PhIGFBP-1 to predict preterm birth in asymptomatic women: A systematic review and meta-analysis

ObjectiveTo assess the prognostic value of cervicovaginal phosphorylated insulin-like growth factor-binding protein 1 (phIGFBP-1) to predict preterm birth in asymptomatic women during the second trimester of pregnancy.Study designThis is a systematic review and meta-analysis of prognostic factor studies. We searched MEDLINE and Embase to identify cohort studies on the prognostic value of mid-trimester phIGFBP-1 on preterm birth in asymptomatic women. We included studies with singleton and twin gestations if they did not receive treatment to reduce the risk of preterm birth. Two reviewers independently screened the titles and abstracts, evaluated full-text articles, extracted the data and performed the risk of bias assessment using the QUIPS tool. The primary outcome was preterm birth < 37 weeks' gestation. We conducted random-effects meta-analyses, with subgroup analyses on populations with different preterm birth risks.ResultsWe included 17 studies with a total of 7618 participants. PhIGFBP-1 positive was associated with higher odds of preterm birth (12 studies, 7466 participants, OR 3.87, 95 %CI 1.60–9.32, I2 87 %). When stratifying by population, phIGFBP-1 positive was associated with higher odds of preterm birth in women with no prior history of preterm birth (6 studies, OR 4.43, 95 %CI 2.50–7.84) but not in women with risk factors for preterm birth (6 studies, OR 1.59, 95 %CI 0.57–4.42). Risk of bias due to confounding was high in included studies.ConclusionsWhile the prognostic value of PhIGFBP-1 in the prediction of preterm birth is a prognostic research question, it has been often treated as a diagnostic research question in the literature. PhIGFBP-1 may be a potential biomarker to predict PTB during mid-trimester in asymptomatic women, especially for women with low risk of PTB. However, the clinical value of phIGFBP-1 remains limited due to bias in confounding. Future research should use the prognostic research framework to address such questions on biomarkers to maximise the clinical implications.