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  • Prediction of patient-speci...
    Dugoff, Lorraine, MD; Cuckle, Howard S., DPhil; Hobbins, John C., MD; Malone, Fergal D., MD; Belfort, Michael A., MD, PhD; Nyberg, David A., MD; Comstock, Christine H., MD; Saade, George R., MD; Eddleman, Keith A., MD; Dar, Peer, MD; Craigo, Sabrina D., MD; Timor-Tritsch, Ilan E., MD; Carr, Steven R., MD; Wolfe, Honor M., MD; D'Alton, Mary E., MD

    American journal of obstetrics and gynecology, 09/2008, Volume: 199, Issue: 3
    Journal Article, Conference Proceeding

    Objective To develop and evaluate a method of estimating patient-specific risk for fetal loss by combining maternal characteristics with serum markers. Study Design Data were obtained on 36,014 women from the FaSTER trial. Separate likelihood ratios were estimated for significant maternal characteristics and serum markers. Patient-specific risk was calculated by multiplying the incidence of fetal loss by the likelihood ratios for each maternal characteristic and for different serum marker combinations. Results Three hundred eighteen women had fetal loss < 24 weeks (early) and 103 > 24 weeks (late). Clinical characteristics evaluated included maternal age, body mass index, race, parity, threatened abortion, previous preterm delivery, and previous early loss. Serum markers studied as possible predictors of early loss included first-trimester pregnancy-associated plasma protein A and second-trimester alpha-fetoprotein, and unconjugated estriol. A risk assessment for early loss based on all of these factors yielded a 46% detection rate, for a fixed 10% false-positive rate, 39% for 5% and 28% for 1%. The only significant marker for late loss was inhibin A. The detection rate was 27% for a fixed 10% false-positive rate and only increased slightly when clinical characteristics were added to the model. Conclusion Patient-specific risk assessment for early fetal loss using serum markers, with or without maternal characteristics, has a moderately high detection. Patient-specific risk assessment for late fetal loss has low detection rates.