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Screening for malnutrition in lung cancer patients undergoing radiotherapy
Authors:Nicole Barthelemy  Sylvie Streel  Anne-Françoise Donneau  Philippe Coucke  Adelin Albert  Michèle Guillaume
Affiliation:1. Department of Radiotherapy, University Hospital of Liege, CHU Sart-Tilman, B35, 4000, Liege, Belgium
2. Department of Public Health, University of Liege, 4000, Liege, Belgium
Abstract:

Purpose

The assessment of nutritional problems is vital to support patients undergoing radiotherapy. Poor nutritional status may occur as a result of preexisting problems, older age, the cancer itself, or treatment side effects. Malnutrition impairs the outcome of the disease and affects patients. This prospective study aimed at developing two simple tools to screen malnutrition before radiotherapy and to assess, prior to treatment, the risk of malnutrition after radiotherapy.

Methods

Forty-seven lung cancer patients treated with curative intent were evaluated before radiotherapy and after completion of the treatment. To assess patient’s malnutrition, two well-known screening tools (PG-SGA and NRS-2002) were used, complemented by patient-specific characteristics, yielding a 59-item questionnaire. Malnutrition status was defined using Thoresen’s criteria. The two screening tools derived by multivariate analyses were validated by comparing anthropometric, biological, and nutritional variables between patients at risk of malnutrition and those who are not.

Results

Malnutrition detection prior to radiotherapy was based on the equation “MDS?=?5.88 ? 0.20?×?BMI?+?0.05?×?(percent weight loss over past 6 months),” while malnutrition prediction after radiotherapy was given by “MPS?=?3.67?+?0.98?×?(age ≥70) ? 0.12?×?BMI?+?1.20?×?edema.” Agreement between observed and estimated outcomes was quite high for the two scores (kappa coefficient 0.80 and 0.85, respectively).

Conclusions

The two assessment tools were found parsimonious and easy to use. Further studies are needed to validate them in larger lung cancer groups and in other cancer populations.
Keywords:
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