Assessing the predictive value of HIV indicator conditions in general practice: a case-control study using the THIN database

BACKGROUND: UK HIV guidelines identify 37 clinical indicator conditions for adult HIV infection that should prompt an HIV test. However, few data currently exist to show their predictive value in identifying undiagnosed HIV.

AIM: To identify symptoms and clinical diagnoses associated with HIV infection and assess their relative importance in identifying HIV cases, using data from The Health Improvement Network (THIN) general practice database.

DESIGN AND SETTING: A case-control study in primary care.

METHOD: Cases (HIV-positive patients) were matched to controls (not known to have HIV). Data from 939 cases and 2576 controls were included (n = 3515). Statistical analysis assessed the incidence of the 37 clinical conditions in cases and controls, and their predictive value in indicating HIV infection, and derived odds ratios (ORs) for each indicator condition.

RESULTS: Twelve indicator conditions were significantly associated with HIV infection; 74.2% of HIV cases (n = 697) presented with none of the HIV indicator conditions prior to diagnosis. The conditions most strongly associated with HIV infection were bacterial pneumonia (OR = 47.7; 95% confidence interval [CI] = 5.6 to 404.2) and oral candidiasis (OR = 29.4; 95% CI = 6.9 to 125.5). The signs and symptoms most associated with HIV were weight loss (OR = 13.4; 95% CI = 5.0 to 36.0), pyrexia of unknown origin (OR = 7.2; 95% CI = 2.8 to 18.7), and diarrhoea (one or two consultations).

CONCLUSION: This is the first study to quantify the predictive value of clinical diagnoses related to HIV infection in primary care. In identifying the conditions most strongly associated with HIV, this study could aid GPs in offering targeted HIV testing to those at highest risk.