Different nutritional screening tools and recommended screening algorithm for pediatric oncology patients

Gallo, N. ✉ [Galló, Nóra (Dietetika), author] II. Department of Pediatrics (SU / FM / C); Horvath, K. [Horváth, Klára (Alváskutatás Gyer...), author] II. Department of Pediatrics (SU / FM / C); Czuppon, K. [Czuppon, Krisztina (dietetika), author] II. Department of Pediatrics (SU / FM / C); Tomsits, E. [Tomsits, Erika (Lipidek szerepe a...), author] II. Department of Pediatrics (SU / FM / C); Felegyhazi, E. [Félegyházi, Edina (dietetika), author] II. Department of Pediatrics (SU / FM / C); Kovacs, G.T. [Kovács, Gábor (Gyermekgyógyászat...), author] II. Department of Pediatrics (SU / FM / C)

English Article (Journal Article) Scientific
Published: CLINICAL NUTRITION 0261-5614 1532-1983 40 (6) pp. 3836-3841 2021
  • SJR Scopus - Critical Care and Intensive Care Medicine: D1
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Background & aims: Cancer is one of the leading causes of death for children; however, appropriate nutritional status can positively affect disease progression and outcome. The aim of this study was to present our self-developed nutritional risk screening method, relate it to another validated tool and to objective bio-impedance measures. We intended to recommend a screening algorithm which can be used in our pediatric oncology facilities. Methods: We analysed data from 109 pediatric oncology patients (age 3–18) at the 2nd Department of Pediatrics, Semmelweis University between 2017 and 2018. The nutritional status was assessed by the Nutrition screening tool for childhood cancer (SCAN), Nutrition risk screening for pediatric cancer (NRS-PC) our own self-developed screening tool and Bio-impedance analysis (InBody 720 and S10). Classifier properties for low muscle mass measured by Bio-impedance analysis were compared for SCAN and NRS-PC in the overall sample and in the different phases of the disease. Results: The AUC of 0.67 [95% CI:0.58,0.75] of the SCAN was significantly lower (Z = −2.46, p = 0.014) than in the case of the NRS-PC (AUC = 0.75 [95% CI:0.67,0.82]), indicating that NRS-PC has better classifier properties to identify children with lower muscle mass. No significant difference was found in the different phases of the disease. Conclusions: Based on our results, we suggest screening high BMI patients first with NRS-PC. However, in case of low BMI bio-impedance measures provide more precise information on muscle mass and nutritional risk. Further data are needed to decide whether the NRS-PC is sensitive enough in normal BMI patients. © 2021 The Authors
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2025-04-02 00:03