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Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms.

Burke, Ó; Benton, S; Szafranski, P; von Dadelszen, P; Buhimschi, SC; Cetin, I; Chappell, L; Figueras, F; Galindo, A; Herraiz, I; et al. Burke, Ó; Benton, S; Szafranski, P; von Dadelszen, P; Buhimschi, SC; Cetin, I; Chappell, L; Figueras, F; Galindo, A; Herraiz, I; Holzman, C; Hubel, C; Knudsen, U; Kronborg, C; Laivuori, H; Lapaire, O; McElrath, T; Moertl, M; Myers, J; Ness, RB; Oliveira, L; Olson, G; Poston, L; Ris-Stalpers, C; Roberts, JM; Schalekamp-Timmermans, S; Schlembach, D; Steegers, E; Stepan, H; Tsatsaris, V; van der Post, JA; Verlohren, S; Villa, PM; Williams, D; Zeisler, H; Redman, CWG; Staff, AC; Global Pregnancy Collaboration (2016) Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms. Pregnancy Hypertension, 6 (1). pp. 53-59. ISSN 2210-7797 https://doi.org/10.1016/j.preghy.2015.12.002
SGUL Authors: von Dadelszen, Peter

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Abstract

BACKGROUND: A common challenge in medicine, exemplified in the analysis of biomarker data, is that large studies are needed for sufficient statistical power. Often, this may only be achievable by aggregating multiple cohorts. However, different studies may use disparate platforms for laboratory analysis, which can hinder merging. METHODS: Using circulating placental growth factor (PlGF), a potential biomarker for hypertensive disorders of pregnancy (HDP) such as preeclampsia, as an example, we investigated how such issues can be overcome by inter-platform standardization and merging algorithms. We studied 16,462 pregnancies from 22 study cohorts. PlGF measurements (gestational age ⩾20 weeks) analyzed on one of four platforms: R&D Systems, AlereTriage, RocheElecsys or AbbottArchitect, were available for 13,429 women. Two merging algorithms, using Z-Score and Multiple of Median transformations, were applied. RESULTS: Best reference curves (BRC), based on merged, transformed PlGF measurements in uncomplicated pregnancy across six gestational age groups, were estimated. Identification of HDP by these PlGF-BRCs was compared to that of platform-specific curves. CONCLUSIONS: We demonstrate the feasibility of merging PlGF concentrations from different analytical platforms. Overall BRC identification of HDP performed at least as well as platform-specific curves. Our method can be extended to any set of biomarkers obtained from different laboratory platforms in any field. Merged biomarker data from multiple studies will improve statistical power and enlarge our understanding of the pathophysiology and management of medical syndromes.

Item Type: Article
Additional Information: © 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. Open Access under CC BY-NC-ND Licence
Keywords: Best reference curve, Biomarker data, Individual patient data, Merging algorithms, Pooled analysis, Pre-eclampsia, Global Pregnancy Collaboration
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Pregnancy Hypertension
ISSN: 2210-7797
Language: ENG
Dates:
DateEvent
12 January 2016Published
8 December 2015Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
UNSPECIFIEDNational Institute of Child Health and Human Developmenthttp://dx.doi.org/10.13039/100000071
PubMed ID: 26955773
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/108351
Publisher's version: https://doi.org/10.1016/j.preghy.2015.12.002

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