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Limitations of Traditional Preterm Birth Screening Methods

Identifying women at higher risk for preterm birth is a critical first step to addressing an early delivery’s health impacts. Until now, risk prediction tools have been limited, with only a small percentage of singleton pregnancies identified to be at risk for a spontaneous preterm birth.

pregnant lady with extreme prematurity complications
Preterm Birth Management: The Main Risk Identifiers for Preterm Birth Complications

The rate of preterm birth has not changed over the past 30 years, despite the research that has gone into it. Dr. Phelps Sandall, MD discusses preterm birth management and how, until the PreTRM Test, the main risk identifiers for preterm birth complications were cervical length and previous preterm birth. Email: Support@PreTRM.com

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Preterm Birth Management: The Main Risk Identifiers for Preterm Birth Complications

Traditional Methods Alone Fail to Detect 80% of Spontaneous Preterm Births

Until recently, clinicians have had limited resources for predicting the risk of spontaneous preterm birth. Up to half of all pregnant women who deliver prematurely have no known risk factors.1,2

Up to half of all pregnant women who deliver prematurely have no known risk factors.1,2

Cervical length alone is not an adequate tool to identify women who go on to deliver prematurely. The data behind the PreTRM® clinical validation studies (PAPR and TREETOP) highlight a real opportunity to provide a tool to clinicians to better help identify and stratify patients at increased risk of delivering prematurely who otherwise have no known risk factors.

Dr. Michael Foley, MD
Medical Advisor
Past President, Society for Maternal Fetal Medicine

Other Risk Factors for Preterm Birth

The specific causes of all spontaneous preterm births are not fully understood. However, there are several known risk factors.

Medical risk factors for preterm birth examples*

  • Prior miscarriage
  • Pregnancy with multiples
  • Family history of premature birth (sister, mother, or grandmother)
  • Short inter-pregnancy interval
  • Maternal age (17 or younger, 35 or older)
  • Prior cervical procedures (such as LEEP or cone biopsy)
  • Diabetes
  • High blood pressure
  • Pregnant through in vitro fertilization (IVF)
  • Sleep disorders (such as insomnia or sleep apnea)
  • Certain infections (such as bacterial vaginosis, chlamydia, gonorrhea)
  • Maternal weight (BMI <19, or pre-pregnancy weight <50kgs [<120lbs] )
  • Vaginal bleeding (1st and 2nd trimester, placenta previa, abruption)

*This is not a comprehensive list or a recommendation of all risk factors that clinicians should use to determine a patient’s risk for preterm birth.

Lifestyle risk factors for preterm birth examples*

  • Heavy alcohol consumption
  • Low socioeconomic status
  • Environmental pollution
  • High stress levels
  • Smoking
  • Drug use

*This is not a comprehensive list or a recommendation of all risk factors that clinicians should use to determine a patient’s risk for preterm birth.

Determine your patient’s risk of spontaneous preterm birth to improve outcomes, even if she lacks evident risk factors

    • The PreTRM Test analyzes two placentally expressed proteins combined with biometric variables to provide a highly accurate prediction of spontaneous preterm births in asymptomatic singleton pregnancies
    • The PreTRM Test has been validated in a diverse patient population, making it accurate regardless of race and ethnicity
    • Patients will receive a personalized risk score, and the higher the risk, the earlier the potential delivery

Clinical Studies

Learn more about the PAPR study

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The Science Behind the Test

Explore the science behind the two proteins assessed by the PreTRM Test.

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References

    1. Institute of Medicine Committee on Understanding Premature Birth and Assuring Healthy Outcomes. Preterm Birth: Causes, Consequences, and Prevention. Behrman RE, Butler AS, eds. Washington (DC): National Academies Press (US)
    2. Iams JD, et al. Prevention of Preterm Parturition N Engl J Med 2014;370:254-61. DOI: 10.1056/NEJMcp1103640
    3. Saade GR, et al. Development and validation of a spontaneous preterm delivery predictor in asymptomatic women. Am J Obstet Gynecol. 2016;214(5):633.e1-24.