Predicting weight loss in people with cancer - Nottingham ePrints
Predicting weight loss in people with cancer
Background: Malnutrition and the cachexia syndrome are common in people with cancer. A combination of reduced nutritional intake and abnormal metabolism can lead to physical and psychological disturbances which may impair quality of life and reduce survival. Improved patient outcomes are more likely if treatments and nutritional support can be initiated before significant weight loss has occurred.
Methods: A three phase, mixed methods study was undertaken. The primary aim was to gain a greater understanding of the complex factors that have an effect on, and can predict, weight loss in people with cancer. Phases I and II involved the psychometric testing of the Cancer Appetite and Symptom Questionnaire (CASQ). The instrument was tested for reliability among patients receiving radiotherapy (n=34). Predictive validity of the CASQ, using ROC curve analysis, was determined in patients with lung or upper GI cancer (n=185). Total CASQ scores (possible range, 0 to 48) were assessed at baseline, together with percentage weight change after 3 months. An exploratory qualitative study, following the principles of grounded theory, was conducted to explore the causes and influencing factors on weight change.
Results: When tested for reliability, the intra-class correlation coefficient of the CASQ was 0.80 (95% CI 0.68 to 0.92) and the difference between total CASQ scores at the two time points was -0.20 (95% CI -1.21 to 0.80). The optimum cut point of the total CASQ score to predict >5% weight loss was 31/32 (C statistic = 0.64; sensitivity 65%, specificity 62%, PPV 33%, NPV 86%), and to predict >10% weight loss was 29/30 (C statistic = 0.75; sensitivity 71%, specificity 66%, PPV 19%, NPV 95%). Exploratory modelling using multiple linear regression techniques suggested that BMI, MUST score, age and the CASQ items of enjoyment of food and pain, were most predictive of weight loss. Nine patients with lung or upper GI cancer and three carers participated in semi-structured interviews. Analysis of the data confirmed the vulnerability of this patient group in terms of symptom burden and nutritional risk. From the findings, a conceptual model that explains the influences on weight change in people with cancer was proposed.
Conclusions: Patients with lung and upper GI cancer are at high risk of malnutrition. Psychometric testing of the CASQ suggests that the instrument can predict weight loss in this patient group. Due to the low PPV, further refinements are needed before the instrument is able to be used in clinical practice. A conceptual model which explains the complex process of influences on weight change in people with cancer can improve knowledge and understanding, ultimately informing healthcare practice.
Porock, D.
Wilcock, A.