TY - JOUR
T1 - Preterm birth prediction in asymptomatic women at mid-gestation using a panel of novel protein biomarkers
T2 - the Prediction of PreTerm Labor (PPeTaL) study
AU - Leow, San Min
AU - Di Quinzio, Megan K.W.
AU - Ng, Zhen Long
AU - Grant, Claire
AU - Amitay, Tal
AU - Wei, Ying
AU - Hod, Moshe
AU - Sheehan, Penelope M.
AU - Brennecke, Shaun P.
AU - Arbel, Nir
AU - Georgiou, Harry M.
N1 - Publisher Copyright:
© 2020 The Author(s)
PY - 2020/5
Y1 - 2020/5
N2 - Background: Accurate prediction of spontaneous preterm labor/preterm birth in asymptomatic women remains an elusive clinical challenge because of the multi-etiological nature of preterm birth. Objective: The aim of this study was to develop and validate an immunoassay-based, multi-biomarker test to predict spontaneous preterm birth. Materials and Methods: This was an observational cohort study of women delivering from December 2017 to February 2019 at 2 maternity hospitals in Melbourne, Australia. Cervicovaginal fluid samples were collected from asymptomatic women at gestational week 16+0−24+0, and biomarker concentrations were quantified by enzyme-linked immunosorbent assay. Women were assigned to a training cohort (n = 136) and a validation cohort (n = 150) based on chronological delivery dates. Results: Seven candidate biomarkers representing key pathways in utero-cervical remodeling were discovered by high-throughput bioinformatic search, and their significance in both in vivo and in vitro studies was assessed. Using a combination of the biomarkers for the first 136 women allocated to the training cohort, we developed an algorithm to stratify term birth (n = 124) and spontaneous preterm birth (n = 12) samples with a sensitivity of 100% (95% confidence interval, 76−100%) and a specificity of 74% (95% confidence interval, 66−81%). The algorithm was further validated in a subsequent cohort of 150 women (n = 139 term birth and n = 11 preterm birth), achieving a sensitivity of 91% (95% confidence interval, 62−100%) and a specificity of 78% (95% confidence interval, 70−84%). Conclusion: We have identified a panel of biomarkers that yield clinically useful diagnostic values when combined in a multiplex algorithm. The early identification of asymptomatic women at risk for preterm birth would allow women to be triaged to specialist clinics for further assessment and appropriate preventive treatment.
AB - Background: Accurate prediction of spontaneous preterm labor/preterm birth in asymptomatic women remains an elusive clinical challenge because of the multi-etiological nature of preterm birth. Objective: The aim of this study was to develop and validate an immunoassay-based, multi-biomarker test to predict spontaneous preterm birth. Materials and Methods: This was an observational cohort study of women delivering from December 2017 to February 2019 at 2 maternity hospitals in Melbourne, Australia. Cervicovaginal fluid samples were collected from asymptomatic women at gestational week 16+0−24+0, and biomarker concentrations were quantified by enzyme-linked immunosorbent assay. Women were assigned to a training cohort (n = 136) and a validation cohort (n = 150) based on chronological delivery dates. Results: Seven candidate biomarkers representing key pathways in utero-cervical remodeling were discovered by high-throughput bioinformatic search, and their significance in both in vivo and in vitro studies was assessed. Using a combination of the biomarkers for the first 136 women allocated to the training cohort, we developed an algorithm to stratify term birth (n = 124) and spontaneous preterm birth (n = 12) samples with a sensitivity of 100% (95% confidence interval, 76−100%) and a specificity of 74% (95% confidence interval, 66−81%). The algorithm was further validated in a subsequent cohort of 150 women (n = 139 term birth and n = 11 preterm birth), achieving a sensitivity of 91% (95% confidence interval, 62−100%) and a specificity of 78% (95% confidence interval, 70−84%). Conclusion: We have identified a panel of biomarkers that yield clinically useful diagnostic values when combined in a multiplex algorithm. The early identification of asymptomatic women at risk for preterm birth would allow women to be triaged to specialist clinics for further assessment and appropriate preventive treatment.
KW - biomarker
KW - cervical remodeling
KW - cervicovaginal fluid
KW - predictive test
KW - pregnancy
KW - prognostic test
KW - protein biomarker
KW - spontaneous preterm birth
UR - http://www.scopus.com/inward/record.url?scp=85088783877&partnerID=8YFLogxK
U2 - 10.1016/j.ajogmf.2019.100084
DO - 10.1016/j.ajogmf.2019.100084
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C2 - 33345955
AN - SCOPUS:85088783877
SN - 2589-9333
VL - 2
JO - American journal of obstetrics & gynecology MFM
JF - American journal of obstetrics & gynecology MFM
IS - 2
M1 - 100084
ER -