Clinical and economic evaluation of a proteomic biomarker preterm birth risk predictor: cost-effectiveness modeling of prenatal interventions applied to predicted higher-risk pregnancies within a large and diverse cohort.

OBJECTIVES: Preterm birth occurs in more than 10% of U.S. births and is the leading cause of U.S. neonatal deaths, with estimated annual costs exceeding $25 billion USD. Using real-world data, we modeled the potential clinical and economic utility of a prematurity-reduction program comprising screening in a racially and ethnically diverse population with a validated proteomic biomarker risk predictor, followed by case management with or without pharmacological treatment. METHODS: The ACCORDANT microsimulation model used individual patient data from a prespecified, randomly selected sub-cohort (N = 847) of a multicenter, observational study of U.S. subjects receiving standard obstetric care with masked risk predictor assessment (TREETOP; NCT02787213). All subjects were included in three arms across 500 simulated trials: standard of care (SoC, control); risk predictor/case management comprising increased outreach, education and specialist care (RP-CM, active); and multimodal management (risk predictor/case management with pharmacological treatment) (RP-MM, active). In the active arms, only subjects stratified as higher risk by the predictor were modeled as receiving the intervention, whereas lower-risk subjects received standard care. Higher-risk subjects' gestational ages at birth were shifted based on published efficacies, and dependent outcomes, calibrated using national datasets, were changed accordingly. Subjects otherwise retained their original TREETOP outcomes. Arms were compared using survival analysis for neonatal and maternal hospital length of stay, bootstrap intervals for neonatal cost, and Fisher's exact test for neonatal morbidity/mortality (significance, p < .05). RESULTS: The model predicted improvements for all outcomes. RP-CM decreased neonatal and maternal hospital stay by 19% (p = .029) and 8.5% (p = .001), respectively; neonatal costs' point estimate by 16% (p = .098); and moderate-to-severe neonatal morbidity/mortality by 29% (p = .025). RP-MM strengthened observed reductions and significance. Point estimates of benefit did not differ by race/ethnicity. CONCLUSIONS: Modeled evaluation of a biomarker-based test-and-treat strategy in a diverse population predicts clinically and economically meaningful improvements in neonatal and maternal outcomes.

Preterm birth, defined as delivery before 37 weeks' gestation, is the leading cause of illness and death in newborns. In the United States, more than 10% of infants are born prematurely, and this rate is substantially higher in lower-income, inner-city and Black populations. Prematurity associates with greatly increased risk of short- and long-term medical complications and can generate significant costs throughout the lives of affected children. Annual U.S. health care costs to manage short- and long-term prematurity complications are estimated to exceed $25 billion.Clinical interventions, including case management (increased patient outreach, education and specialist care), pharmacological treatment and their combination can provide benefit to pregnancies at higher risk for preterm birth. Early and sensitive risk detection, however, remains a challenge.We have developed and validated a proteomic biomarker risk predictor for early identification of pregnancies at increased risk of preterm birth. The ACCORDANT study modeled treatments with real-world patient data from a racially and ethnically diverse U.S. population to compare the benefits of risk predictor testing plus clinical intervention for higher-risk pregnancies versus no testing and standard care. Measured outcomes included neonatal and maternal length of hospital stay, associated costs and neonatal morbidity and mortality. The model projected improved outcomes and reduced costs across all subjects, including ethnic and racial minority populations, when predicted higher-risk pregnancies were treated using case management with or without pharmacological treatment. The biomarker risk predictor shows high potential to be a clinically important component of risk stratification for pregnant women, leading to tangible gains in reducing the impact of preterm birth.

Diagnosis of rupture of membranes: AmniSure, clinical assessment, and the Food and Drug Administration warning.

BACKGROUND: An accurate diagnosis of rupture of membranes is critical to the rendering of appropriate maternity care in both preterm and term patients. Immunoassays, such as the one detecting placental alpha microglobulin-1 (AmniSure) in cervicovaginal secretions, have replaced the traditional speculum-based assessment in some clinical settings; however, the Food and Drug Administration recently issued a warning regarding the potential risks of using the test in isolation. OBJECTIVE: The study aimed to report the performance of AmniSure as a first-line nurse-administered screening test for rupture of membranes in our teaching county hospital obstetrical triage unit and as part of a clinical protocol to diagnose rupture of membranes. STUDY DESIGN: We conducted a retrospective secondary analysis of 310 randomly selected term and preterm patients with concern for rupture of membranes screened with the AmniSure test. We systematically reviewed medical records to determine membrane status at the time of the AmniSure test. We calculated test characteristics of the AmniSure test used independently and in conjunction with speculum-based assessment. RESULTS: Of 302 women evaluated for retrospective determination of membrane status at 17 to 41 weeks' gestation (median, 36.6 weeks' gestation), 208 (68.9%) were intact and 94 (31.1%) were ruptured at the time of the AmniSure test using a gold standard of retrospective membrane status determined by medical record review. A total of 4 false-negative AmniSure results and 16 false-positive AmniSure results were identified. The AmniSure test used independently had a sensitivity of 95.7%, specificity of 92.3%, positive predictive value of 84.9%, and negative predictive value of 98.0%. A rupture of membranes protocol combining AmniSure and clinical assessment had a sensitivity of 98.2%, specificity of 99.5%, positive predictive value of 100.0%, and negative predictive value of 100.0%. CONCLUSION: The AmniSure has a high sensitivity as a first-line nurse-administered screening test for membrane rupture. Consistent with the Food and Drug Administration warning, the sensitivity, specificity, positive predictive value, and negative predictive value are improved when it is used as part of a clinical protocol and not in isolation. Determination of membrane status remains challenging in a small subset of patients, especially those with an equivocal speculum-based assessment; therefore, engaging women in their care and careful follow-up for identifying persistent or recurrent symptoms are required.