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Sveiven M, Gassman A, Rosenberg J, Chan M, Boniface J, O’Donoghue AJ, Laurent LC, Hall DA. A dual-binding magnetic immunoassay to predict spontaneous preterm birth. Front Bioeng Biotechnol 2023; 11:1256267. [PMID: 37790251 PMCID: PMC10542577 DOI: 10.3389/fbioe.2023.1256267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/25/2023] [Indexed: 10/05/2023] Open
Abstract
Complications posed by preterm birth (delivery before 37 weeks of pregnancy) are a leading cause of newborn morbidity and mortality. The previous discovery and validation of an algorithm that includes maternal serum protein biomarkers, sex hormone-binding globulin (SHBG), and insulin-like growth factor-binding protein 4 (IBP4), with clinical factors to predict preterm birth represents an opportunity for the development of a widely accessible point-of-care assay to guide clinical management. Toward this end, we developed SHBG and IBP4 quantification assays for maternal serum using giant magnetoresistive (GMR) sensors and a self-normalizing dual-binding magnetic immunoassay. The assays have a picomolar limit of detections (LOD) with a relatively broad dynamic range that covers the physiological level of the analytes as they change throughout gestation. Measurement of serum from pregnant donors using the GMR assays was highly concordant with those obtained using a clinical mass spectrometry (MS)-based assay for the same protein markers. The MS assay requires capitally intense equipment and highly trained operators with a few days turnaround time, whereas the GMR assays can be performed in minutes on small, inexpensive instruments with minimal personnel training and microfluidic automation. The potential for high sensitivity, accuracy, and speed of the GMR assays, along with low equipment and personnel requirements, make them good candidates for developing point-of-care tests. Rapid turnaround risk assessment for preterm birth would enable patient testing and counseling at the same clinic visit, thereby increasing the timeliness of recommended interventions.
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Affiliation(s)
- Michael Sveiven
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
| | - Andrew Gassman
- Sera Prognostics, Inc., Salt Lake City, UT, United States
| | - Joshua Rosenberg
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
| | - Matthew Chan
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
| | - Jay Boniface
- Sera Prognostics, Inc., Salt Lake City, UT, United States
| | - Anthony J. O’Donoghue
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, United States
| | - Louise C. Laurent
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, United States
| | - Drew A. Hall
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
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Couture C, Girard S. Diagnostic or Therapeutic Strategies for Pregnancy Complications. J Clin Med 2022; 11:jcm11113144. [PMID: 35683531 PMCID: PMC9181516 DOI: 10.3390/jcm11113144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 05/30/2022] [Indexed: 11/30/2022] Open
Affiliation(s)
- Camille Couture
- Ste-Justine Hospital Research Center, Department of Microbiology, Infectiology and Immunology, Universite de Montreal, Montreal, QC H3T 1C5, Canada;
| | - Sylvie Girard
- Department of Obstetrics & Gynecology, Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
- Correspondence:
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Burchard J, Saade GR, Boggess KA, Markenson GR, Iams JD, Coonrod DV, Pereira LM, Hoffman MK, Polpitiya AD, Treacy R, Fox AC, Randolph TL, Fleischer TC, Dufford MT, Garite TJ, Critchfield GC, Boniface JJ, Kearney PE. Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating. J Clin Med 2022; 11:jcm11102885. [PMID: 35629011 PMCID: PMC9146613 DOI: 10.3390/jcm11102885] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/11/2022] [Accepted: 05/18/2022] [Indexed: 02/05/2023] Open
Abstract
The clinical management of pregnancy and spontaneous preterm birth (sPTB) relies on estimates of gestational age (GA). Our objective was to evaluate the effect of GA dating uncertainty on the observed performance of a validated proteomic biomarker risk predictor, and then to test the generalizability of that effect in a broader range of GA at blood draw. In a secondary analysis of a prospective clinical trial (PAPR; NCT01371019), we compared two GA dating categories: both ultrasound and dating by last menstrual period (LMP) (all subjects) and excluding dating by LMP (excluding LMP). The risk predictor's performance was observed at the validated risk predictor threshold both in weeks 191/7-206/7 and extended to weeks 180/7-206/7. Strict blinding and independent statistical analyses were employed. The validated biomarker risk predictor showed greater observed sensitivity of 88% at 75% specificity (increases of 17% and 1%) in more reliably dated (excluding-LMP) subjects, relative to all subjects. Excluding dating by LMP significantly improved the sensitivity in weeks 191/7-206/7. In the broader blood draw window, the previously validated risk predictor threshold significantly stratified higher and lower risk of sPTB, and the risk predictor again showed significantly greater observed sensitivity in excluding-LMP subjects. These findings have implications for testing the performance of models aimed at predicting PTB.
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Affiliation(s)
- Julja Burchard
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
- Correspondence: ; Tel.: +1-801-990-0597
| | - George R. Saade
- Department of Obstetrics & Gynecology, The University of Texas Medical Branch, Galveston, TX 77555, USA;
| | - Kim A. Boggess
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina, Chapel Hill, NC 27599, USA;
| | - Glenn R. Markenson
- Maternal Fetal Medicine, Boston University School of Medicine, Boston, MA 02118, USA;
| | - Jay D. Iams
- Department of Obstetrics & Gynecology, The Ohio State University, Columbus, OH 43210, USA;
| | - Dean V. Coonrod
- Department of Obstetrics and Gynecology, Valleywise Health, Phoenix, AZ 85008, USA;
| | - Leonardo M. Pereira
- Division of Maternal-Fetal Medicine, Oregon Health & Science University, Portland, OR 97239, USA;
| | - Matthew K. Hoffman
- Department of Obstetrics & Gynecology, Christiana Care Health System, Newark, DE 19718, USA;
| | - Ashoka D. Polpitiya
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Ryan Treacy
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Angela C. Fox
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Todd L. Randolph
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Tracey C. Fleischer
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Max T. Dufford
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Thomas J. Garite
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Gregory C. Critchfield
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - J. Jay Boniface
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Paul E. Kearney
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
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Burchard J, Markenson GR, Saade GR, Laurent LC, Heyborne KD, Coonrod DV, Schoen CN, Baxter JK, Haas DM, Longo SA, Sullivan SA, Wheeler SM, Pereira LM, Boggess KA, Hawk AF, Crockett AH, Treacy R, Fox AC, Polpitiya AD, Fleischer TC, Garite TJ, Jay Boniface J, Zupancic JAF, Critchfield GC, Kearney PE. 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. J Med Econ 2022; 25:1255-1266. [PMID: 36377363 DOI: 10.1080/13696998.2022.2147771] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
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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Affiliation(s)
| | - Glenn R Markenson
- Department of Obstetrics and Gynecology, Boston University School of Medicine, Boston, MA, USA
| | - George R Saade
- Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX, USA
| | - Louise C Laurent
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, CA, USA
| | - Kent D Heyborne
- Department of Obstetrics and Gynecology, Denver Health and Hospital Authority, Denver, CO, and Department of Obstetrics and Gynecology, University of Colorado Denver, Aurora, CO, USA
| | - Dean V Coonrod
- Department of Obstetrics and Gynecology, Valleywise Health, and Department of Obstetrics and Gynecology, University of Arizona College of Medicine, Phoenix, AZ, USA
| | - Corina N Schoen
- Department of Obstetrics and Gynecology, University of Massachusetts-Baystate, Springfield, MA, USA
| | - Jason K Baxter
- Department of Obstetrics and Gynecology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - David M Haas
- Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sherri A Longo
- Department of Obstetrics and Gynecology, Ochsner Health, New Orleans, LA, USA
| | - Scott A Sullivan
- Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC, USA
| | - Sarahn M Wheeler
- Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, NC, USA
| | - Leonardo M Pereira
- Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, OR, USA
| | - Kim A Boggess
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Angela F Hawk
- Regional Obstetrical Consultants, Chattanooga, TN, USA
| | - Amy H Crockett
- Department of Obstetrics and Gynecology, University of South Carolina School of Medicine Greenville and Prisma Health-Upstate, Greenville, SC, USA
| | - Ryan Treacy
- Sera Prognostics, Inc, Salt Lake City, UT, USA
| | | | | | | | | | | | - John A F Zupancic
- Department of Pediatrics, Harvard Medical School, and Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA, USA
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