Development of a spontaneous preterm birth predictive model using a panel of serum protein biomarkers for early pregnant women: A nested case-control study

Objective: To develop a model based on first trimester maternal serum LC-MS/MS to predict spontaneous preterm birth (sPTB) < 37weeks. Methods: A cohort of 2,053 women were enrolled in a tertiary maternity hospital in China from July 1, 2018 to January 31, 2019. In total, 110 singleton pregnancies (26 cases of sPTB and 84 controls) at 11-136/7 gestational weeks were used for model development and internal validation. A total of 72 pregnancies (25 cases of sPTB and 47 controls) at 20-32 gestational weeks from an additional cohort of 2,167 women were used to evaluate the scalability of the prediction model. Maternal serum samples were collected at enrollment and analyzed by LC-MS/MS, and candidate proteins were used to develop an optimal predictive model by machine learning algorithms. Results: A novel predictive panel with four proteins, including sFlt-1, MMP-8, ceruloplasmin, and SHBG, which was the most discriminative subset, was developed. The optimal model of logistic regression had an AUC of 0.934, with additional prediction of sPTB in second and third trimester (0.868 AUC). Importantly, higher-risk subjects defined by the prediction generally gave birth earlier than lower-risk subjects. Conclusion: First trimester modeling based on maternal serum LC-MS/MS identifies pregnant women at risk of sPTB, which may provide utility in identifying women at risk at an early stage of pregnancy before clinical presentation to allow for earlier intervention. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the National Natural Science Foundation of China (61802209), the Open Fund of Tianjin Central Hospital of Gynecology Obstetrics/Tianjin Key Laboratory of Human Development and Reproductive Regulation (2020XHY03), Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-043A). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the Ethics Committee of Tianjin Central Hospital of Obstetrics and Gynecology (2020KY023, April 2, 2020). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.