Prediction model to predict critical weight loss in patients with head and neck cancer during (chemo)radiotherapy

Jacqueline A.E. Langius, Jos Twisk, Martine Kampman, Patricia Doornaert, Mark H.H. Kramer, Peter J.M. Weijs, C. René Leemans

Research output: Contribution to journalArticleAcademicpeer-review

38 Citations (Scopus)
1 Downloads (Pure)


OBJECTIVES: Patients with head and neck cancer (HNC) frequently encounter weight loss with multiple negative outcomes as a consequence. Adequate treatment is best achieved by early identification of patients at risk for critical weight loss. The objective of this study was to detect predictive factors for critical weight loss in patients with HNC receiving (chemo)radiotherapy ((C)RT).

MATERIALS AND METHODS: In this cohort study, 910 patients with HNC were included receiving RT (±surgery/concurrent chemotherapy) with curative intent. Body weight was measured at the start and end of (C)RT. Logistic regression and classification and regression tree (CART) analyses were used to analyse predictive factors for critical weight loss (defined as >5%) during (C)RT. Possible predictors included gender, age, WHO performance status, tumour location, TNM classification, treatment modality, RT technique (three-dimensional conformal RT (3D-RT) vs intensity-modulated RT (IMRT)), total dose on the primary tumour and RT on the elective or macroscopic lymph nodes.

RESULTS: At the end of (C)RT, mean weight loss was 5.1±4.9%. Fifty percent of patients had critical weight loss during (C)RT. The main predictors for critical weight loss during (C)RT by both logistic and CART analyses were RT on the lymph nodes, higher RT dose on the primary tumour, receiving 3D-RT instead of IMRT, and younger age.

CONCLUSION: Critical weight loss during (C)RT was prevalent in half of HNC patients. To predict critical weight loss, a practical prediction tree for adequate nutritional advice was developed, including the risk factors RT to the neck, higher RT dose, 3D-RT, and younger age.

Original languageEnglish
Pages (from-to)91-96
JournalOral oncology
Issue numberJanuary
Publication statusPublished - Jan 2016


Dive into the research topics of 'Prediction model to predict critical weight loss in patients with head and neck cancer during (chemo)radiotherapy'. Together they form a unique fingerprint.

Cite this