Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study

ABSTRACT

Background: Most studies evaluate active case findings (ACF) for bacteriologically confirmed TB. Adapted diagnostic approaches are needed to identify cases with lower bacillary loads.

Objectives: To assess the likelihood of diagnosing all forms of TB, including clinically diagnosed pulmonary and extra-pulmonary TB, using different ACF algorithms in Cambodia.

Methods: Clients were stratified into ‘high-risk’ (presumptive TB plus TB contact, or history of TB, or presumptive HIV infection; n = 12,337) and ‘moderate-risk’ groups (presumptive TB; n = 28,804). Sputum samples were examined by sputum smear microscopy (SSM) or Xpert MTB/RIF (Xpert). Initially, chest X-ray using a mobile radiography unit was a follow-up test after a negative sputum examination [algorithms A (Xpert/X-ray) and B (SSM/X-ray)]. Subsequently, all clients received an X-ray [algorithms C (X-ray+Xpert) and D (Xray+SSM/Xpert)]. X-rays were interpreted on the spot.

Results: Between 25 August 2014 and 31 March 2016, 2217 (5.4%) cases with all forms of TB cases were diagnosed among 41,141 adults. The majority of TB cases (1488; 67.1%) were diagnosed using X-ray. When X-rays were taken and interpreted the same day the sputum was collected, same-day diagnosis more than doubled. Overall, the number needed to test (NNT) to diagnose one case was 18.6 (95%CI:17.9–19.2). In the high-risk group the NNT was lower [algorithm D: NNT = 17.3(15.9–18.9)] compared with the ‘moderate-risk group’ [algorithm D: NNT = 20.8(19.6–22.2)]. In the high-risk group the NNT was lower when using Xpert as an initial test [algorithm A: NNT = 12.2(10.8–13.9) or algorithm C: NNT = 11.2(9.6–13.0)] compared with Xpert as a follow-up test [algorithm D: NNT = 17.3(15.9–18.9)].

Conclusion: To diagnose all TB forms, X-ray should be part of the diagnostic algorithm. The combination of X-ray and Xpert testing for high-risk clients was the most effective ACF approach in this setting.

KEYWORDS:

• Outreach
• chest X-ray
• Xpert MTB/RIF
• sputum smear microscopy
• clinical diagnosis

Responsible Editor

Jennifer Stewart Williams, Umeå University, Sweden

Responsible Editor

Jennifer Stewart Williams, Umeå University, Sweden

Author contributions

KC, TD, LL and ST contributed to the concept and design of the study. KC and TD analysed the data and wrote the first draft of the paper. All authors (KC, TD, TEM, NL, LG, JC, AJC, LL and ST) contributed to the interpretation of data and were involved revising the manuscript critically for important intellectual content. All authors gave a final approval of the version to be published and agree to be accountable for all aspects of the work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethics and consent

The study involved retrospective analysis of routinely collected program. The database and the manuscript do not contain identifying data, such as names or addresses. The need for written consent was waived by the Institutional Review Board of the Institute of Tropical Medicine, Antwerp . The study was approved by the Institutional Review Board of the Institute of Tropical Medicine, Antwerp and the management of the Sihanouk Hospital Center of HOPE, Infectious Disease Department, Phnom Penh, Cambodia.

Paper context

Active case finding should target all forms of tuberculosis (TB), including clinically diagnosed TB. However, most studies on active case finding focus on bacteriologically confirmed TB. Our study showed that algorithms using chest X-ray and Xpert MTB/RIF are effective in diagnosing all forms of TB.

Additional information

Funding

The active case finding activities conducted between 2012 and 2013 were supported by the Stop TB Partnership’s TB REACH initiative. However, this research used routinely collected program data and received no specific grant from any funding agency in the public, commercial, or non-profit sectors.