Xpert MTB/RIF (‘Xpert’) and urinary lateral-flow lipoarabinomannan (LF-LAM) assays offer rapid tuberculosis (TB) diagnosis. This study evaluated the cost-effectiveness of novel diagnostic algorithms utilizing combinations of Xpert and LF-LAM for the detection of active TB among people living with HIV.
Cost-effectiveness analysis using data from a comparative study of LF-LAM and Xpert, with a target population of HIV-infected individuals with signs/symptoms of TB in Uganda.
A decision-analysis model compared multiple strategies for rapid TB diagnosis:sputum smear-microscopy; sputum Xpert; smear-microscopy combined with LF-LAM; and Xpert combined with LF-LAM. Primary outcomes were the costs and DALY's averted for each algorithm. Cost-effectiveness was represented using incremental cost-effectiveness ratios (ICER).
Compared with an algorithm of Xpert testing alone, the combination of Xpert with LF-LAM was considered highly cost-effective (ICER $57/DALY-averted) at a willingness to pay threshold of Ugandan GDP per capita. Addition of urine LF-LAM testing to smear-microscopy was a less effective strategy than Xpert replacement of smear-microscopy, but was less costly and also considered highly cost-effective (ICER $33 per DALY-averted) compared with continued usage of smear-microscopy alone. Cost-effectiveness of the Xpert plus LF-LAM algorithm was most influenced by HIV/ART costs and life-expectancy of patients after TB treatment.
The addition of urinary LF-LAM to TB diagnostic algorithms for HIV-infected individuals is highly cost-effective compared with usage of either sputum smear-microscopy or Xpert alone.
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aJohns Hopkins University School of Medicine
bJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
cDepartment of Microbiology
dInfectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda.
Correspondence to Maunank Shah, MD, Johns Hopkins University, School of Medicine, 1503 East Jefferson St, Room 118, Baltimore, MD 21231, USA. Tel: +1 443 287 0401; fax: +1 410 955 0740; e-mail: email@example.com
Received 12 June, 2013
Revised 09 July, 2013
Accepted 11 July, 2013
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