Quantitative fetal fibronectin and cervical length to predict preterm birth in asymptomatic women with previous cervical surgery.

BACKGROUND: Quantitative fetal fibronectin testing has demonstrated accuracy for prediction of spontaneous preterm birth in asymptomatic women with a history of preterm birth. Predictive accuracy in women with previous cervical surgery (a potentially different risk mechanism) is not known. OBJECTIVE: We sought to compare the predictive accuracy of cervicovaginal fluid quantitative fetal fibronectin and cervical length testing in asymptomatic women with previous cervical surgery to that in women with 1 previous preterm birth. STUDY DESIGN: We conducted a prospective blinded secondary analysis of a larger observational study of cervicovaginal fluid quantitative fetal fibronectin concentration in asymptomatic women measured with a Hologic 10Q system (Hologic, Marlborough, MA). Prediction of spontaneous preterm birth (<30, <34, and <37 weeks) with cervicovaginal fluid quantitative fetal fibronectin concentration in primiparous women who had undergone at least 1 invasive cervical procedure (n = 473) was compared with prediction in women who had previous spontaneous preterm birth, preterm prelabor rupture of membranes, or late miscarriage (n = 821). Relationship with cervical length was explored. RESULTS: The rate of spontaneous preterm birth <34 weeks in the cervical surgery group was 3% compared with 9% in previous spontaneous preterm birth group. Receiver operating characteristic curves comparing quantitative fetal fibronectin for prediction at all 3 gestational end points were comparable between the cervical surgery and previous spontaneous preterm birth groups (34 weeks: area under the curve, 0.78 [95% confidence interval 0.64-0.93] vs 0.71 [95% confidence interval 0.64-0.78]; P = .39). Prediction of spontaneous preterm birth using cervical length compared with quantitative fetal fibronectin for prediction of preterm birth <34 weeks of gestation offered similar prediction (area under the curve, 0.88 [95% confidence interval 0.79-0.96] vs 0.77 [95% confidence interval 0.62-0.92], P = .12 in the cervical surgery group; and 0.77 [95% confidence interval 0.70-0.84] vs 0.74 [95% confidence interval 0.67-0.81], P = .32 in the previous spontaneous preterm birth group). CONCLUSION: Prediction of spontaneous preterm birth using cervicovaginal fluid quantitative fetal fibronectin in asymptomatic women with cervical surgery is valid, and has comparative accuracy to that in women with a history of spontaneous preterm birth

Assessment of current biomarkers and interventions to identify and treat women at risk of preterm birth

Preterm birth remains an important global problem, and an important contributor to under-5 mortality. Reducing spontaneous preterm birth rates at the global level will require the early identification of patients at risk of preterm delivery in order to allow the initiation of appropriate prophylactic management strategies. Ideally these strategies target the underlying pathophysiologic causes of preterm labor. Prevention, however, becomes problematic as the causes of preterm birth are multifactorial and vary by gestational age, ethnicity, and social context. Unfortunately, current screening and diagnostic tests are non-specific, with only moderate clinical risk prediction, relying on the detection of downstream markers of the common end-stage pathway rather than identifying upstream pathway-specific pathophysiology that would help the provider initiate targeted interventions. As a result, the available management options (including cervical cerclage and vaginal progesterone) are used empirically with, at best, ambiguous results in clinical trials. Furthermore, the available screening tests have only modest clinical risk prediction, and fail to identify most patients who will have a preterm birth. Clearly defining preterm birth phenotypes and the biologic pathways leading to preterm birth is key to providing targeted, biomolecular pathway-specific interventions, ideally initiated in early pregnancy Pathway specific biomarker discovery, together with management strategies based on early, mid-, and-late trimester specific markers is integral to this process, which must be addressed in a systematic way through rigorously planned biomarker trials

The Preterm Clinical Network (PCN) Database: a web-based systematic method of collecting data on the care of women at risk of preterm birth

Background: Despite much research effort, there is a paucity of conclusive evidence in the field of preterm birth prediction and prevention. The methods of monitoring and prevention strategies offered to women at risk vary considerably around the UK and depend on local maternity care provision. It is becoming increasingly recognised that this experience and knowledge, if captured on a larger scale, could be a utilized as a valuable source of evidence for others. The UK Preterm Clinical Network (UKPCN) was established with the aim of improving care and outcomes for women at risk of preterm birth through the sharing of a wealth of experience and knowledge, as well as the building of clinical and research collaboration. The design and development of a bespoke internet-based database was fundamental to achieving this aim. Method: Following consultation with UKPCN members and agreement on a minimal dataset, the Preterm Clinical Network (PCN) Database was constructed to collect data from women at risk of preterm birth and their children. Information Governance and research ethics committee approval was given for the storage of historical as well as prospectively collected data. Collaborating centres have instant access to their own records, while use of pooled data is governed by the PCN Database Access Committee. Applications are welcomed from UKPCN members and other established research groups. The results of investigations using the data are expected to provide insights into the effectiveness of current surveillance practices and preterm birth interventions on a national and international scale, as well as the generation of ideas for innovation and research. To date, 31 sites are registered as Data Collection Centres, four of which are outside the UK. Conclusion: This paper outlines the aims of the PCN Database along with the development process undertaken from the initial idea to live launch