ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2025
Demographic, lifestyle, and clinical factors associated with muscle function in patients with head and neck cancer: a prospective cohort study.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThis study examined changes in muscle function over two years following diagnosis in patients with head and neck cancer (HNC), and identified demographic, lifestyle, and clinical factors associated with muscle function.
methodsData were derived from the NETherlands QUality of life and Biomedical cohort (NET-QUBIC), including patients with newly diagnosed HNC. Muscle function was assessed using the 30-second chair stand test (30s-CST) at baseline (pre-treatment), and 6, 12, and 24 months post-treatment. Linear mixed models (LMM) were used to evaluate changes in 30s-CST scores over time and to explore the influence of factors such as age, sex, education, body mass index, smoking, alcohol use, WHO performance status, tumor site, tumor stage, comorbidities, and treatment modality. Both main and interaction effects were examined.
resultsOf the 737 included patients, 622 completed at least one 30s-CST. Univariable LMM showed a significant decline in 30s-CST scores between baseline and 6 months. However, the multivariable LMM analysis showed no significant changes over time or interactions between time and the examined factors. Muscle function was significantly lower in patients with severe comorbidities, current smokers, non-drinkers, those with low education, or a WHO score of one. Each additional year of age was associated with a decrease in muscle function.
conclusionAlthough muscle function declined initially, this was not significant after adjusting for demographic, lifestyle, and clinical factors. Comorbidity, smoking, alcohol use, education, WHO score, and age were significantly associated with muscle function. These findings highlight the need to consider these factors when designing and implementing rehabilitation programs.
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