The competing risk approach for prediction of preeclampsia

The established method of the assessment of the risk for development of preeclampsia is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors, the patient is classified as high risk and in their absence as low risk. Although this approach is simple to perform, it has poor performance of the prediction of preeclampsia and does not provide patient-specific risks. This review describes a new approach that allows the estimation of patient-specific risks of delivery with preeclampsia before any specified gestational age by maternal demographic characteristics and medical history with biomarkers obtained either individually or in combination at any stage in pregnancy. In the competing risks approach, every woman has a personalized distribution of gestational age at delivery with preeclampsia; whether she experiences preeclampsia or not before a specified gestational age depends on competition between delivery before or after the development of preeclampsia. The personalized distribution comes from the application of Bayes theorem to combine a previous distribution, which is determined from maternal factors, with likelihoods from biomarkers. As new data become available, what were posterior probabilities take the role as the previous probability, and data collected at different stages are combined by repeating the application of Bayes theorem to form a new posterior at each stage, which allows for dynamic prediction of preeclampsia. The competing risk model can be used for precision medicine and risk stratification at different stages of pregnancy. In the first trimester, the model has been applied to identify a high-risk group that would benefit from preventative therapeutic interventions. In the second trimester, the model has been used to stratify the population into high-, intermediate-, and low-risk groups in need of different intensities of subsequent monitoring, thereby minimizing unexpected adverse perinatal events. The competing risks model can also be used in surveillance of women presenting to specialist clinics with signs or symptoms of hypertensive disorders; combination of maternal factors and biomarkers provide patient-specific risks for preeclampsia that lead to personalized stratification of the intensity of monitoring, with risks updated on each visit on the basis of biomarker measurements. The established method of the assessment of the risk for development of preeclampsia is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors, the patient is classified as high risk and in their absence as low risk. Although this approach is simple to perform, it has poor performance of the prediction of preeclampsia and does not provide patient-specific risks. This review describes a new approach that allows the estimation of patient-specific risks of delivery with preeclampsia before any specified gestational age by maternal demographic characteristics and medical history with biomarkers obtained either individually or in combination at any stage in pregnancy. In the competing risks approach, every woman has a personalized distribution of gestational age at delivery with preeclampsia; whether she experiences preeclampsia or not before a specified gestational age depends on competition between delivery before or after the development of preeclampsia. The personalized distribution comes from the application of Bayes theorem to combine a previous distribution, which is determined from maternal factors, with likelihoods from biomarkers. As new data become available, what were posterior probabilities take the role as the previous probability, and data collected at different stages are combined by repeating the application of Bayes theorem to form a new posterior at each stage, which allows for dynamic prediction of preeclampsia. The competing risk model can be used for precision medicine and risk stratification at different stages of pregnancy. In the first trimester, the model has been applied to identify a high-risk group that would benefit from preventative therapeutic interventions. In the second trimester, the model has been used to stratify the population into high-, intermediate-, and low-risk groups in need of different intensities of subsequent monitoring, thereby minimizing unexpected adverse perinatal events. The competing risks model can also be used in surveillance of women presenting to specialist clinics with signs or symptoms of hypertensive disorders; combination of maternal factors and biomarkers provide patient-specific risks for preeclampsia that lead to personalized stratification of the intensity of monitoring, with risks updated on each visit on the basis of biomarker measurements. How to calculate the risk of preeclampsia in women with a history of positive screeningAmerican Journal of Obstetrics & GynecologyVol. 223Issue 2PreviewWith the current demonstration of the benefits of aspirin initiated in early pregnancy to prevent the most severe and preterm forms of preeclampsia, there is a growing interest for the prediction of preterm preeclampsia in the first trimester of pregnancy.1 In the review by Wright et al,2 the authors reported that approximately 90% of women who will develop early preeclampsia could be identified using a competing risks approach in the first trimester of pregnancy, with a false-positive rate of 10%. Full-Text PDF