The Clinical and Public Health Impact of Automated Nucleic Acid Testing for TB in San Francisco


Location(s): United States

Parent Project: UCSF-Gladstone Center for AIDS Research (CFAR)


Standard diagnostic strategies for tuberculosis (TB) are inadequate, and result in misuse of resources in public health programs; overutilization of hospital isolation facilities; and anxiety for patients. The reason for this waste is that standard diagnostic tests for TB are either inaccurate (smear microscopy) or slow (mycobacterial culture).

Nucleic-acid testing (NAT) has great potential to improve TB suspect evaluation because it is faster, more accurate, and simpler than existing alternatives. Unfortunately, few laboratories offer these assays because they are complex and laborious. The recent automation of NAT has eliminated these practical barriers to implementation, yet clinicians remain uncertain of the practical value of NAT. The common practice of empiric treatment reduces the need for NAT for early confirmation of TB, and there is insufficient data on how imperfectly sensitive nucleic acid tests can be safely used for early exclusion of TB. If shown to be safe and accurate for ruling out TB, NAT could eliminate much of the wasted care and expenditure in TB control programs.

We propose prospective observational studies to evaluate the likely clinical and public health impact of incorporating automated NAT into new diagnostic evaluation strategies for inpatient and outpatient TB suspects. Our overall hypothesis is that automated NAT could dramatically reduce unnecessary management practices. Aim 1 will determine if using automated NAT to exclude TB could decrease unnecessary treatment and contact investigation among outpatient TB suspects. Aim 2 will determine if using automated NAT to exclude infectious TB could decrease unnecessary inpatient respiratory isolation among hospitalized TB suspects. Taking the innovative approach of evaluating NAT for excluding TB -- rather than for identifying TB -- this research will produce preliminary data both for a future R01 proposal for a randomized trial of automated NAT, and for public health programs seeking to apply automated NAT for TB suspect evaluation.