| Sumario: | • Identifying the most influential factors associated with pregnancy incidence is crucial in HIV prevention trials. • We developed an algorithm to predict women at highest risk of pregnancy during the study follow-ups. • Four out of five risk factors in our pregnancy scoring algorithm, namely, younger age, single/not cohabiting, low number of children and higher number of sexual partners, were also identified as significant predictors of HIV infections among women who enrolled in HIV prevention trials. • Collectively, these overlapping risk factors indicate the seriousness of the problem and the potential future burden in HIV prevention trials particularly for pregnant HIV infected women and their unborn babies. • This is the first and the largest study to report age-specific probabilities of becoming pregnant during a biomedical intervention trial among South African women. 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. 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. 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). 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.
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