Browsing by Author "Longo, Sherri A."

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    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
    (Taylor & Francis, 2022-12) Burchard, Julja; Markenson, Glenn R.; Saade, George R.; Laurent, Louise C.; Heyborne, Kent D.; Coonrod, Dean V.; Schoen, Corina N.; Baxter, Jason K.; Haas, David M.; Longo, Sherri A.; Sullivan, Scott A.; Wheeler, Sarahn M.; Pereira, Leonardo M.; Boggess, Kim A.; Hawk, Angela F.; Crockett, Amy H.; Treacy, Ryan; Fox, Angela C.; Polpitiya, Ashoka D.; Fleischer, Tracey C.; Garite, Thomas J.; Boniface, J. Jay; Zupancic, John A. F.; Critchfield, Gregory C.; Kearney, Paul E.; Obstetrics and Gynecology, School of Medicine
    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.
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    Outcomes of shared institutional review board compared with multiple individual site institutional review board models in a multisite clinical trial
    (Elsevier, 2023) Martin, Samantha L.; Allman, Phillip H.; Dugoff, Lorraine; Sibai, Baha; Lynch, Stephanie; Ferrara, Jennifer; Aagaard, Kjersti; Zornes, Christina; Wilson, Jennifer L.; Gibson, Marie; Adams, Molly; Longo, Sherri A.; Staples, Amy; Saade, George; Beche, Imene; Carter, Ebony B.; Owens, Michelle Y.; Simhan, Hyagriv; Frey, Heather A.; Khan, Shama; Palatnik, Anna; August, Phyllis; Irby, Les'Shon; Lee, Tiffany; Lee, Christine; Schum, Paula; Chan-Akeley, Rosalyn; Duhon, Catera; Rincon, Monica; Gibson, Kelly; Wiegand, Samantha; Eastham, Donna; Oparil, Suzanne; Szychowski, Jeff M.; Tita, Alan; Chronic Hypertension and Pregnancy Consortium; Obstetrics and Gynecology, School of Medicine
    Background: Institutional review boards play a crucial role in initiating clinical trials. Although many multicenter clinical trials use an individual institutional review board model, where each institution uses their local institutional review board, it is unknown if a shared (single institutional review board) model would reduce the time required to approve a standard institutional review board protocol. Objective: This study aimed to compare processing times and other processing characteristics between sites using a single institutional review board model and those using their individual site institutional review board model in a multicenter clinical trial. Study design: This was a retrospective study of sites in an open-label, multicenter randomized control trial from 2014 to 2021. Participating sites in the multicenter Chronic Hypertension and Pregnancy trial were asked to complete a survey collecting data describing their institutional review board approval process. Results: A total of 45 sites participated in the survey (7 used a shared institutional review board model and 38 used their individual institutional review board model). Most sites (86%) using the shared institutional review board model did not require a full-board institutional review board meeting before protocol approval, compared with 1 site (3%) using the individual institutional review board model (P<.001). Median total approval times (41 vs 56 days; P=.42), numbers of submission rounds (1 vs 2; P=.09), and numbers of institutional review board stipulations (1 vs 4; P=.12) were lower for the group using the shared institutional review board model than those using the individual site institutional review board model; however, these differences were not statistically significant. Conclusion: The findings supported the hypothesis that the shared institutional review board model for multicenter studies may be more efficient in terms of cumulative time and effort required to obtain approval of an institutional review board protocol than the individual institutional review board model. Given that these data have important implications for multicenter clinical trials, future research should evaluate these findings using larger or multiple multicenter trials.