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Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)

PURPOSE: To investigate the role of symptom clusters in the analysis and utilisation of patient reported outcome measures (PROMs) for data modelling and clinical practice. To compare symptom clusters with scales, and to explore their value in PROMs interpretation and symptom management. METHODS: A d...

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Autores principales: Lemanska, Agnieszka, Chen, Tao, Dearnaley, David. P., Jena, Rajesh, Sydes, Matthew. R., Faithfull, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509840/
https://www.ncbi.nlm.nih.gov/pubmed/28352980
http://dx.doi.org/10.1007/s11136-017-1548-y
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author Lemanska, Agnieszka
Chen, Tao
Dearnaley, David. P.
Jena, Rajesh
Sydes, Matthew. R.
Faithfull, Sara
author_facet Lemanska, Agnieszka
Chen, Tao
Dearnaley, David. P.
Jena, Rajesh
Sydes, Matthew. R.
Faithfull, Sara
author_sort Lemanska, Agnieszka
collection PubMed
description PURPOSE: To investigate the role of symptom clusters in the analysis and utilisation of patient reported outcome measures (PROMs) for data modelling and clinical practice. To compare symptom clusters with scales, and to explore their value in PROMs interpretation and symptom management. METHODS: A dataset called RT01 (ISCRTN47772397) of 843 prostate cancer patients was used. PROMs were reported with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI). Symptom clusters were explored with hierarchical cluster analysis (HCA) and average linkage method (correlation > 0.6). The reliability of the Urinary Function Scale was evaluated with Cronbach’s Alpha. The strength of the relationship between the items was investigated with Spearman’s correlation. Predictive accuracy of the clusters was compared to the scales by receiver operating characteristic (ROC) analysis. Presence of urinary symptoms at 3 years measured with the late effects on normal tissue: subjective, objective, management tool (LENT/SOM) was an endpoint. RESULTS: Two symptom clusters were identified (urinary cluster and sexual cluster). The grouping of symptom clusters was different than UCLA-PCI Scales. Two items of the urinary function scales (“number of pads” and “urinary leak interfering with sex”) were excluded from the urinary cluster. The correlation with the other items in the scale ranged from 0.20 to 0.21 and 0.31 to 0.39, respectively. Cronbach’s Alpha showed low correlation of those items with the Urinary Function Scale (0.14–0.36 and 0.33–0.44, respectively). All urinary function scale items were subject to a ceiling effect. Clusters had better predictive accuracy, AUC = 0.70 –0.65, while scales AUC = 0.67–0.61. CONCLUSION: This study adds to the knowledge on how cluster analysis can be applied for the interpretation and utilisation of PROMs. We conclude that multiple-item scales should be evaluated and that symptom clusters provide a study-specific approach for modelling and interpretation of PROMs.
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spelling pubmed-55098402017-07-28 Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397) Lemanska, Agnieszka Chen, Tao Dearnaley, David. P. Jena, Rajesh Sydes, Matthew. R. Faithfull, Sara Qual Life Res Article PURPOSE: To investigate the role of symptom clusters in the analysis and utilisation of patient reported outcome measures (PROMs) for data modelling and clinical practice. To compare symptom clusters with scales, and to explore their value in PROMs interpretation and symptom management. METHODS: A dataset called RT01 (ISCRTN47772397) of 843 prostate cancer patients was used. PROMs were reported with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI). Symptom clusters were explored with hierarchical cluster analysis (HCA) and average linkage method (correlation > 0.6). The reliability of the Urinary Function Scale was evaluated with Cronbach’s Alpha. The strength of the relationship between the items was investigated with Spearman’s correlation. Predictive accuracy of the clusters was compared to the scales by receiver operating characteristic (ROC) analysis. Presence of urinary symptoms at 3 years measured with the late effects on normal tissue: subjective, objective, management tool (LENT/SOM) was an endpoint. RESULTS: Two symptom clusters were identified (urinary cluster and sexual cluster). The grouping of symptom clusters was different than UCLA-PCI Scales. Two items of the urinary function scales (“number of pads” and “urinary leak interfering with sex”) were excluded from the urinary cluster. The correlation with the other items in the scale ranged from 0.20 to 0.21 and 0.31 to 0.39, respectively. Cronbach’s Alpha showed low correlation of those items with the Urinary Function Scale (0.14–0.36 and 0.33–0.44, respectively). All urinary function scale items were subject to a ceiling effect. Clusters had better predictive accuracy, AUC = 0.70 –0.65, while scales AUC = 0.67–0.61. CONCLUSION: This study adds to the knowledge on how cluster analysis can be applied for the interpretation and utilisation of PROMs. We conclude that multiple-item scales should be evaluated and that symptom clusters provide a study-specific approach for modelling and interpretation of PROMs. Springer International Publishing 2017-03-28 2017 /pmc/articles/PMC5509840/ /pubmed/28352980 http://dx.doi.org/10.1007/s11136-017-1548-y Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Lemanska, Agnieszka
Chen, Tao
Dearnaley, David. P.
Jena, Rajesh
Sydes, Matthew. R.
Faithfull, Sara
Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)
title Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)
title_full Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)
title_fullStr Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)
title_full_unstemmed Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)
title_short Symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the Medical Research Council RT01 trial (ISCRTN47772397)
title_sort symptom clusters for revising scale membership in the analysis of prostate cancer patient reported outcome measures: a secondary data analysis of the medical research council rt01 trial (iscrtn47772397)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509840/
https://www.ncbi.nlm.nih.gov/pubmed/28352980
http://dx.doi.org/10.1007/s11136-017-1548-y
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