560: Predictors of response to 17-alpha hydroxyprogesterone caproate (17P) for prevention of recurrent spontaneous preterm birth (SPTB)

Abstract

We hypothesized that differences in demographics, history, and pregnancy course affect response to 17P for recurrent SPTB prevention. Secondary analysis of a prospective, multi-center, longitudinal study of women with >1 prior SPTB <37 weeks gestation. Data were collected at 3 pre-specified gestational age epochs during pregnancy. All women included in this analysis received 17P during the studied pregnancy. We classified women as a 17P responder or non-responder by calculating the difference in delivery gestational age between the 17P treated pregnancy and her earliest SPTB. Responders delivered at term and/or ≥3 weeks later with 17P vs. their earliest SPTB. 11 women whose earliest SPTB was late preterm and delivered <3 weeks later but at term were considered ‘equivocal’ responders and were excluded. Data were analyzed using chi2, t-test, and logistic regression. 155 women met inclusion criteria. The 118 responders delivered later on average (37.7 weeks) than the 37 non-responders (33.5 weeks), p<0.001. Although 32% of responders (38/118) had a recurrent SPTB, they were considered responders because they delivered ≥3 weeks later compared to their earliest SPTB. Demographics (age, race/ethnicity, education, and parity) were similar between groups. Selected historical and current pregnancy factors are shown in the Table.In the regression model, each additional week gestation of the earliest prior SPTB (OR 0.68, 95% CI 0.56-0.82, p<0.001), vaginal bleeding/abruption in the current pregnancy (OR 0.24, 95% CI 0.06-0.88, p=0.031), and first-degree family history of SPTB (OR 0.37, 95% CI 0.15-0.88, p=0.024) were associated with reduced likelihood of response to 17P. Several historical and current pregnancy characteristics define women at risk for suboptimal response to 17P. These data should be prospectively studied in larger cohorts and combined with genetic and environmental data to identify women most likely to benefit from this intervention.