A novel, automated nutrition screening system as a predictor of nutritional risk in an oncology day treatment unit (ODTU)

Abbott, J., Teleni, L., McKavanagh, D., Watson, J., McCarthy, A., & Isenring, E. (2014) A novel, automated nutrition screening system as a predictor of nutritional risk in an oncology day treatment unit (ODTU). Supportive Care in Cancer, 22(8), pp. 2107-2112.

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Abstract

Purpose

Paper-based nutrition screening tools can be challenging to implement in the ambulatory oncology setting. The aim of this study was to determine the validity of the Malnutrition Screening Tool (MST) and a novel, automated nutrition screening system compared to a ‘gold standard’ full nutrition assessment using the Patient-Generated Subjective Global Assessment (PG-SGA).

Methods

An observational, cross-sectional study was conducted in an outpatient oncology day treatment unit (ODTU) within an Australian tertiary health service. Eligibility criteria were as follows: ≥18 years, receiving outpatient anticancer treatment and English literate. Patients self-administered the MST. A dietitian assessed nutritional status using the PGSGA, blinded to the MST score. Automated screening system data were extracted from an electronic oncology prescribing system. This system used weight loss over 3 to 6 weeks prior to the most recent weight record or age-categorised body mass index (BMI) to identify nutritional risk. Sensitivity and specificity against PG-SGA (malnutrition) were calculated using contingency tables and receiver operating curves.

Results

There were a total of 300 oncology outpatients (51.7 % male, 58.6±13.3 years). The area under the curve (AUC) for weight loss alone was 0.69 with a cut-off value of ≥1 % weight loss yielding 63 % sensitivity and 76.7 % specificity. MST (score ≥2) resulted in 70.6 % sensitivity and 69.5 % specificity, AUC 0.77.

Conclusions

Both the MST and the automated method fell short of the accepted professional standard for sensitivity (~≥80 %) derived from the PG-SGA. Further investigation into other automated nutrition screening options and the most appropriate parameters available electronically is warranted to support targeted service provision.

Impact and interest:

4 citations in Scopus
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4 citations in Web of Science®

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ID Code: 69018
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Nutrition screening, Sensitivity, Specificity, Malnutrition, Cancer, Automated
DOI: 10.1007/s00520-014-2210-7
ISSN: 1433-7339
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > NURSING (111000) > Clinical Nursing - Secondary (Acute Care) (111003)
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > NURSING (111000) > Nursing not elsewhere classified (111099)
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Nursing
Copyright Owner: Copyright 2014 Springer-Verlag Berlin Heidelberg
Deposited On: 21 Mar 2014 00:51
Last Modified: 07 Sep 2015 09:39

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