Peebles K, Palanee-Phillips T, Balkus JE, Beesham I, Makkan H, Deese J, Smit J, Heffron R, Morrison CS, Philip NM, Malahleha M, Kasaro M, Naidoo Y, Nielson T, Reddy K, Kotze P, Ahmed K, Rees H, Baeten JM, Barnabas RV; Evidence for Contraceptive Options and HIV Outcomes (ECHO) Trial Consortium.
J Acquir Immune Defic Syndr. 2020 Oct 1;85(2):156-164. doi: 10.1097/QAI.0000000000002436. PMID: 32701820.
Background: HIV-1 risk scoring tools could help target provision of prevention modalities such as pre-exposure prophylaxis. Recent research suggests that risk scores for women aged 18-45 may not predict risk well among young women aged 18-24. We evaluated the predictive performance of age-specific risk scores compared with the existing non-age-specific VOICE risk score, developed for women aged 18-45.
Methods: We conducted a secondary analysis of the Evidence for Contraceptive Options and HIV Outcomes Trial to develop and internally validate HIV-1 risk scores for women aged 18-24 and 25-35 in South Africa. Candidate predictors included baseline demographic, clinical, behavioral, and contextual characteristics readily available in clinical settings. The VOICE risk score was applied to women aged 18-35. We evaluated predictive performance of each risk score by area under the receiver operating characteristic curve (AUC).
Results: Predictive performance of all risk scores was moderate, with AUC (95% confidence interval) of 0.64 (0.60 to 0.67) among women aged 18-24, 0.68 (0.62 to 0.73) among those aged 25-35, and 0.61 (0.58 to 0.65) for the VOICE risk score applied to women aged 18-35; The AUC was similar in internal validation. Among women aged 18-24, HIV-1 incidence was high even at low risk scores, at 3.9 per 100 person-years (95% confidence interval: 3.2 to 4.7).
Conclusions: All risk scores were moderately predictive of HIV-1 acquisition, and age-specific risk scores performed only marginally better than the VOICE non-age-specific risk score. Approaches for targeted pre-exposure prophylaxis provision to women in South Africa may require more extensive data than are currently available to improve prediction.