scholarly journals Evaluating inter-study variability in phthalate and trace element analyses within the Children’s Health Exposure Analysis Resource (CHEAR) using multivariate control charts

2021 ◽  
Vol 31 (2) ◽  
pp. 318-327
Author(s):  
Matthew J. Mazzella ◽  
Dana Boyd Barr ◽  
Kurunthachalam Kannan ◽  
Chitra Amarasiriwardena ◽  
Syam S. Andra ◽  
...  

Abstract Background The Children’s Health Exposure Analysis Resource (CHEAR) program allows researchers to expand their research goals by offering the assessment of environmental exposures in their previously collected biospecimens. Samples are analyzed in one of CHEAR’s network of six laboratory hubs with the ability to assess a wide array of environmental chemicals. The ability to assess inter-study variability is important for researchers who want to combine datasets across studies and laboratories. Objective Herein we establish a process of evaluating inter-study variability for a given analytic method. Methods Common quality control (QC) pools at two concentration levels (A and B) in urine were created within CHEAR for insertion into each batch of samples tested at a rate of three samples of each pool per 100 study samples. We assessed these QC pool results for seven phthalates analyzed for five CHEAR studies by three different lab hubs utilizing multivariate control charts to identify out-of-control runs or sets of samples associated with a given QC sample. We then tested the conditions that would lead to an out-of-control run by simulating outliers in an otherwise “in-control” set of 12 trace elements in blood QC samples (NIST SRM 955c). Results When phthalates were assessed within study, we identified a single out-of-control run for two of the five studies. Combining QC results across lab hubs, all of the runs from these two studies were now in-control, while multiple runs from two other studies were pushed out-of-control. In our simulation study we found that 3–6 analytes with outlier values (5xSD) within a run would push that run out of control in 65–83% of simulations, respectively. Significance We show how acceptable bounds of variability can be established for a given analytic method by evaluating QC materials across studies using multivariate control charts.

2021 ◽  
Vol 16 (1) ◽  
pp. 122-149
Author(s):  
Renan Mitsuo Ueda ◽  
Leandro Cantorski da Rosa ◽  
Wesley Vieira da Silva ◽  
Ícaro Romolo Sousa Agostino ◽  
Adriano Mendonça Souza

Purpose – This paper aims to present a Systematic Literature Review (SLR) of studies in Brazil with applications of multivariate control charts indexed in journals on the Web of Science. Design/methodology/approach – The following steps were carried out: a detailed synthesis was performed on the general characteristics of the corpus, co-citation and collaboration networks analyzed; and a co-occurrence of terms in the text corpus was verified. A Systematic Literature Review was carried out using the protocols set out by Biolchini et al. (2007), Kitchenham (2004) and Tranfield, Denyer and Smart (2003). Papers were selected from the Web of Science database, and after applying filters, results for 29 articles were given to compose the corpus. Findings – A tendency was found for an increase in publications, along with more international research on the issue. The journal most used for publication was the Microchemical Journal. This analysis provided relevant authors for research in this area: Harold Hotelling, Douglas Montgomery, and John Frederick MacGregor. Important Brazilian researchers were highlighted who work mainly in the pharmaceutical and biodiesel industry. Originality/value – No articles were found that had carried out a Systematic Literature Review of Brazilian research on multivariate control charts. The main contributions to this manuscript related to an increase in scientific know-how in the area of multivariate and bibliometric analysis. Keywords - Multivariate Control Charts. Systematic literature review. Bibliometric analysis.


2003 ◽  
Vol 75 (20) ◽  
pp. 5567-5574 ◽  
Author(s):  
Emilio Marengo ◽  
Elisa Robotti ◽  
Maria Cristina Liparota ◽  
Maria Carla Gennaro

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