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Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study
AIM: To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership. METHODS: This was a 3-mo prospective observational study (n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors o...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Baishideng Publishing Group Inc
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309716/ https://www.ncbi.nlm.nih.gov/pubmed/28246587 http://dx.doi.org/10.5306/wjco.v8.i1.75 |
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author | Meghani, Salimah H Knafl, George J |
author_facet | Meghani, Salimah H Knafl, George J |
author_sort | Meghani, Salimah H |
collection | PubMed |
description | AIM: To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership. METHODS: This was a 3-mo prospective observational study (n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors or multiple myelomas, and had at least one prescription of around-the-clock pain medication for cancer or cancer-treatment-related pain. Patients were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). Patients employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). Patients were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership. RESULTS: The analyses found 4 unique clusters: Most patients made trade-offs based on the expectation of pain relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including pain relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e., pain medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)]. CONCLUSION: Most patients appear to be driven by a single salient concern in using analgesia for cancer pain. Addressing these concerns, perhaps through real time clinical assessments, may improve patients’ analgesic adherence patterns and cancer pain outcomes. |
format | Online Article Text |
id | pubmed-5309716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-53097162017-02-28 Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study Meghani, Salimah H Knafl, George J World J Clin Oncol Prospective Study AIM: To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership. METHODS: This was a 3-mo prospective observational study (n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors or multiple myelomas, and had at least one prescription of around-the-clock pain medication for cancer or cancer-treatment-related pain. Patients were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). Patients employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). Patients were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership. RESULTS: The analyses found 4 unique clusters: Most patients made trade-offs based on the expectation of pain relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including pain relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e., pain medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)]. CONCLUSION: Most patients appear to be driven by a single salient concern in using analgesia for cancer pain. Addressing these concerns, perhaps through real time clinical assessments, may improve patients’ analgesic adherence patterns and cancer pain outcomes. Baishideng Publishing Group Inc 2017-02-10 2017-02-10 /pmc/articles/PMC5309716/ /pubmed/28246587 http://dx.doi.org/10.5306/wjco.v8.i1.75 Text en ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Prospective Study Meghani, Salimah H Knafl, George J Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study |
title | Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study |
title_full | Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study |
title_fullStr | Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study |
title_full_unstemmed | Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study |
title_short | Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study |
title_sort | salient concerns in using analgesia for cancer pain among outpatients: a cluster analysis study |
topic | Prospective Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309716/ https://www.ncbi.nlm.nih.gov/pubmed/28246587 http://dx.doi.org/10.5306/wjco.v8.i1.75 |
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