A tool to predict spontaneous preterm birth, incorporating fetal fibronectin and cervical length, in symptomatic women and high-risk asymptomatic women.

Miss Katy KUHRT, BSc; Elizabeth SMOUT, MBBS; Natasha HEZELGRAVE, Mr Paul T SEED, MSc; Andrew H SHENNAN, MD

Woman’s Health Academic Centre, Kings College London


Every year 15 million babies are born preterm (<37 weeks’ gestation)1 but prediction of spontaneous preterm birth (sPTB) is poor making it difficult to target interventions appropriately.

Recently, fetal fibronectin (fFN), though to act like a ‘glue’ between the maternal and fetal membranes,2 and cervical length (CL) assessment have superseded previous risk assessment, not only in women symptomatic of preterm birth, but in asymptomatic women where prophylactic preventative therapies can be attempted.2,3

Our aim was to develop a reliable and validated tool incorporating the improved quantitative fetal fibronectin (qfFN) measurement with other relevant risk factors to predict sPTB in asymptomatic women at high risk of preterm birth (one or more of: previous sPTB or previous preterm rupture of membranes (PPROM), previous late miscarriage (16-23+6), previous cervical surgery or cervical length measuring <25 mm in the current pregnancy) and symptomatic women presenting with symptoms suggestive of preterm labour (Abdominal pain and or threatened preterm labour: >1 painful contraction every 10 minutes for at least 30 minutes).


Blinded prospective data was collected from asymptomatic women attending preterm surveillance clinic or women presenting with symptoms suggestive of preterm labour.  Separate analyses were performed for asymptomatic and symptomatic women separately but the statistical methodology was the same.

Parametric survival models, with time updated covariates for sPTB, were compared for combinations of predictors and the best selected using the Akaike and Bayesian Information Criteria.4,5  The model was developed in a training set of women and tested in a validation. Probabilities of delivery before 5 gestations (30, 34, 37 weeks’ and within 2 or 4 weeks of test) were compared to actual event rates.  Predictive statistics were calculated to compare training and validation sets.


The final model for asymptomatic women incorporated cervical length, √fFN and previous sPTB/ PPROM as predictors and qfFN and previous sPTB/PPROM were included in the model for symptomatic women.

ROC areas ranged from 0.77-0.99 and 0.77-0.88 for asymptomatic and symptomatic models respectively, which is better than previously reported6, indicating good prediction across a range of fFN thresholds. Overall sensitivity and specificity are similar to the current literature 7 but for an individual woman the risk will be more accurate using the algorithm rather than having to use summary values across a range of women. The two models have been incorporated into an algorithm which is available as a smart phone app.  This is intended for clinicians caring for women at risk of sPTB or where PTL is suspected.  It will enable them to accurately determine a women’s risk at various clinically important gestations and to tailor management decisions appropriately. 


1. Blencowe H, Cousens S, Oestergaard MZ, Chou D, Moller AB, Narwal R

Adler A, Vera Garcia C, Rohde S, Say L, Lawn JE.  National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet 2012; 379: 2162-72.

2. Genc MR, Ford CE. The clinical use of inflammatory markers during pregnancy  Curr Opin Obstet Gynecol. 2010; 22: 116-21

3. Bolt LA, Chandiramani M, de Greeff A, Seed PT, Kurtzman J, Shennan AH. The value of combined cervical length measurement and fetal fibronectin testing to predict spontaneous preterm birth in asymptomatic high risk women. J Matern Fetal Neonatal Med. 2011; 24: 928-932.

4. Akaike, H. Information Theory and the Extension of the Maximum Likelihood Principle. In Second International Symposium on Information Theory. Petrov VN, Csaki F (eds), Akailseoniai-Kiudo: Budapest, 1973; 267 -281.

5. Schwarz G. Estimating the dimension of a model. Ann Stat. 1978; 6: 461-464

6. Honest H, Bachmann LM, Gupta JK, Kleijnen J, Khan KS. Accuracy of cervicovaginal fetal fibronectin test in predicting risk of spontaneous preterm birth: systematic review. BMJ 2002; 325:301

5. Abbott DS, Radford SK, Seed PT, Tribe RM, Shennan AH. Evaluation of quantitative fetal fibronectin test for spontaneous preterm birth in symptomatic women. Am J Obstet Gynecol. 2012; 208: 122 e1-e6.


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