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A multiple marker model to predict pregnancy viability when progesterone is indeterminate.

Beth J Plante¹, Jeffrey D Blume, Geralyn Lambert-Messerlian

¹Department of Obstetrics and Gynecology, Women and Infants Hospital, Brown Medical School, USA. bethplante@gmail.com

The Journal of Reproductive Medicine

|May 14, 2008

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A new multiple marker model accurately predicts pregnancy viability in symptomatic women during the first trimester. This model combines progesterone levels with other factors for improved diagnostic accuracy.

Area of Science:

Obstetrics and Gynecology
Reproductive Endocrinology
Clinical Diagnostics

Background:

Early pregnancy viability assessment is crucial for symptomatic women.
Differentiating viable from nonviable pregnancies often requires multiple visits and tests.
Accurate prediction at a single visit can improve patient management and reduce anxiety.

Purpose of the Study:

To develop and validate a predictive model for pregnancy viability.
To assess the diagnostic accuracy of single and multiple biomarkers.
To identify key predictors for differentiating viable from nonviable first-trimester pregnancies.

Main Methods:

Prospective cohort study of 256 symptomatic first-trimester women.
Collection of clinical data, serum biomarkers (including progesterone and human chorionic gonadotropin), and ultrasound findings.

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Analysis using receiver operator characteristic curves to evaluate predictor accuracy.

Main Results:

Progesterone demonstrated high accuracy in predicting viability, especially at extreme values (AUC=0.99).
A multiple marker model incorporating progesterone, hCG, ultrasound, and symptoms achieved 90% accuracy (AUC=0.90) in the 'grey zone'.
The model effectively differentiated viable from nonviable pregnancies in symptomatic women.

Conclusions:

A multiple marker model provides accurate prediction of pregnancy viability in symptomatic women.
This model can aid in timely diagnosis and management decisions during the first trimester.
Integrating multiple biomarkers enhances diagnostic performance beyond single marker assessment.