2018
DOI: 10.1111/all.13470
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Longitudinal evaluation of clustering of chronic sinonasal and related symptoms using exploratory factor analysis

Abstract: Background: Sinonasal symptoms are common and can have several underlying causes. When symptoms occur in specified patterns lasting three months or more they meet criteria for chronic rhinosinusitis (CRS). Approaches to CRS symptom measurement do not specify how to measure symptoms and treat six sinonasal symptoms as generally interchangeable, suggesting that such symptoms should cluster on one or two latent factors. Methods: We used questionnaire responses to 37 questions on presence, severity, bother, and … Show more

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Cited by 11 publications
(13 citation statements)
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“…For each omics profile, the top 1,000 features with P-values in ascending order were first screened and further filtered with conditions of P < 0.01 and fold change (FC) > 1.5 or FC < 2/3. Then, to reduce the feature dimensionality of multi-omics profiles combined by single-omics, exploratory factor analysis (EFA) (Cole et al, 2018) was performed on the profile of the above detected differential features on single omics by using the psych package of R software (Lorenzo-Seva and Van Ginkel, 2016) to obtain the weight matrix between factors and original features, as well as the scoring matrix of factors. For multi-omics, including double-omics, triple-omics, and quadruple-omics, the factor scoring matrix was obtained by combining the corresponding factor scoring matrix in single-omics.…”
Section: Determining Prognosis-related Features or Mpa Model Construcmentioning
confidence: 99%
“…For each omics profile, the top 1,000 features with P-values in ascending order were first screened and further filtered with conditions of P < 0.01 and fold change (FC) > 1.5 or FC < 2/3. Then, to reduce the feature dimensionality of multi-omics profiles combined by single-omics, exploratory factor analysis (EFA) (Cole et al, 2018) was performed on the profile of the above detected differential features on single omics by using the psych package of R software (Lorenzo-Seva and Van Ginkel, 2016) to obtain the weight matrix between factors and original features, as well as the scoring matrix of factors. For multi-omics, including double-omics, triple-omics, and quadruple-omics, the factor scoring matrix was obtained by combining the corresponding factor scoring matrix in single-omics.…”
Section: Determining Prognosis-related Features or Mpa Model Construcmentioning
confidence: 99%
“…It may also be that current approaches to measuring CRS symptoms identify other diseases that are unrelated to sinus inflammation and, thus, do not align with objective evidence of disease. Alternative approaches to symptom measurement may identify symptom subgroups differentially associated with sinus inflammation, findings that would have potential relevance to targeted disease management strategies …”
Section: Discussionmentioning
confidence: 99%
“…Recently, there have been efforts to build upon this library of known phenotypes by using clustering methods to identify various phenotypic subgroups, each with its characteristic phenotype, inflammatory cytokine profile and prognosticated treatment outcome . The limitations of these studies are that these clusters are heterogeneous and tend to vary from study to study.…”
Section: Precision Medicine In Crsmentioning
confidence: 99%