Cancer sleep symptom‐related phenotypic clustering differs across three cancer specific patient cohorts

Summary Specific sleep disorders have been linked to disease progression in different cancers. We hypothesised sleep symptom clusters would differ between cancer types. The aim of this study was to compare sleep symptom clusters in post‐treatment melanoma, breast and endometrial cancer patients. Dat...

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Veröffentlicht in:Journal of sleep research 2022-10, Vol.31 (5), p.e13588-n/a
Hauptverfasser: Kairaitis, Kristina, Madut, Ayey S., Subramanian, Harini, Trivedi, Ritu, Man, Hong, Mather, Marius, Brand, Alison, Elder, Elisabeth, Howle, Julie, Mann, Graham J, Amis, Terence C., De Fazio, Anna
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container_issue 5
container_start_page e13588
container_title Journal of sleep research
container_volume 31
creator Kairaitis, Kristina
Madut, Ayey S.
Subramanian, Harini
Trivedi, Ritu
Man, Hong
Mather, Marius
Brand, Alison
Elder, Elisabeth
Howle, Julie
Mann, Graham J
Amis, Terence C.
De Fazio, Anna
description Summary Specific sleep disorders have been linked to disease progression in different cancers. We hypothesised sleep symptom clusters would differ between cancer types. The aim of this study was to compare sleep symptom clusters in post‐treatment melanoma, breast and endometrial cancer patients. Data were collected from 124 breast cancer patients (1 male, 60 ± 15 years, 28.1 ± 6.6 kg/m2), 82 endometrial cancer patients (64.0 ± 12.5 years, 33.5 ± 10.4 kg/m2) and 112 melanoma patients (59 male, 65.0 ± 18.0 years, 29.1 ± 6.6 kg/m2). All patients completed validated questionnaires to assess sleep symptoms, including the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Functional Outcomes of Sleep Questionnaire‐10 (FOSQ‐10). Snoring, tiredness, observed apneas, age, BMI, and gender data were also collected. Binary values (PSQI, ISI, FOSQ), or continuous variables for sleepiness (ESS) and perceived sleep quality (PSQI), were created and sleep symptom clusters were identified and compared across cancer cohorts. Four distinct sleep symptom clusters were identified: minimally symptomatic (n = 152, 47.7%); insomnia‐predominant (n = 87, 24.9%); very sleepy with upper airway symptoms (n = 51, 16.3%), and severely symptomatic with severe dysfunction (n = 34, 11.1%). Breast cancer patients were significantly more likely to be in the insomnia predominant or severely symptomatic with severe dysfunction clusters, whereas melanoma patients were more likely to be minimally symptomatic or sleepy with upper airway symptoms (p 
doi_str_mv 10.1111/jsr.13588
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We hypothesised sleep symptom clusters would differ between cancer types. The aim of this study was to compare sleep symptom clusters in post‐treatment melanoma, breast and endometrial cancer patients. Data were collected from 124 breast cancer patients (1 male, 60 ± 15 years, 28.1 ± 6.6 kg/m2), 82 endometrial cancer patients (64.0 ± 12.5 years, 33.5 ± 10.4 kg/m2) and 112 melanoma patients (59 male, 65.0 ± 18.0 years, 29.1 ± 6.6 kg/m2). All patients completed validated questionnaires to assess sleep symptoms, including the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Functional Outcomes of Sleep Questionnaire‐10 (FOSQ‐10). Snoring, tiredness, observed apneas, age, BMI, and gender data were also collected. Binary values (PSQI, ISI, FOSQ), or continuous variables for sleepiness (ESS) and perceived sleep quality (PSQI), were created and sleep symptom clusters were identified and compared across cancer cohorts. Four distinct sleep symptom clusters were identified: minimally symptomatic (n = 152, 47.7%); insomnia‐predominant (n = 87, 24.9%); very sleepy with upper airway symptoms (n = 51, 16.3%), and severely symptomatic with severe dysfunction (n = 34, 11.1%). Breast cancer patients were significantly more likely to be in the insomnia predominant or severely symptomatic with severe dysfunction clusters, whereas melanoma patients were more likely to be minimally symptomatic or sleepy with upper airway symptoms (p &lt;0.0001). Endometrial cancer patients were equally distributed across symptom clusters. Sleep symptom clusters vary across cancer patients. A more personalised approach to the management of sleep‐related symptoms in these patients may improve the long term quality of life and survival.</description><identifier>ISSN: 0962-1105</identifier><identifier>ISSN: 1365-2869</identifier><identifier>EISSN: 1365-2869</identifier><identifier>DOI: 10.1111/jsr.13588</identifier><identifier>PMID: 35470503</identifier><language>eng</language><publisher>England: John Wiley and Sons Inc</publisher><subject>breast cancer ; Breast Neoplasms ; Cluster Analysis ; endometrial cancer ; Endometrial Neoplasms ; Female ; Humans ; Male ; melanoma ; Melanoma - complications ; Miscellaneous ; Quality of Life ; Sleep ; Sleep Initiation and Maintenance Disorders ; sleep symptom clusters ; Sleepiness ; Surveys and Questionnaires ; Syndrome</subject><ispartof>Journal of sleep research, 2022-10, Vol.31 (5), p.e13588-n/a</ispartof><rights>2022 The Authors. published by John Wiley &amp; Sons Ltd on behalf of European Sleep Research Society.</rights><rights>2022 The Authors. Journal of Sleep Research published by John Wiley &amp; Sons Ltd on behalf of European Sleep Research Society.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4158-4b4df3839265031f2b946a7772684a280eb88912b1388d72c9f2f7e32f5814ac3</citedby><cites>FETCH-LOGICAL-c4158-4b4df3839265031f2b946a7772684a280eb88912b1388d72c9f2f7e32f5814ac3</cites><orcidid>0000-0002-8808-3183</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjsr.13588$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjsr.13588$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35470503$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kairaitis, Kristina</creatorcontrib><creatorcontrib>Madut, Ayey S.</creatorcontrib><creatorcontrib>Subramanian, Harini</creatorcontrib><creatorcontrib>Trivedi, Ritu</creatorcontrib><creatorcontrib>Man, Hong</creatorcontrib><creatorcontrib>Mather, Marius</creatorcontrib><creatorcontrib>Brand, Alison</creatorcontrib><creatorcontrib>Elder, Elisabeth</creatorcontrib><creatorcontrib>Howle, Julie</creatorcontrib><creatorcontrib>Mann, Graham J</creatorcontrib><creatorcontrib>Amis, Terence C.</creatorcontrib><creatorcontrib>De Fazio, Anna</creatorcontrib><title>Cancer sleep symptom‐related phenotypic clustering differs across three cancer specific patient cohorts</title><title>Journal of sleep research</title><addtitle>J Sleep Res</addtitle><description>Summary Specific sleep disorders have been linked to disease progression in different cancers. We hypothesised sleep symptom clusters would differ between cancer types. The aim of this study was to compare sleep symptom clusters in post‐treatment melanoma, breast and endometrial cancer patients. Data were collected from 124 breast cancer patients (1 male, 60 ± 15 years, 28.1 ± 6.6 kg/m2), 82 endometrial cancer patients (64.0 ± 12.5 years, 33.5 ± 10.4 kg/m2) and 112 melanoma patients (59 male, 65.0 ± 18.0 years, 29.1 ± 6.6 kg/m2). All patients completed validated questionnaires to assess sleep symptoms, including the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Functional Outcomes of Sleep Questionnaire‐10 (FOSQ‐10). Snoring, tiredness, observed apneas, age, BMI, and gender data were also collected. Binary values (PSQI, ISI, FOSQ), or continuous variables for sleepiness (ESS) and perceived sleep quality (PSQI), were created and sleep symptom clusters were identified and compared across cancer cohorts. Four distinct sleep symptom clusters were identified: minimally symptomatic (n = 152, 47.7%); insomnia‐predominant (n = 87, 24.9%); very sleepy with upper airway symptoms (n = 51, 16.3%), and severely symptomatic with severe dysfunction (n = 34, 11.1%). Breast cancer patients were significantly more likely to be in the insomnia predominant or severely symptomatic with severe dysfunction clusters, whereas melanoma patients were more likely to be minimally symptomatic or sleepy with upper airway symptoms (p &lt;0.0001). Endometrial cancer patients were equally distributed across symptom clusters. Sleep symptom clusters vary across cancer patients. A more personalised approach to the management of sleep‐related symptoms in these patients may improve the long term quality of life and survival.</description><subject>breast cancer</subject><subject>Breast Neoplasms</subject><subject>Cluster Analysis</subject><subject>endometrial cancer</subject><subject>Endometrial Neoplasms</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>melanoma</subject><subject>Melanoma - complications</subject><subject>Miscellaneous</subject><subject>Quality of Life</subject><subject>Sleep</subject><subject>Sleep Initiation and Maintenance Disorders</subject><subject>sleep symptom clusters</subject><subject>Sleepiness</subject><subject>Surveys and Questionnaires</subject><subject>Syndrome</subject><issn>0962-1105</issn><issn>1365-2869</issn><issn>1365-2869</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNp1kctO3DAUhi3UCqZTFrxA5WW7CPgSJ_YGCY16FVKlXtaW4xwzRkmc2h7Q7PoIPCNPUpeZIljUm7Pwp-_8Oj9CJ5Sc0vLOrlM8pVxIeYAWlDeiYrJRL9CCqIZVlBJxhF6ldE0IbQVXh-iIi7olgvAF8iszWYg4DQAzTttxzmG8_30XYTAZejyvYQp5O3uL7bBJGaKfrnDvnYOYsLExpITzOgJguzfNYL0r_GyyhyljG9Yh5vQavXRmSHC8n0v088P7H6tP1eXXj59XF5eVramQVd3VveOSK9aUgNSxTtWNaduWNbI2TBLopFSUdZRL2bfMKsdcC5w5IWltLF-i85133nQj9LZEiGbQc_SjiVsdjNfPfya_1lfhRqtWSsZJEbzdC2L4tYGU9eiThWEwE4RN0iWYEA0Vqinoux36cIcI7nENJfpvNbpUox-qKeybp7keyX9dFOBsB9z6Abb_N-kv37_tlH8AJm-cBw</recordid><startdate>202210</startdate><enddate>202210</enddate><creator>Kairaitis, Kristina</creator><creator>Madut, Ayey S.</creator><creator>Subramanian, Harini</creator><creator>Trivedi, Ritu</creator><creator>Man, Hong</creator><creator>Mather, Marius</creator><creator>Brand, Alison</creator><creator>Elder, Elisabeth</creator><creator>Howle, Julie</creator><creator>Mann, Graham J</creator><creator>Amis, Terence C.</creator><creator>De Fazio, Anna</creator><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-8808-3183</orcidid></search><sort><creationdate>202210</creationdate><title>Cancer sleep symptom‐related phenotypic clustering differs across three cancer specific patient cohorts</title><author>Kairaitis, Kristina ; Madut, Ayey S. ; Subramanian, Harini ; Trivedi, Ritu ; Man, Hong ; Mather, Marius ; Brand, Alison ; Elder, Elisabeth ; Howle, Julie ; Mann, Graham J ; Amis, Terence C. ; De Fazio, Anna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4158-4b4df3839265031f2b946a7772684a280eb88912b1388d72c9f2f7e32f5814ac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>breast cancer</topic><topic>Breast Neoplasms</topic><topic>Cluster Analysis</topic><topic>endometrial cancer</topic><topic>Endometrial Neoplasms</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>melanoma</topic><topic>Melanoma - complications</topic><topic>Miscellaneous</topic><topic>Quality of Life</topic><topic>Sleep</topic><topic>Sleep Initiation and Maintenance Disorders</topic><topic>sleep symptom clusters</topic><topic>Sleepiness</topic><topic>Surveys and Questionnaires</topic><topic>Syndrome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kairaitis, Kristina</creatorcontrib><creatorcontrib>Madut, Ayey S.</creatorcontrib><creatorcontrib>Subramanian, Harini</creatorcontrib><creatorcontrib>Trivedi, Ritu</creatorcontrib><creatorcontrib>Man, Hong</creatorcontrib><creatorcontrib>Mather, Marius</creatorcontrib><creatorcontrib>Brand, Alison</creatorcontrib><creatorcontrib>Elder, Elisabeth</creatorcontrib><creatorcontrib>Howle, Julie</creatorcontrib><creatorcontrib>Mann, Graham J</creatorcontrib><creatorcontrib>Amis, Terence C.</creatorcontrib><creatorcontrib>De Fazio, Anna</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of sleep research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kairaitis, Kristina</au><au>Madut, Ayey S.</au><au>Subramanian, Harini</au><au>Trivedi, Ritu</au><au>Man, Hong</au><au>Mather, Marius</au><au>Brand, Alison</au><au>Elder, Elisabeth</au><au>Howle, Julie</au><au>Mann, Graham J</au><au>Amis, Terence C.</au><au>De Fazio, Anna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cancer sleep symptom‐related phenotypic clustering differs across three cancer specific patient cohorts</atitle><jtitle>Journal of sleep research</jtitle><addtitle>J Sleep Res</addtitle><date>2022-10</date><risdate>2022</risdate><volume>31</volume><issue>5</issue><spage>e13588</spage><epage>n/a</epage><pages>e13588-n/a</pages><issn>0962-1105</issn><issn>1365-2869</issn><eissn>1365-2869</eissn><abstract>Summary Specific sleep disorders have been linked to disease progression in different cancers. We hypothesised sleep symptom clusters would differ between cancer types. The aim of this study was to compare sleep symptom clusters in post‐treatment melanoma, breast and endometrial cancer patients. Data were collected from 124 breast cancer patients (1 male, 60 ± 15 years, 28.1 ± 6.6 kg/m2), 82 endometrial cancer patients (64.0 ± 12.5 years, 33.5 ± 10.4 kg/m2) and 112 melanoma patients (59 male, 65.0 ± 18.0 years, 29.1 ± 6.6 kg/m2). All patients completed validated questionnaires to assess sleep symptoms, including the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Functional Outcomes of Sleep Questionnaire‐10 (FOSQ‐10). Snoring, tiredness, observed apneas, age, BMI, and gender data were also collected. Binary values (PSQI, ISI, FOSQ), or continuous variables for sleepiness (ESS) and perceived sleep quality (PSQI), were created and sleep symptom clusters were identified and compared across cancer cohorts. Four distinct sleep symptom clusters were identified: minimally symptomatic (n = 152, 47.7%); insomnia‐predominant (n = 87, 24.9%); very sleepy with upper airway symptoms (n = 51, 16.3%), and severely symptomatic with severe dysfunction (n = 34, 11.1%). Breast cancer patients were significantly more likely to be in the insomnia predominant or severely symptomatic with severe dysfunction clusters, whereas melanoma patients were more likely to be minimally symptomatic or sleepy with upper airway symptoms (p &lt;0.0001). Endometrial cancer patients were equally distributed across symptom clusters. Sleep symptom clusters vary across cancer patients. A more personalised approach to the management of sleep‐related symptoms in these patients may improve the long term quality of life and survival.</abstract><cop>England</cop><pub>John Wiley and Sons Inc</pub><pmid>35470503</pmid><doi>10.1111/jsr.13588</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-8808-3183</orcidid><oa>free_for_read</oa></addata></record>
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source Wiley Free Content; MEDLINE; Wiley Online Library Journals Frontfile Complete; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects breast cancer
Breast Neoplasms
Cluster Analysis
endometrial cancer
Endometrial Neoplasms
Female
Humans
Male
melanoma
Melanoma - complications
Miscellaneous
Quality of Life
Sleep
Sleep Initiation and Maintenance Disorders
sleep symptom clusters
Sleepiness
Surveys and Questionnaires
Syndrome
title Cancer sleep symptom‐related phenotypic clustering differs across three cancer specific patient cohorts
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