Determining clinical decision thresholds for HIV-positive patients suspected of having tuberculosis

Tom Boyles, Isabella Locatelli, Nicolas Senn, Mark Ebell

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Clinical decision thresholds may aid the evaluation of diagnostic tests but have rarely been determined for tuberculosis (TB). We presented clinicians with six web-based clinical scenarios, describing patients with HIV and possible TB at various sites and with a range of clinical stability. The probability of disease was varied randomly and clinicians asked to make treatment decisions; threshold curves and therapeutic thresholds were calculated. Test and treatment thresholds were calculated using Bayes theorem and the diagnostic accuracy of Xpert MTB/RIF. We received 165 replies to our survey. Therapeutic thresholds vary depending on the clinical stability and site of suspected disease. For inpatients, it ranges from 3.4% in unstable to 79.6% in stable patients. For TB meningitis, it ranges from 0% in unstable to 51.4% in stable patients and for pulmonary TB in outpatients it ranges from 29.1% in unstable to 74.5% in the stable patients. Test and treatment thresholds vary in a similar way with test thresholds ranging from 0 in unstable patients with suspected meningitis to 8.2% for stable inpatients. Treatment thresholds vary from 0 for unstable patients with suspected meningitis to 97% for stable inpatients. Therapeutic thresholds for TB can be determined by presenting clinicians with patient scenarios with random probabilities of disease and can be used to calculate test and treatment thresholds using Bayes theorem. Thresholds are lower when patients are more clinically unstable and when the implications of inappropriately withholding therapy are more serious. These results can be used to improve use and evaluation of diagnostic tests.

Original languageEnglish (US)
Pages (from-to)132-138
Number of pages7
JournalEvidence-Based Medicine
Volume22
Issue number4
DOIs
StatePublished - Aug 2017

Keywords

  • Diagnostic Microbiology
  • Infectious Diseases
  • Tuberculosis

ASJC Scopus subject areas

  • Medicine(all)

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