Validating a novel, low cost, automated malnutrition screening system as a predictor of nutritional risk in the Oncology Day Care Unit — ASN Events
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Validating a novel, low cost, automated malnutrition screening system as a predictor of nutritional risk in the Oncology Day Care Unit (#141)

Jessica Abbott 1 , L Teleni 1 , D Mckavanagh 1 , J Watson 1 , A McCarthy 2 , E Isenring 1 3
  1. Princess Alexandra Hospital, Woolloongabba, QLD, Australia
  2. Queensland University of Technology, Kelvin Grove, QLD, Australia
  3. University of Queensland, St Lucia, QLD, Australia

Background: Cancer-related malnutrition is associated with increased morbidity, poorer tolerance of treatment, decreased quality of life, increased hospital admissions, and increased health care costs (Isenring et al., 2013). This study’s aim was to determine whether a novel, automated screening system was a useful tool for nutrition screening when compared against a full nutrition assessment using the Patient-Generated Subjective Global Assessment (PG-SGA) tool.

Methods: A single site, observational, cross-sectional study was conducted in an outpatient oncology day care unit within a Queensland tertiary facility, with three hundred outpatients (51.7% male, mean age 58.6 ±13.3 years). Eligibility criteria: ≥18 years, receiving anticancer treatment, able to provide written consent. Patients completed the Malnutrition Screening Tool (MST). Nutritional status was assessed using the PG-SGA.  Data for the automated screening system was extracted from the pharmacy software program Charm. This included body mass index (BMI) and weight records dating back up to six months.

Results: The prevalence of malnutrition was 17%. Any weight loss over three to six weeks prior to the most recent weight record as identified by the automated screening system relative to malnutrition resulted in 56.52% sensitivity, 35.43% specificity, 13.68% positive predictive value, 81.82% negative predictive value. MST score 2 or greater was a stronger predictor of nutritional risk relative to PG-SGA classified malnutrition (70.59% sensitivity, 69.48% specificity, 32.14% positive predictive value, 92.02% negative predictive value).

Conclusions: Both the automated screening system and the MST fell short of the accepted professional standard for sensitivity (80%) or specificity (60%) when compared to the PG-SGA. However, although the MST remains a better predictor of malnutrition in this setting, uptake of this tool in the Oncology Day Care Unit remains challenging.

  1. Isenring E, Zabel R, Bannister M, Brown T, Findlay M, Kiss N, Loeliger J, Burgess C, Camilleri B, Davidson W, Hill J, Bauer J. Update of the evidence based guidelines for the nutritional management of patients receiving radiation therapy and/or chemotherapy. Nutrition and Dietetics 2013; DOI: 10.1111/1747-0080.12013