Statistical approaches in the studies assessing associations between human milk immune composition and allergic diseases: A scoping review

Oleg Blyuss, Ka Yan Cheung, Jessica Chen, Callum Parr, Loukia Petrou, Alina Komarova, Maria Kokina, Polina Luzan, Egor Pasko, Alina Eremeeva, Dmitrii Peshko, Vladimir I. Eliseev, Sindre Andre Pedersen, Meghan B. Azad, Kirsi M. Jarvinen, Diego G. Peroni, Valerie Verhasselt, Robert J. Boyle, John O. Warner, Melanie R. Simpson & 1 others Daniel Munblit

Research output: Contribution to journalArticle

Abstract

A growing number of studies are focusing on the associations between human milk (HM) immunological composition and allergic diseases. This scoping review aims to identify statistical methods applied in the field and highlight pitfalls and unmet needs. A comprehensive literature search in MEDLINE and Embase retrieved 13,607 unique records. Following title/abstract screening, 29 studies met the selection criteria and were included in this review. We found that definitions of colostrum and mature milk varied across the studies. A total of 17 out of 29 (59%) studies collected samples longitudinally, but only 12% of these used serial (longitudinal) analyses. Multivariable analysis was used in 45% of the studies, but statistical approaches to modelling varied largely across the studies. Types of variables included as potential confounding factors differed considerably between models. Discrimination analysis was absent from all studies and only a single study reported classification measures. Outcomes of this scoping review highlight lack of standardization, both in data collection and handling, which remains one of the main challenges in the field. Improved standardization could be obtained by a consensus group of researchers and clinicians that could recommend appropriate methods to be applied in future prospective studies, as well as already existing datasets.

Original languageEnglish
Article number2416
JournalNutrients
Volume11
Issue number10
DOIs
Publication statusPublished - 1 Oct 2019

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Human Milk
breast milk
standardization
Colostrum
selection criteria
prospective studies
colostrum
MEDLINE
Patient Selection
Milk
statistical analysis
researchers
Research Personnel
Prospective Studies
screening
milk
sampling
methodology
Datasets

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Blyuss, Oleg ; Cheung, Ka Yan ; Chen, Jessica ; Parr, Callum ; Petrou, Loukia ; Komarova, Alina ; Kokina, Maria ; Luzan, Polina ; Pasko, Egor ; Eremeeva, Alina ; Peshko, Dmitrii ; Eliseev, Vladimir I. ; Pedersen, Sindre Andre ; Azad, Meghan B. ; Jarvinen, Kirsi M. ; Peroni, Diego G. ; Verhasselt, Valerie ; Boyle, Robert J. ; Warner, John O. ; Simpson, Melanie R. ; Munblit, Daniel. / Statistical approaches in the studies assessing associations between human milk immune composition and allergic diseases : A scoping review. In: Nutrients. 2019 ; Vol. 11, No. 10.
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Blyuss, O, Cheung, KY, Chen, J, Parr, C, Petrou, L, Komarova, A, Kokina, M, Luzan, P, Pasko, E, Eremeeva, A, Peshko, D, Eliseev, VI, Pedersen, SA, Azad, MB, Jarvinen, KM, Peroni, DG, Verhasselt, V, Boyle, RJ, Warner, JO, Simpson, MR & Munblit, D 2019, 'Statistical approaches in the studies assessing associations between human milk immune composition and allergic diseases: A scoping review' Nutrients, vol. 11, no. 10, 2416. https://doi.org/10.3390/nu11102416

Statistical approaches in the studies assessing associations between human milk immune composition and allergic diseases : A scoping review. / Blyuss, Oleg; Cheung, Ka Yan; Chen, Jessica; Parr, Callum; Petrou, Loukia; Komarova, Alina; Kokina, Maria; Luzan, Polina; Pasko, Egor; Eremeeva, Alina; Peshko, Dmitrii; Eliseev, Vladimir I.; Pedersen, Sindre Andre; Azad, Meghan B.; Jarvinen, Kirsi M.; Peroni, Diego G.; Verhasselt, Valerie; Boyle, Robert J.; Warner, John O.; Simpson, Melanie R.; Munblit, Daniel.

In: Nutrients, Vol. 11, No. 10, 2416, 01.10.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Statistical approaches in the studies assessing associations between human milk immune composition and allergic diseases

T2 - A scoping review

AU - Blyuss, Oleg

AU - Cheung, Ka Yan

AU - Chen, Jessica

AU - Parr, Callum

AU - Petrou, Loukia

AU - Komarova, Alina

AU - Kokina, Maria

AU - Luzan, Polina

AU - Pasko, Egor

AU - Eremeeva, Alina

AU - Peshko, Dmitrii

AU - Eliseev, Vladimir I.

AU - Pedersen, Sindre Andre

AU - Azad, Meghan B.

AU - Jarvinen, Kirsi M.

AU - Peroni, Diego G.

AU - Verhasselt, Valerie

AU - Boyle, Robert J.

AU - Warner, John O.

AU - Simpson, Melanie R.

AU - Munblit, Daniel

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Y1 - 2019/10/1

N2 - A growing number of studies are focusing on the associations between human milk (HM) immunological composition and allergic diseases. This scoping review aims to identify statistical methods applied in the field and highlight pitfalls and unmet needs. A comprehensive literature search in MEDLINE and Embase retrieved 13,607 unique records. Following title/abstract screening, 29 studies met the selection criteria and were included in this review. We found that definitions of colostrum and mature milk varied across the studies. A total of 17 out of 29 (59%) studies collected samples longitudinally, but only 12% of these used serial (longitudinal) analyses. Multivariable analysis was used in 45% of the studies, but statistical approaches to modelling varied largely across the studies. Types of variables included as potential confounding factors differed considerably between models. Discrimination analysis was absent from all studies and only a single study reported classification measures. Outcomes of this scoping review highlight lack of standardization, both in data collection and handling, which remains one of the main challenges in the field. Improved standardization could be obtained by a consensus group of researchers and clinicians that could recommend appropriate methods to be applied in future prospective studies, as well as already existing datasets.

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KW - Breast milk

KW - Colostrum

KW - Human milk

KW - Immune composition

KW - Immune markers

KW - Longitudinal algorithms

KW - Methodology

KW - Serial analysis

KW - Statistical analysis

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