Predictive Factors of the Degrees of Malnutrition According to GLIM Criteria in Head and Neck Cancer Patients: Valor Group
Background: Malnutrition is highly prevalent in patients with head and neck cancer, with relevant consequences in the treatment results. Methods: Multicenter observational study including 514 patients diagnosed with HNC. The morphofunctional assessment was carried out during the first 2 weeks of rad...
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creator | Vílchez-López, Francisco Javier González-Pacheco, María Fernández-Jiménez, Rocío Zarco-Martín, María Teresa Gonzalo-Marín, Montserrat Cobo-Molinos, Jesús Carmona-Llanos, Alba Muñoz-Garach, Araceli García-Luna, Pedro Pablo Herrera-Martínez, Aura D Zarco-Rodríguez, Felisa Pilar Galindo-Gallardo, María del Carmen Miguel-Luengo, Luis Fernández-Soto, María Luisa García-Almeida, José Manuel |
description | Background: Malnutrition is highly prevalent in patients with head and neck cancer, with relevant consequences in the treatment results. Methods: Multicenter observational study including 514 patients diagnosed with HNC. The morphofunctional assessment was carried out during the first 2 weeks of radiotherapy treatment. A correlation analysis between nutritional variables and groups of malnutrition, a multivariate logistic regression analysis, and a random forest analysis to select the most relevant variables to predict malnutrition were performed. Results: In total, 51.6% were undernourished (26.3% moderately and 25.3% severely). There was a negative correlation between morphofunctional variables and a positive correlation between hsCRP and well vs. moderate and well vs. severe malnutrition groups. The increase in different bioelectrical and ultrasound parameters was associated with a lower risk of moderate and severe malnutrition when groups with different degrees of malnutrition were compared. To predict the importance of morphofunctional variables on the risk of undernutrition, a nomogram, a random forest, and decision tree models were conducted. For the well vs. moderate, for the well vs. severe, and for the moderate vs. severe malnutrition groups, FFMI (cut-off < 20 kg/m2), BCMI (cut-off < 7.6 kg/m2), and RF-Y-axis (cut-off < 0.94 cm), respectively, were the most crucial variables, showing a greater probability of mortality in the two last comparisons. Conclusions: Malnutrition is very prevalent in HNC patients. Morphofunctional assessment with simple tools such as electrical impedance and muscle ultrasound allows an early nutritional diagnosis with an impact on survival. Therefore, these techniques should be incorporated into the daily clinical attention of patients with HNC. |
doi_str_mv | 10.3390/cancers16244255 |
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Methods: Multicenter observational study including 514 patients diagnosed with HNC. The morphofunctional assessment was carried out during the first 2 weeks of radiotherapy treatment. A correlation analysis between nutritional variables and groups of malnutrition, a multivariate logistic regression analysis, and a random forest analysis to select the most relevant variables to predict malnutrition were performed. Results: In total, 51.6% were undernourished (26.3% moderately and 25.3% severely). There was a negative correlation between morphofunctional variables and a positive correlation between hsCRP and well vs. moderate and well vs. severe malnutrition groups. The increase in different bioelectrical and ultrasound parameters was associated with a lower risk of moderate and severe malnutrition when groups with different degrees of malnutrition were compared. To predict the importance of morphofunctional variables on the risk of undernutrition, a nomogram, a random forest, and decision tree models were conducted. For the well vs. moderate, for the well vs. severe, and for the moderate vs. severe malnutrition groups, FFMI (cut-off < 20 kg/m2), BCMI (cut-off < 7.6 kg/m2), and RF-Y-axis (cut-off < 0.94 cm), respectively, were the most crucial variables, showing a greater probability of mortality in the two last comparisons. Conclusions: Malnutrition is very prevalent in HNC patients. Morphofunctional assessment with simple tools such as electrical impedance and muscle ultrasound allows an early nutritional diagnosis with an impact on survival. Therefore, these techniques should be incorporated into the daily clinical attention of patients with HNC.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers16244255</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Abdomen ; Biochemical analysis ; Body fat ; Cancer patients ; Cancer therapies ; Care and treatment ; Chemotherapy ; Functional morphology ; Head & neck cancer ; Head and neck ; Head and neck cancer ; Health aspects ; Longitudinal studies ; Malnutrition ; Medical prognosis ; Mortality ; Musculoskeletal system ; Nutrition ; Nutritional status ; Parenteral nutrition ; Patients ; Quality of life ; Radiation therapy ; Spain ; Ultrasonic imaging ; Ultrasound</subject><ispartof>Cancers, 2024-12, Vol.16 (24), p.4255</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 by the authors. 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1919-551ba259e8e76cf8188d9ce6db08f8aa357ca913efd9ec1bf9203fbe4dd6b0e13</cites><orcidid>0009-0003-0106-5594 ; 0000-0001-7780-1402</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674739/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674739/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27922,27923,53789,53791</link.rule.ids></links><search><creatorcontrib>Vílchez-López, Francisco Javier</creatorcontrib><creatorcontrib>González-Pacheco, María</creatorcontrib><creatorcontrib>Fernández-Jiménez, Rocío</creatorcontrib><creatorcontrib>Zarco-Martín, María Teresa</creatorcontrib><creatorcontrib>Gonzalo-Marín, Montserrat</creatorcontrib><creatorcontrib>Cobo-Molinos, Jesús</creatorcontrib><creatorcontrib>Carmona-Llanos, Alba</creatorcontrib><creatorcontrib>Muñoz-Garach, Araceli</creatorcontrib><creatorcontrib>García-Luna, Pedro Pablo</creatorcontrib><creatorcontrib>Herrera-Martínez, Aura D</creatorcontrib><creatorcontrib>Zarco-Rodríguez, Felisa Pilar</creatorcontrib><creatorcontrib>Galindo-Gallardo, María del Carmen</creatorcontrib><creatorcontrib>Miguel-Luengo, Luis</creatorcontrib><creatorcontrib>Fernández-Soto, María Luisa</creatorcontrib><creatorcontrib>García-Almeida, José Manuel</creatorcontrib><title>Predictive Factors of the Degrees of Malnutrition According to GLIM Criteria in Head and Neck Cancer Patients: Valor Group</title><title>Cancers</title><description>Background: Malnutrition is highly prevalent in patients with head and neck cancer, with relevant consequences in the treatment results. Methods: Multicenter observational study including 514 patients diagnosed with HNC. The morphofunctional assessment was carried out during the first 2 weeks of radiotherapy treatment. A correlation analysis between nutritional variables and groups of malnutrition, a multivariate logistic regression analysis, and a random forest analysis to select the most relevant variables to predict malnutrition were performed. Results: In total, 51.6% were undernourished (26.3% moderately and 25.3% severely). There was a negative correlation between morphofunctional variables and a positive correlation between hsCRP and well vs. moderate and well vs. severe malnutrition groups. The increase in different bioelectrical and ultrasound parameters was associated with a lower risk of moderate and severe malnutrition when groups with different degrees of malnutrition were compared. To predict the importance of morphofunctional variables on the risk of undernutrition, a nomogram, a random forest, and decision tree models were conducted. For the well vs. moderate, for the well vs. severe, and for the moderate vs. severe malnutrition groups, FFMI (cut-off < 20 kg/m2), BCMI (cut-off < 7.6 kg/m2), and RF-Y-axis (cut-off < 0.94 cm), respectively, were the most crucial variables, showing a greater probability of mortality in the two last comparisons. Conclusions: Malnutrition is very prevalent in HNC patients. Morphofunctional assessment with simple tools such as electrical impedance and muscle ultrasound allows an early nutritional diagnosis with an impact on survival. Therefore, these techniques should be incorporated into the daily clinical attention of patients with HNC.</description><subject>Abdomen</subject><subject>Biochemical analysis</subject><subject>Body fat</subject><subject>Cancer patients</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>Chemotherapy</subject><subject>Functional morphology</subject><subject>Head & neck cancer</subject><subject>Head and neck</subject><subject>Head and neck cancer</subject><subject>Health aspects</subject><subject>Longitudinal studies</subject><subject>Malnutrition</subject><subject>Medical prognosis</subject><subject>Mortality</subject><subject>Musculoskeletal system</subject><subject>Nutrition</subject><subject>Nutritional status</subject><subject>Parenteral nutrition</subject><subject>Patients</subject><subject>Quality of life</subject><subject>Radiation therapy</subject><subject>Spain</subject><subject>Ultrasonic imaging</subject><subject>Ultrasound</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptUU1v1DAQjRBIVG3PXC1x3taO4zjmglYL3VbaQg_A1XLG461L1l5sp1L59bgfAoqYOczXm6enmaZ5w-gJ54qeggmAKbO-7bpWiBfNQUtlu-h71b38K3_dHOd8Q6txzmQvD5qfVwmth-JvkZwZKDFlEh0p10g-4DYhPpSXZgpzSb74GMgSICbrw5aUSNabi0uyqhNM3hAfyDkaS0yw5BPCd7J60EWuTPEYSn5HvpkpJrJOcd4fNa-cmTIeP8XD5uvZxy-r88Xm8_pitdwsgCmmFkKw0bRC4YCyBzewYbAKsLcjHdxgDBcSjGIcnVUIbHSqpdyN2FnbjxQZP2zeP_Lu53GHFqqQZCa9T35n0p2Oxuvnk-Cv9TbeasZ62UmuKsPbJ4YUf8yYi76JcwpVtOasU6KTlIs_qK2ZUPvgYmWDnc-gl0Nbz80EkxV18h9UdYs7DzGg87X_bOH0cQFSzDmh-62cUX3_fP3P8_kviemj4A</recordid><startdate>20241221</startdate><enddate>20241221</enddate><creator>Vílchez-López, 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AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7TO</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>5PM</scope><orcidid>https://orcid.org/0009-0003-0106-5594</orcidid><orcidid>https://orcid.org/0000-0001-7780-1402</orcidid></search><sort><creationdate>20241221</creationdate><title>Predictive Factors of the Degrees of Malnutrition According to GLIM Criteria in Head and Neck Cancer Patients: Valor Group</title><author>Vílchez-López, Francisco Javier ; González-Pacheco, María ; Fernández-Jiménez, Rocío ; Zarco-Martín, María Teresa ; Gonzalo-Marín, Montserrat ; Cobo-Molinos, Jesús ; Carmona-Llanos, Alba ; Muñoz-Garach, Araceli ; García-Luna, Pedro Pablo ; Herrera-Martínez, Aura D ; Zarco-Rodríguez, Felisa Pilar ; Galindo-Gallardo, María del Carmen ; Miguel-Luengo, Luis ; Fernández-Soto, María Luisa ; García-Almeida, José Manuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1919-551ba259e8e76cf8188d9ce6db08f8aa357ca913efd9ec1bf9203fbe4dd6b0e13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Abdomen</topic><topic>Biochemical analysis</topic><topic>Body fat</topic><topic>Cancer patients</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>Chemotherapy</topic><topic>Functional morphology</topic><topic>Head & neck cancer</topic><topic>Head and neck</topic><topic>Head and neck cancer</topic><topic>Health aspects</topic><topic>Longitudinal studies</topic><topic>Malnutrition</topic><topic>Medical prognosis</topic><topic>Mortality</topic><topic>Musculoskeletal system</topic><topic>Nutrition</topic><topic>Nutritional status</topic><topic>Parenteral nutrition</topic><topic>Patients</topic><topic>Quality of life</topic><topic>Radiation therapy</topic><topic>Spain</topic><topic>Ultrasonic imaging</topic><topic>Ultrasound</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vílchez-López, Francisco Javier</creatorcontrib><creatorcontrib>González-Pacheco, María</creatorcontrib><creatorcontrib>Fernández-Jiménez, Rocío</creatorcontrib><creatorcontrib>Zarco-Martín, María Teresa</creatorcontrib><creatorcontrib>Gonzalo-Marín, Montserrat</creatorcontrib><creatorcontrib>Cobo-Molinos, Jesús</creatorcontrib><creatorcontrib>Carmona-Llanos, Alba</creatorcontrib><creatorcontrib>Muñoz-Garach, Araceli</creatorcontrib><creatorcontrib>García-Luna, Pedro Pablo</creatorcontrib><creatorcontrib>Herrera-Martínez, Aura D</creatorcontrib><creatorcontrib>Zarco-Rodríguez, Felisa Pilar</creatorcontrib><creatorcontrib>Galindo-Gallardo, María del Carmen</creatorcontrib><creatorcontrib>Miguel-Luengo, Luis</creatorcontrib><creatorcontrib>Fernández-Soto, María Luisa</creatorcontrib><creatorcontrib>García-Almeida, José Manuel</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni 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Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vílchez-López, Francisco Javier</au><au>González-Pacheco, María</au><au>Fernández-Jiménez, Rocío</au><au>Zarco-Martín, María Teresa</au><au>Gonzalo-Marín, Montserrat</au><au>Cobo-Molinos, Jesús</au><au>Carmona-Llanos, Alba</au><au>Muñoz-Garach, Araceli</au><au>García-Luna, Pedro Pablo</au><au>Herrera-Martínez, Aura D</au><au>Zarco-Rodríguez, Felisa Pilar</au><au>Galindo-Gallardo, María del Carmen</au><au>Miguel-Luengo, Luis</au><au>Fernández-Soto, María Luisa</au><au>García-Almeida, José Manuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictive Factors of the Degrees of Malnutrition According to GLIM Criteria in Head and Neck Cancer Patients: Valor Group</atitle><jtitle>Cancers</jtitle><date>2024-12-21</date><risdate>2024</risdate><volume>16</volume><issue>24</issue><spage>4255</spage><pages>4255-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><abstract>Background: Malnutrition is highly prevalent in patients with head and neck cancer, with relevant consequences in the treatment results. Methods: Multicenter observational study including 514 patients diagnosed with HNC. The morphofunctional assessment was carried out during the first 2 weeks of radiotherapy treatment. A correlation analysis between nutritional variables and groups of malnutrition, a multivariate logistic regression analysis, and a random forest analysis to select the most relevant variables to predict malnutrition were performed. Results: In total, 51.6% were undernourished (26.3% moderately and 25.3% severely). There was a negative correlation between morphofunctional variables and a positive correlation between hsCRP and well vs. moderate and well vs. severe malnutrition groups. The increase in different bioelectrical and ultrasound parameters was associated with a lower risk of moderate and severe malnutrition when groups with different degrees of malnutrition were compared. To predict the importance of morphofunctional variables on the risk of undernutrition, a nomogram, a random forest, and decision tree models were conducted. For the well vs. moderate, for the well vs. severe, and for the moderate vs. severe malnutrition groups, FFMI (cut-off < 20 kg/m2), BCMI (cut-off < 7.6 kg/m2), and RF-Y-axis (cut-off < 0.94 cm), respectively, were the most crucial variables, showing a greater probability of mortality in the two last comparisons. Conclusions: Malnutrition is very prevalent in HNC patients. Morphofunctional assessment with simple tools such as electrical impedance and muscle ultrasound allows an early nutritional diagnosis with an impact on survival. Therefore, these techniques should be incorporated into the daily clinical attention of patients with HNC.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/cancers16244255</doi><orcidid>https://orcid.org/0009-0003-0106-5594</orcidid><orcidid>https://orcid.org/0000-0001-7780-1402</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abdomen Biochemical analysis Body fat Cancer patients Cancer therapies Care and treatment Chemotherapy Functional morphology Head & neck cancer Head and neck Head and neck cancer Health aspects Longitudinal studies Malnutrition Medical prognosis Mortality Musculoskeletal system Nutrition Nutritional status Parenteral nutrition Patients Quality of life Radiation therapy Spain Ultrasonic imaging Ultrasound |
title | Predictive Factors of the Degrees of Malnutrition According to GLIM Criteria in Head and Neck Cancer Patients: Valor Group |
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