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

Global Pregnancy Collaboration

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    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, Alere®Triage, Roche®Elecsys or Abbott®Architect, 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.

    Original languageEnglish (US)
    Pages (from-to)53-59
    Number of pages7
    JournalPregnancy Hypertension
    Volume6
    Issue number1
    DOIs
    StatePublished - Jan 1 2016

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    Intercellular Signaling Peptides and Proteins
    Biomarkers
    Pregnancy
    Gestational Age
    Pre-Eclampsia
    Cohort Studies
    Age Groups
    Medicine

    Keywords

    • Abbreviations PlGF placental growth factor
    • BRC best reference curve
    • CI confidence interval
    • GA gestational age
    • HDP hypertensive disorders of pregnancy
    • IPD individual patient data
    • MoM Multiple of the Median

    ASJC Scopus subject areas

    • Obstetrics and Gynecology
    • Internal Medicine

    Cite this

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

    In: Pregnancy Hypertension, Vol. 6, No. 1, 01.01.2016, p. 53-59.

    Research output: Contribution to journalArticle

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    title = "Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms",
    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{\circledR} Systems, Alere{\circledR}Triage, Roche{\circledR}Elecsys or Abbott{\circledR}Architect, 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.",
    keywords = "Abbreviations PlGF placental growth factor, BRC best reference curve, CI confidence interval, GA gestational age, HDP hypertensive disorders of pregnancy, IPD individual patient data, MoM Multiple of the Median",
    author = "{Global Pregnancy Collaboration} and {\'O}rlaith Burke and Samantha Benton and Pawel Szafranski and {Von Dadelszen}, Peter and Buhimschi, {S. Catalin} and Irene Cetin and Lucy Chappell and Francesc Figueras and Alberto Galindo and Ignacio Herraiz and Claudia Holzman and Carl Hubel and Ulla Knudsen and Camilla Kronborg and Hannele Laivuori and Olav Lapaire and Thomas McElrath and Manfred Moertl and Jenny Myers and Ness, {Roberta B.} and Leandro Oliveira and Gayle Olson and Lucilla Poston and Carrie Ris-Stalpers and Roberts, {James M.} and Sarah Schalekamp-Timmermans and Dietmar Schlembach and Eric Steegers and Holger Stepan and Vassilis Tsatsaris and {Van Der Post}, {Joris A.} and Stefan Verlohren and Villa, {Pia M.} and David Williams and Harald Zeisler and Redman, {Christopher W G} and Staff, {Anne Cathrine}",
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    T1 - Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms

    AU - Global Pregnancy Collaboration

    AU - Burke, Órlaith

    AU - Benton, Samantha

    AU - Szafranski, Pawel

    AU - Von Dadelszen, Peter

    AU - Buhimschi, S. Catalin

    AU - Cetin, Irene

    AU - Chappell, Lucy

    AU - Figueras, Francesc

    AU - Galindo, Alberto

    AU - Herraiz, Ignacio

    AU - Holzman, Claudia

    AU - Hubel, Carl

    AU - Knudsen, Ulla

    AU - Kronborg, Camilla

    AU - Laivuori, Hannele

    AU - Lapaire, Olav

    AU - McElrath, Thomas

    AU - Moertl, Manfred

    AU - Myers, Jenny

    AU - Ness, Roberta B.

    AU - Oliveira, Leandro

    AU - Olson, Gayle

    AU - Poston, Lucilla

    AU - Ris-Stalpers, Carrie

    AU - Roberts, James M.

    AU - Schalekamp-Timmermans, Sarah

    AU - Schlembach, Dietmar

    AU - Steegers, Eric

    AU - Stepan, Holger

    AU - Tsatsaris, Vassilis

    AU - Van Der Post, Joris A.

    AU - Verlohren, Stefan

    AU - Villa, Pia M.

    AU - Williams, David

    AU - Zeisler, Harald

    AU - Redman, Christopher W G

    AU - Staff, Anne Cathrine

    PY - 2016/1/1

    Y1 - 2016/1/1

    N2 - 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, Alere®Triage, Roche®Elecsys or Abbott®Architect, 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.

    AB - 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, Alere®Triage, Roche®Elecsys or Abbott®Architect, 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.

    KW - Abbreviations PlGF placental growth factor

    KW - BRC best reference curve

    KW - CI confidence interval

    KW - GA gestational age

    KW - HDP hypertensive disorders of pregnancy

    KW - IPD individual patient data

    KW - MoM Multiple of the Median

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    U2 - 10.1016/j.preghy.2015.12.002

    DO - 10.1016/j.preghy.2015.12.002

    M3 - Article

    C2 - 26955773

    AN - SCOPUS:84954271782

    VL - 6

    SP - 53

    EP - 59

    JO - Pregnancy Hypertension

    JF - Pregnancy Hypertension

    SN - 2210-7789

    IS - 1

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