Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry
Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared...
Gespeichert in:
Veröffentlicht in: | Journal of geriatric oncology 2024-07, Vol.15 (6), p.101815, Article 101815 |
---|---|
Hauptverfasser: | , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 6 |
container_start_page | 101815 |
container_title | Journal of geriatric oncology |
container_volume | 15 |
creator | Thai, Sydney T. Lund, Jennifer L. Poole, Charles Buse, John B. Stürmer, Til Harmon, Christian A. Al-Obaidi, Mustafa Williams, Grant R. |
description | Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared performance by sex and diabetes status.
We analyzed patients in the Cancer & Aging Resilience Evaluation (CARE) Registry. Frailty and diabetes were captured using a patient-reported geriatric assessment (CARE tool). Frailty was defined using CARE frailty index (CARE-FI) based on principles of deficit accumulation. SMD was calculated from computed tomography scans (L3 vertebrae). Analyses were conducted by sex and diabetes status. Scatterplots and linear regression described crude associations between SMD and frailty score. Classification performance (frail vs. non-frail) was analyzed with (1) area under the receiver operating characteristic curves (AUC) and confidence intervals (CIs); and (2) sensitivity/specificity for sex-specific SMD quartile cut-offs (Q1, median, Q3). Performance was compared between patients with and without diabetes using differences and estimated CIs (2000 bootstrap replicates). We additionally calculated positive and negative likelihood ratios (LR+, LR-).
The analytic cohort included 872 patients (39% female, median age 68 years, 27% with diabetes) with predominately stage III/IV gastrointestinal cancer; >60% planning to initiate first-line chemotherapy. SMD was negatively associated with frailty score; models were best fit in male patients with diabetes. AUC estimates for female (range: 0.58–0.62) and male (0.58–0.68) patients were low. Q3 cut-offs had high sensitivity (range: 0.76–0.89), but poor specificity (0.25–0.34). Diabetes did not impact estimates for female patients. Male patients with diabetes had greater sensitivity estimates compared to those without (sensitivity differences: 0.23 [0.07, 0.38], 0.08 [−0.07, 0.24], and 0.11 [0.00, 0.22] for Q1, median, Q3, respectively). LR estimates were most notable for male patients with diabetes (LR+ = 2.92, Q1 cut-off; LR- = 0.46, Q3 cut-off).
Using SMD alone to screen older patients for geriatric assessment requires improvement. High-sensitivity cut-off points could miss 11–24% of patients with frailty, and many non-frail patients may be flagged. Screening with SMD is practical but work is needed to understand clinical andresource impacts of different cut-off points. Future research sho |
doi_str_mv | 10.1016/j.jgo.2024.101815 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3070822664</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1879406824001139</els_id><sourcerecordid>3070822664</sourcerecordid><originalsourceid>FETCH-LOGICAL-c235t-14d2e5e1027ca56ba8d1f278102206a91011457ad9259e4fcd245ec075a374823</originalsourceid><addsrcrecordid>eNp9kEtPGzEUhS1UBFHgB7BBXnaTYHvGj2lXURSgEhISj7Xl2HeCU89MantaZd0_jqNQlr2be310zpH8IXRFyZwSKm628-1mmDPC6sNbUX6CJlTJZlYTKb583kKdo8uUtqRMxZpGijN0XinViIbTCfr7_BMCZBNwNyYbADvok897vIPYDrEzvQVcDpxsBOh9v8FtND4Uh-_xEBxEbNwYcsJ_fH7D9hAoUu9wfgPsu52xGQ8tdt6sIUP6hl-Kvlw8rfATbHzKcX-BTlsTElx-7Cl6vV29LO9nD493P5aLh5llFc8zWjsGHChh0hou1kY52jKpisCIME2hQGsujWsYb6BurWM1B0skN5WsFaum6OuxdxeHXyOkrDufLIRgehjGpCsiiWJMiLpY6dFq45BShFbvou9M3GtK9AG_3uqCXx_w6yP-krn-qB_XHbjPxD_YxfD9aIDyyd8eok7WQ-HlfASbtRv8f-rfAVVdlUs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3070822664</pqid></control><display><type>article</type><title>Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><creator>Thai, Sydney T. ; Lund, Jennifer L. ; Poole, Charles ; Buse, John B. ; Stürmer, Til ; Harmon, Christian A. ; Al-Obaidi, Mustafa ; Williams, Grant R.</creator><creatorcontrib>Thai, Sydney T. ; Lund, Jennifer L. ; Poole, Charles ; Buse, John B. ; Stürmer, Til ; Harmon, Christian A. ; Al-Obaidi, Mustafa ; Williams, Grant R.</creatorcontrib><description>Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared performance by sex and diabetes status.
We analyzed patients in the Cancer & Aging Resilience Evaluation (CARE) Registry. Frailty and diabetes were captured using a patient-reported geriatric assessment (CARE tool). Frailty was defined using CARE frailty index (CARE-FI) based on principles of deficit accumulation. SMD was calculated from computed tomography scans (L3 vertebrae). Analyses were conducted by sex and diabetes status. Scatterplots and linear regression described crude associations between SMD and frailty score. Classification performance (frail vs. non-frail) was analyzed with (1) area under the receiver operating characteristic curves (AUC) and confidence intervals (CIs); and (2) sensitivity/specificity for sex-specific SMD quartile cut-offs (Q1, median, Q3). Performance was compared between patients with and without diabetes using differences and estimated CIs (2000 bootstrap replicates). We additionally calculated positive and negative likelihood ratios (LR+, LR-).
The analytic cohort included 872 patients (39% female, median age 68 years, 27% with diabetes) with predominately stage III/IV gastrointestinal cancer; >60% planning to initiate first-line chemotherapy. SMD was negatively associated with frailty score; models were best fit in male patients with diabetes. AUC estimates for female (range: 0.58–0.62) and male (0.58–0.68) patients were low. Q3 cut-offs had high sensitivity (range: 0.76–0.89), but poor specificity (0.25–0.34). Diabetes did not impact estimates for female patients. Male patients with diabetes had greater sensitivity estimates compared to those without (sensitivity differences: 0.23 [0.07, 0.38], 0.08 [−0.07, 0.24], and 0.11 [0.00, 0.22] for Q1, median, Q3, respectively). LR estimates were most notable for male patients with diabetes (LR+ = 2.92, Q1 cut-off; LR- = 0.46, Q3 cut-off).
Using SMD alone to screen older patients for geriatric assessment requires improvement. High-sensitivity cut-off points could miss 11–24% of patients with frailty, and many non-frail patients may be flagged. Screening with SMD is practical but work is needed to understand clinical andresource impacts of different cut-off points. Future research should evaluate performance with additional clinical data and in subgroups.</description><identifier>ISSN: 1879-4068</identifier><identifier>ISSN: 1879-4076</identifier><identifier>EISSN: 1879-4076</identifier><identifier>DOI: 10.1016/j.jgo.2024.101815</identifier><identifier>PMID: 38896951</identifier><language>eng</language><publisher>Netherlands: Elsevier Ltd</publisher><subject>Aged ; Aged, 80 and over ; cancer ; CT scan ; Diabetes Mellitus - epidemiology ; Female ; Frail Elderly - statistics & numerical data ; Frailty ; Frailty - diagnosis ; Geriatric Assessment - methods ; Geriatric oncology ; Humans ; Male ; Muscle, Skeletal - diagnostic imaging ; Myosteatosis ; Neoplasms - complications ; Registries ; Sarcopenia - diagnosis ; Sarcopenia - epidemiology ; Sex Factors ; Skeletal muscle density ; Tomography, X-Ray Computed</subject><ispartof>Journal of geriatric oncology, 2024-07, Vol.15 (6), p.101815, Article 101815</ispartof><rights>2024 Elsevier Ltd</rights><rights>Copyright © 2024 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c235t-14d2e5e1027ca56ba8d1f278102206a91011457ad9259e4fcd245ec075a374823</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1879406824001139$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38896951$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Thai, Sydney T.</creatorcontrib><creatorcontrib>Lund, Jennifer L.</creatorcontrib><creatorcontrib>Poole, Charles</creatorcontrib><creatorcontrib>Buse, John B.</creatorcontrib><creatorcontrib>Stürmer, Til</creatorcontrib><creatorcontrib>Harmon, Christian A.</creatorcontrib><creatorcontrib>Al-Obaidi, Mustafa</creatorcontrib><creatorcontrib>Williams, Grant R.</creatorcontrib><title>Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry</title><title>Journal of geriatric oncology</title><addtitle>J Geriatr Oncol</addtitle><description>Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared performance by sex and diabetes status.
We analyzed patients in the Cancer & Aging Resilience Evaluation (CARE) Registry. Frailty and diabetes were captured using a patient-reported geriatric assessment (CARE tool). Frailty was defined using CARE frailty index (CARE-FI) based on principles of deficit accumulation. SMD was calculated from computed tomography scans (L3 vertebrae). Analyses were conducted by sex and diabetes status. Scatterplots and linear regression described crude associations between SMD and frailty score. Classification performance (frail vs. non-frail) was analyzed with (1) area under the receiver operating characteristic curves (AUC) and confidence intervals (CIs); and (2) sensitivity/specificity for sex-specific SMD quartile cut-offs (Q1, median, Q3). Performance was compared between patients with and without diabetes using differences and estimated CIs (2000 bootstrap replicates). We additionally calculated positive and negative likelihood ratios (LR+, LR-).
The analytic cohort included 872 patients (39% female, median age 68 years, 27% with diabetes) with predominately stage III/IV gastrointestinal cancer; >60% planning to initiate first-line chemotherapy. SMD was negatively associated with frailty score; models were best fit in male patients with diabetes. AUC estimates for female (range: 0.58–0.62) and male (0.58–0.68) patients were low. Q3 cut-offs had high sensitivity (range: 0.76–0.89), but poor specificity (0.25–0.34). Diabetes did not impact estimates for female patients. Male patients with diabetes had greater sensitivity estimates compared to those without (sensitivity differences: 0.23 [0.07, 0.38], 0.08 [−0.07, 0.24], and 0.11 [0.00, 0.22] for Q1, median, Q3, respectively). LR estimates were most notable for male patients with diabetes (LR+ = 2.92, Q1 cut-off; LR- = 0.46, Q3 cut-off).
Using SMD alone to screen older patients for geriatric assessment requires improvement. High-sensitivity cut-off points could miss 11–24% of patients with frailty, and many non-frail patients may be flagged. Screening with SMD is practical but work is needed to understand clinical andresource impacts of different cut-off points. Future research should evaluate performance with additional clinical data and in subgroups.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>cancer</subject><subject>CT scan</subject><subject>Diabetes Mellitus - epidemiology</subject><subject>Female</subject><subject>Frail Elderly - statistics & numerical data</subject><subject>Frailty</subject><subject>Frailty - diagnosis</subject><subject>Geriatric Assessment - methods</subject><subject>Geriatric oncology</subject><subject>Humans</subject><subject>Male</subject><subject>Muscle, Skeletal - diagnostic imaging</subject><subject>Myosteatosis</subject><subject>Neoplasms - complications</subject><subject>Registries</subject><subject>Sarcopenia - diagnosis</subject><subject>Sarcopenia - epidemiology</subject><subject>Sex Factors</subject><subject>Skeletal muscle density</subject><subject>Tomography, X-Ray Computed</subject><issn>1879-4068</issn><issn>1879-4076</issn><issn>1879-4076</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtPGzEUhS1UBFHgB7BBXnaTYHvGj2lXURSgEhISj7Xl2HeCU89MantaZd0_jqNQlr2be310zpH8IXRFyZwSKm628-1mmDPC6sNbUX6CJlTJZlYTKb583kKdo8uUtqRMxZpGijN0XinViIbTCfr7_BMCZBNwNyYbADvok897vIPYDrEzvQVcDpxsBOh9v8FtND4Uh-_xEBxEbNwYcsJ_fH7D9hAoUu9wfgPsu52xGQ8tdt6sIUP6hl-Kvlw8rfATbHzKcX-BTlsTElx-7Cl6vV29LO9nD493P5aLh5llFc8zWjsGHChh0hou1kY52jKpisCIME2hQGsujWsYb6BurWM1B0skN5WsFaum6OuxdxeHXyOkrDufLIRgehjGpCsiiWJMiLpY6dFq45BShFbvou9M3GtK9AG_3uqCXx_w6yP-krn-qB_XHbjPxD_YxfD9aIDyyd8eok7WQ-HlfASbtRv8f-rfAVVdlUs</recordid><startdate>202407</startdate><enddate>202407</enddate><creator>Thai, Sydney T.</creator><creator>Lund, Jennifer L.</creator><creator>Poole, Charles</creator><creator>Buse, John B.</creator><creator>Stürmer, Til</creator><creator>Harmon, Christian A.</creator><creator>Al-Obaidi, Mustafa</creator><creator>Williams, Grant R.</creator><general>Elsevier Ltd</general><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></search><sort><creationdate>202407</creationdate><title>Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry</title><author>Thai, Sydney T. ; Lund, Jennifer L. ; Poole, Charles ; Buse, John B. ; Stürmer, Til ; Harmon, Christian A. ; Al-Obaidi, Mustafa ; Williams, Grant R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c235t-14d2e5e1027ca56ba8d1f278102206a91011457ad9259e4fcd245ec075a374823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>cancer</topic><topic>CT scan</topic><topic>Diabetes Mellitus - epidemiology</topic><topic>Female</topic><topic>Frail Elderly - statistics & numerical data</topic><topic>Frailty</topic><topic>Frailty - diagnosis</topic><topic>Geriatric Assessment - methods</topic><topic>Geriatric oncology</topic><topic>Humans</topic><topic>Male</topic><topic>Muscle, Skeletal - diagnostic imaging</topic><topic>Myosteatosis</topic><topic>Neoplasms - complications</topic><topic>Registries</topic><topic>Sarcopenia - diagnosis</topic><topic>Sarcopenia - epidemiology</topic><topic>Sex Factors</topic><topic>Skeletal muscle density</topic><topic>Tomography, X-Ray Computed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Thai, Sydney T.</creatorcontrib><creatorcontrib>Lund, Jennifer L.</creatorcontrib><creatorcontrib>Poole, Charles</creatorcontrib><creatorcontrib>Buse, John B.</creatorcontrib><creatorcontrib>Stürmer, Til</creatorcontrib><creatorcontrib>Harmon, Christian A.</creatorcontrib><creatorcontrib>Al-Obaidi, Mustafa</creatorcontrib><creatorcontrib>Williams, Grant R.</creatorcontrib><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><jtitle>Journal of geriatric oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Thai, Sydney T.</au><au>Lund, Jennifer L.</au><au>Poole, Charles</au><au>Buse, John B.</au><au>Stürmer, Til</au><au>Harmon, Christian A.</au><au>Al-Obaidi, Mustafa</au><au>Williams, Grant R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry</atitle><jtitle>Journal of geriatric oncology</jtitle><addtitle>J Geriatr Oncol</addtitle><date>2024-07</date><risdate>2024</risdate><volume>15</volume><issue>6</issue><spage>101815</spage><pages>101815-</pages><artnum>101815</artnum><issn>1879-4068</issn><issn>1879-4076</issn><eissn>1879-4076</eissn><abstract>Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared performance by sex and diabetes status.
We analyzed patients in the Cancer & Aging Resilience Evaluation (CARE) Registry. Frailty and diabetes were captured using a patient-reported geriatric assessment (CARE tool). Frailty was defined using CARE frailty index (CARE-FI) based on principles of deficit accumulation. SMD was calculated from computed tomography scans (L3 vertebrae). Analyses were conducted by sex and diabetes status. Scatterplots and linear regression described crude associations between SMD and frailty score. Classification performance (frail vs. non-frail) was analyzed with (1) area under the receiver operating characteristic curves (AUC) and confidence intervals (CIs); and (2) sensitivity/specificity for sex-specific SMD quartile cut-offs (Q1, median, Q3). Performance was compared between patients with and without diabetes using differences and estimated CIs (2000 bootstrap replicates). We additionally calculated positive and negative likelihood ratios (LR+, LR-).
The analytic cohort included 872 patients (39% female, median age 68 years, 27% with diabetes) with predominately stage III/IV gastrointestinal cancer; >60% planning to initiate first-line chemotherapy. SMD was negatively associated with frailty score; models were best fit in male patients with diabetes. AUC estimates for female (range: 0.58–0.62) and male (0.58–0.68) patients were low. Q3 cut-offs had high sensitivity (range: 0.76–0.89), but poor specificity (0.25–0.34). Diabetes did not impact estimates for female patients. Male patients with diabetes had greater sensitivity estimates compared to those without (sensitivity differences: 0.23 [0.07, 0.38], 0.08 [−0.07, 0.24], and 0.11 [0.00, 0.22] for Q1, median, Q3, respectively). LR estimates were most notable for male patients with diabetes (LR+ = 2.92, Q1 cut-off; LR- = 0.46, Q3 cut-off).
Using SMD alone to screen older patients for geriatric assessment requires improvement. High-sensitivity cut-off points could miss 11–24% of patients with frailty, and many non-frail patients may be flagged. Screening with SMD is practical but work is needed to understand clinical andresource impacts of different cut-off points. Future research should evaluate performance with additional clinical data and in subgroups.</abstract><cop>Netherlands</cop><pub>Elsevier Ltd</pub><pmid>38896951</pmid><doi>10.1016/j.jgo.2024.101815</doi></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1879-4068 |
ispartof | Journal of geriatric oncology, 2024-07, Vol.15 (6), p.101815, Article 101815 |
issn | 1879-4068 1879-4076 1879-4076 |
language | eng |
recordid | cdi_proquest_miscellaneous_3070822664 |
source | MEDLINE; Elsevier ScienceDirect Journals |
subjects | Aged Aged, 80 and over cancer CT scan Diabetes Mellitus - epidemiology Female Frail Elderly - statistics & numerical data Frailty Frailty - diagnosis Geriatric Assessment - methods Geriatric oncology Humans Male Muscle, Skeletal - diagnostic imaging Myosteatosis Neoplasms - complications Registries Sarcopenia - diagnosis Sarcopenia - epidemiology Sex Factors Skeletal muscle density Tomography, X-Ray Computed |
title | Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T23%3A17%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Skeletal%20muscle%20density%20performance%20for%20screening%20frailty%20in%20older%20adults%20with%20cancer%20and%20the%20impact%20of%20diabetes:%20The%20CARE%20Registry&rft.jtitle=Journal%20of%20geriatric%20oncology&rft.au=Thai,%20Sydney%20T.&rft.date=2024-07&rft.volume=15&rft.issue=6&rft.spage=101815&rft.pages=101815-&rft.artnum=101815&rft.issn=1879-4068&rft.eissn=1879-4076&rft_id=info:doi/10.1016/j.jgo.2024.101815&rft_dat=%3Cproquest_cross%3E3070822664%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3070822664&rft_id=info:pmid/38896951&rft_els_id=S1879406824001139&rfr_iscdi=true |