Prediction of The Earliest Detection Time of Fetal DNA Concentration in Noninvasive Prenatal Testing Based on Multivariate and Logistic Regression Model

Abstract

Fetal DNA concentration (FF) is a critical indicator affecting the accuracy and stability of non-invasive prenatal testing (NIPT). An excessively low FF may lead to test failure or false negatives. To address the lack of quantitative prediction for the earliest safe testing time at which clinical thresholds (FF ≥4%) are met, this study constructed multivariate linear regression and Logistic regression models based on publicly available sample data. The models analyzed the influence of gestational age and maternal body mass index (BMI) on FF levels and the probability of meeting the threshold, and introduced a gestational age quadratic term to establish a nonlinear model. The results demonstrated that BMI was a significant negative predictor of both FF and the probability of meeting the threshold. Further, the study derived the earliest gestational age at which the probability of meeting the threshold ≥95% for different BMI stratifications and validated model stability using the Bootstrap method. This research provides a quantitative basis for individualized NIPT testing timing.