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Functional principal component analysis and sparse-group LASSO to identify associations between biomarker trajectories and mortality among hospitalized SARS-CoV-2 infected individuals.
Cao, Tingyi; Reeder, Harrison T; Foulkes, Andrea S.
Afiliación
  • Cao T; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. tingyi_cao@hsph.harvard.edu.
  • Reeder HT; Biostatistics, Massachusetts General Hospital, Boston, MA, USA.
  • Foulkes AS; Department of Medicine, Harvard Medical School, Boston, MA, USA.
BMC Med Res Methodol ; 23(1): 254, 2023 10 28.
Article en En | MEDLINE | ID: mdl-37898791
BACKGROUND: A substantial body of clinical research involving individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evaluated the association between in-hospital biomarkers and severe SARS-CoV-2 outcomes, including intubation and death. However, most existing studies considered each of multiple biomarkers independently and focused analysis on baseline or peak values. METHODS: We propose a two-stage analytic strategy combining functional principal component analysis (FPCA) and sparse-group LASSO (SGL) to characterize associations between biomarkers and 30-day mortality rates. Unlike prior reports, our proposed approach leverages: 1) time-varying biomarker trajectories, 2) multiple biomarkers simultaneously, and 3) the pathophysiological grouping of these biomarkers. We apply this method to a retrospective cohort of 12, 941 patients hospitalized at Massachusetts General Hospital or Brigham and Women's Hospital and conduct simulation studies to assess performance. RESULTS: Renal, inflammatory, and cardio-thrombotic biomarkers were associated with 30-day mortality rates among hospitalized SARS-CoV-2 patients. Sex-stratified analysis revealed that hematogolical biomarkers were associated with higher mortality in men while this association was not identified in women. In simulation studies, our proposed method maintained high true positive rates and outperformed alternative approaches using baseline or peak values only with respect to false positive rates. CONCLUSIONS: The proposed two-stage approach is a robust strategy for identifying biomarkers that associate with disease severity among SARS-CoV-2-infected individuals. By leveraging information on multiple, grouped biomarkers' longitudinal trajectories, our method offers an important first step in unraveling disease etiology and defining meaningful risk strata.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Límite: Female / Humans / Male Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Límite: Female / Humans / Male Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido