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An Empiric HIV Risk Scoring Tool to Predict HIV-1 Acquisition in African Women
Jennifer E Balkus1, Elizabeth Brown, Thesla Palanee
1*Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA; Departments of †Global Health; ‡Epidemiology; §Biostatistics University of Washington, Seattle, WA; ‖Wits Reproductive Health and HIV Institute, University of the Witswatersrand, Johannesburg, South Africa; ¶Centre for AIDS Programme of Research in South Africa, University of KwaZulu Natal, Durban, South Africa; #HIV Prevention Research Unit, South African Medical Research Council, Durban, South Africa; **Department of Obstetrics and Gynecology, University of Zimbabwe, Harare, Zimbabwe; and ††Department of Medicine, University of Washington, Seattle, WA.
Objective:
To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women.
Design:
Data were analyzed from 3 randomized trials of biomedical HIV prevention interventions among African women (VOICE, HPTN 035, and FEM-PrEP).
Methods:
We implemented standard methods for the development of clinical prediction rules to generate a risk-scoring tool to predict HIV acquisition over the course of 1 year. Performance of the score was assessed through internal and external validations.
Results:
The final risk score resulting from multivariable modeling included age, married/living with a partner, partner provides financial or material support, partner has other partners, alcohol use, detection of a curable sexually transmitted infection, and herpes simplex virus 2 serostatus. Point values for each factor ranged from 0 to 2, with a maximum possible total score of 11. Scores ≥5 were associated with HIV incidence >5 per 100 person-years and identified 91% of incident HIV infections from among only 64% of women. The area under the curve (AUC) for predictive ability of the score was 0.71 (95% confidence interval [CI]: 0.68 to 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC = 0.69; 95% CI: 0.66 to 0.73) and external validation in HPTN 035 (AUC = 0.70; 95% CI: 0.65 to 0.75) and FEM-PrEP (AUC = 0.58; 95% CI: 0.51 to 0.65).
Conclusions:
A discrete set of characteristics that can be easily assessed in clinical and research settings was predictive of HIV acquisition over 1 year. The use of a validated risk score could improve efficiency of recruitment into HIV prevention research and inform scale-up of HIV prevention strategies in women at highest risk.
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