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...
| Autores: | , , , , , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/387005 |
| Acceso en línea: | http://hdl.handle.net/10261/387005 https://api.elsevier.com/content/abstract/scopus_id/85213319439 |
| Access Level: | acceso abierto |
| Palabra clave: | Glim criteria Head and neck cancer Malnutrition Morphofunctional assessment |
| Sumario: | 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. |
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