A joint modeling of length-biased longitudinal process and competing risks event: application to spontaneous labor

Music City Center 

Maternal mortality is of national priority. This is resulting in increased attention to labor progression, resulting in sometimes unnecessary medical intervention during spontaneous labor.
Thus, guidelines for obstetrical care are getting much closer attention. Motivated by these issues, we focus on data-driven approach for women who will deliver naturally outside of the clinical guidelines. Spontaneous labor in women is a muti-state process, with the duration of first stage of labor denoting the time to full cervical dilation of 10 centimeters and the second stage of labor denoting the time to pushing the fetus out. The first stage of labor is a length-biased data due to start of dilation not known to the woman and the second stage of labor is a competing risks event type as the woman either delivers spontaneously or through various medical interventions, like cesarean section. Due to considerable increase in the C-section rates world wide, it is of considerable interest in identifying women at risk for C-section delivery. We propose a shared parameter model, where we predict the duration of second stage of labor based on her first stage of labor. This will help identify women who are at risk for prolonged second stage of labor and at higher risk for medical intervention. The proposed method will be assessed through simulation studies and a full analysis of NICHD Consortium of Safe Labor will be presented.