Contraceptives and sexual behaviours in predicting pregnancy rates in HIV prevention trials in South Africa: Past, present and future implications.

Objective: Despite all efforts, high pregnancy rates are often reported in HIV biomedical intervention trials conducted in African countries. We therefore aimed to develop a pregnancy risk scoring algorithm for targeted recruitment and screening strategies among a cohort of women in South Africa.
Methods: The study population was ~ 10,000 women who enrolled in one of the six biomedical intervention trials conducted in KwaZulu Natal, South Africa. Cox regression models were used to create a pregnancy risk scoring algorithm which was internally validated using standard statistical measures.
Results: Five factors were identified as significant predictors of pregnancy incidence:<25 years old, not using injectable contraceptives, parity (<3), being single/not cohabiting and having ≥ 2 sexual partners in the past three months. Women with total scores of 21-24, 25-35 and 36+ were classified as being at "moderate", "high", "severe" risk of pregnancy. Sensitivity of the development and validation models were reasonably high (sensitivity 76% and 74% respectively).
Conclusion: Our risk scoring algorithm can identify and alert researchers to women who need additional non-routine pregnancy assessment and counselling, with statistically acceptable accuracy and robustness.
(Copyright © 2020 Elsevier B.V. All rights reserved.)