A systematic review of commercial serological antibody detection tests for the diagnosis of extrapulmonary tuberculosis
- Karen R Steingart (karenst{at}u.washington.edu)
- Megan Henry (meganhenry80{at}gmail.com)
- Andrew Ramsay (ramsaya{at}who.int)
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), Switzerland
- Jane Cunningham (cunninghamj{at}who.int)
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), Switzerland
Abstract
Conventional diagnostic tests for tuberculosis have several limitations and are often unhelpful in establishing the diagnosis of extrapulmonary tuberculosis. Although commercial serological antibody-based tests are available, their utility in the diagnosis of extrapulmonary tuberculosis is unknown. We conducted a systematic review to assess the accuracy of commercial serological antibody detection tests for the diagnosis of extrapulmonary tuberculosis. In a comprehensive search, we identified 21 studies that reported data on sensitivity and specificity for extrapulmonary tuberculosis. These studies evaluated seven different commercial tests, with Anda-TB IgG accounting for 48% of the studies. Results of the review demonstrated that (1) all commercial tests provided highly variable estimates of sensitivity (range, 0.00-1.00) and specificity (range, 0.59-1.00) for all extrapulmonary sites combined; (2) the Anda-TB IgG kit showed highly variable sensitivity (range, 0.26-1.00) and specificity (range, 0.59-1.00) for all extrapulmonary sites combined; (3) for all tests combined, sensitivity estimates for both lymph node tuberculosis (range, 0.23-1.00) and pleural tuberculosis (range, 0.26-0.59) were poor and inconsistent; and (4) there were no data to determine accuracy of the tests in children or in patients with HIV infection, the two groups for which the test would be most useful. At the current time, commercial antibody detection tests for extrapulmonary tuberculosis have no role in clinical care or case detection.









