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Maternal Plasma RNA in First Trimester Nullipara for the Prediction of Spontaneous Preterm Birth ≤ 32 Weeks: Validation Study

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The first-trimester prediction of spontaneous preterm birth (sPTB) has been elusive, and current screening is heavily dependent on obstetric history. However, nullipara lack a relevant history and are at higher… Click to show full abstract

The first-trimester prediction of spontaneous preterm birth (sPTB) has been elusive, and current screening is heavily dependent on obstetric history. However, nullipara lack a relevant history and are at higher risk for spontaneous (s)PTB ≤ 32 weeks compared to multipara. No available objective first-trimester screening test has proven a fair predictor of sPTB ≤ 32 weeks. We questioned whether a panel of maternal plasma cell-free (PCF) RNAs (PSME2, NAMPT, APOA1, APOA4, and Hsa-Let-7g) previously validated at 16–20 weeks for the prediction of sPTB ≤ 32 weeks might be useful in first-trimester nullipara. Sixty (60) nulliparous women (40 with sPTB ≤ 32 weeks) who were free of comorbidities were randomly selected from the King’s College Fetal Medicine Research Institute biobank. Total PCF RNA was extracted and the expression of panel RNAs was quantitated by qRT-PCR. The analysis employed, primarily, multiple regression with the main outcome being the prediction of subsequent sPTB ≤ 32 weeks. The test performance was judged by the area under the curve (AUC) using a single threshold cut point with observed detection rates (DRs) at three fixed false positive rates (FPR). The mean gestation was 12.9 ± 0.5 weeks (range 12.0–14.1 weeks). Two RNAs were differentially expressed in women destined for sPTB ≤ 32 weeks: APOA1 (p < 0.001) and PSME2 (p = 0.05). APOA1 testing at 11–14 weeks predicted sPTB ≤ 32 weeks with fair to good accuracy. The best predictive model generated an AUC of 0.79 (95% CI 0.66–0.91) with observed DRs of 41%, 61%, and 79% for FPRs of 10%, 20%, and 30%, including crown–rump length, maternal weight, race, tobacco use, and age.

Keywords: sptb weeks; preterm birth; first trimester; spontaneous preterm; prediction spontaneous

Journal Title: Biomedicines
Year Published: 2023

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