoS One. 2015 Jun 1;10(6):e0126376. doi: 10.1371/journal.pone.0126376. eCollection 2015.

Background: The current cost of Xpert MTB RIF (Xpert) consumables is such that algorithms are needed to select which patients to prioritise for testing with Xpert.

Objective: To evaluate two algorithms for prioritisation of Xpert in primary health care settings in a high TB and HIV burden setting.

Method: Consecutive, presumptive TB patients with a cough of any duration were offered either Xpert or Fluorescence microscopy (FM) test depending on their CXR score or HIV status. In one facility, sputa from patients with an abnormal CXR were tested with Xpert and those with a normal CXR were tested with FM ("CXR algorithm"). CXR was scored automatically using a Computer Aided Diagnosis (CAD) program. In the other facility, patients who were HIV positive were tested using Xpert and those who were HIV negative were tested with FM ("HIV algorithm").

Results: Of 9482 individuals pre-screened with CXR, Xpert detected TB in 2090/6568 (31.8%) with an abnormal CXR, and FM was AFB positive in 8/2455 (0.3%) with a normal CXR. Of 4444 pre-screened with HIV, Xpert detected TB in 508/2265 (22.4%) HIV positive and FM was AFB positive in 212/1920 (11.0%) in HIV negative individuals. The notification rate of new bacteriologically confirmed TB increased; from 366 to 620/100 000/yr and from 145 to 261/100 000/yr at the CXR and HIV algorithm sites respectively. The median time to starting TB treatment at the CXR site compared to the HIV algorithm site was: 1(IQR 1-3 days) and 3 (2-5 days) (p<0.0001) respectively.

Conclusion: Use of Xpert in a resource-limited setting at primary care level in conjunction with pre-screening tests reduced the number of Xpert tests performed. The routine use of Xpert resulted in additional cases of confirmed TB patients starting treatment. However, there was no increase in absolute numbers of patients starting TB treatment. Same day diagnosis and treatment commencement was achieved for both bacteriologically confirmed and empirically diagnosed patients where Xpert was used in conjunction with CXR.

Abstract [1]  Full-text [free] access [2]

Editor’s notes: Although many countries have begun to deploy molecular TB diagnostics, the cost of these technologies remains prohibitive for widespread use in low- and middle-income countries. This study in Zambian primary health care clinics aimed to explore whether the use of Xpert® MTB/RIF could be rationalised by pre-screening individuals with cough, either by chest X-ray (CXR) or by HIV testing. CXR screening only marginally reduced the use of Xpert® (as three-quarters of people screened had an abnormal CXR, using digital X-ray and computerised interpretation). Restricting use of Xpert® to those known to be HIV-positive reduced the number of Xpert® tests by around half. Under both algorithms, the proportion testing Xpert® positive was very high (22-32%), suggesting that too few people were being identified as needing TB investigation. Similar to other studies of Xpert® implementation, the overall number of people starting TB treatment did not increase with the introduction of Xpert®. However, the proportion of people starting TB treatment who had microbiological confirmation did increase substantially under both algorithms. Empirical TB treatment (meaning initiation of treatment without microbiological confirmation) remained common, in the X-ray algorithm particularly where a third of people with an abnormal CXR but a negative Xpert® were started on TB treatment. This study was not designed to determine how many people who genuinely had TB were missed by each algorithm. Also this paper did not include cost-effectiveness analyses. Based on this evidence, neither of these algorithms can be clearly recommended. Further evaluation of different screening and testing strategies will be important to inform the scale-up of molecular diagnostics.   

Avoid TB deaths [4]
Africa [9]
Zambia [10]
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