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PS-SiZer map to investigate significant features of body-weight profile changes in HIV infected patients in the IeDEA Collaboration

dc.contributor.authorJaroslaw Harezlaken_US
dc.contributor.authorSamiha Sarwaten_US
dc.contributor.authorKara Wools-Kaloustianen_US
dc.contributor.authorMichael Schomakeren_US
dc.contributor.authorEric Balestreen_US
dc.contributor.authorMatthew Lawen_US
dc.contributor.authorSasisopin Kiertiburanakulen_US
dc.contributor.authorMatthew Foxen_US
dc.contributor.authorDiana Huisin‘t Velden_US
dc.contributor.authorBeverly Sue Musicken_US
dc.contributor.authorConstantin Theodore Yiannoutsosen_US
dc.contributor.otherUniversity Hospital of Ghenten_US
dc.contributor.otherKirby Instituteen_US
dc.contributor.otherIndiana University-Purdue University Indianapolisen_US
dc.contributor.otherIndiana University School of Medicineen_US
dc.contributor.otherIndiana University Bloomingtonen_US
dc.contributor.otherSchool of Public Healthen_US
dc.contributor.otherFaculty of Medicine, Ramathibodi Hospital, Mahidol Universityen_US
dc.contributor.otherInsermen_US
dc.contributor.otherUniversity of Cape Townen_US
dc.contributor.otherBayer US LLCen_US
dc.date.accessioned2020-06-02T03:58:49Z
dc.date.available2020-06-02T03:58:49Z
dc.date.issued2020-05-01en_US
dc.description.abstract© 2020 Harezlak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objectives We extend the method of Significant Zero Crossings of Derivatives (SiZer) to address within-subject correlations of repeatedly collected longitudinal biomarker data and the computational aspects of the methodology when analyzing massive biomarker databases. SiZer is a powerful visualization tool for exploring structures in curves by mapping areas where the first derivative is increasing, decreasing or does not change (plateau) thus exploring changes and normalization of biomarkers in the presence of therapy. Methods We propose a penalized spline SiZer (PS-SiZer) which can be expressed as a linear mixed model of the longitudinal biomarker process to account for irregularly collected data and within-subject correlations. Through simulations we show how sensitive PS-SiZer is in detecting existing features in longitudinal data versus existing versions of SiZer. In a real-world data analysis PS-SiZer maps are used to map areas where the first derivative of weight change after antiretroviral therapy (ART) start is significantly increasing, decreasing or does not change, thus exploring the durability of weight increase after the start of therapy. We use weight data repeatedly collected from persons living with HIV initiating ART in five regions in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) worldwide collaboration and compare the durability of weight gain between ART regimens containing and not containing the drug stavudine (d4T), which has been associated with shorter durability of weight gain. Results Through simulations we show that the PS-SiZer is more accurate in detecting relevant features in longitudinal data than existing SiZer variants such as the local linear smoother (LL) SiZer and the SiZer with smoothing splines (SS-SiZer). In the illustration we include data from 185,010 persons living with HIV who started ART with a d4T (53.1%) versus non-d4T (46.9%) containing regimen. The largest difference in durability of weight gain identified by the SiZer maps was observed in Southern Africa where weight gain in patients treated with d4T-containing regimens lasted 59.9 weeks compared to 133.8 weeks for those with nond4T-containing regimens. In the other regions, persons receiving d4T-containing regimens experienced weight gains lasting 38–62 weeks versus 55–93 weeks in those receiving nond4T-based regimens. Discussion PS-SiZer, a SiZer variant, can handle irregularly collected longitudinal data and within-subject correlations and is sensitive in detecting even subtle features in biomarker curves.en_US
dc.identifier.citationPLoS ONE. Vol.15, No.5 (2020)en_US
dc.identifier.doi10.1371/journal.pone.0220165en_US
dc.identifier.issn19326203en_US
dc.identifier.other2-s2.0-85084226215en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/56079
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084226215&origin=inwarden_US
dc.subjectAgricultural and Biological Sciencesen_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.subjectMultidisciplinaryen_US
dc.titlePS-SiZer map to investigate significant features of body-weight profile changes in HIV infected patients in the IeDEA Collaborationen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084226215&origin=inwarden_US

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