How to Improve Sleep Quality in Patients With Cancer-Related Fatigue

Abstract

Zhang et al. (2024) recently conducted a systematic review exploring the role of risk prediction models in managing cancer-related fatigue. Their study highlights the increasing reliance on predictive modelling to identify patients at higher risk, thereby enabling early interventions and personalised management strategies. By synthesising data from multiple sources, the authors emphasise how machine learning algorithms and statistical models can enhance clinical decision-making. This study found that anxiety, depression, age, chemotherapy status, sleep quality and pain are common factors related to cancer-related fatigue. These findings are both important and interesting, as they facilitate clinical decision-making by helping clinicians identify potential risk factors. Notably, the study identified sleep quality as a significant modifiable factor associated with cancer-related fatigue. Given that poor sleep quality is prevalent among cancer patients and can exacerbate fatigue, targeted interventions to improve sleep could play a crucial role in fatigue management. We commend the authors for their valuable contribution and suggest several strategies to enhance sleep quality in order to reduce the burden of cancer-related fatigue.

Firstly, for healthcare professionals, improving sleep quality in cancer patients requires a multi-faceted approach tailored to individual needs. It is essential to assess the underlying causes of poor sleep, which may include pain, anxiety, depression or the side effects of treatment. Healthcare providers should conduct thorough evaluations to identify these factors and address them accordingly. One of the most effective interventions is Cognitive Behavioural Therapy for Insomnia (CBT-I) (Ma et al. 2021; Johnson et al. 2016), which has shown promise in improving sleep quality in cancer patients. This evidence-based therapy helps patients change negative thoughts and behaviours surrounding sleep, promoting healthier sleep habits. Pharmacological approaches, such as low-dose antidepressants or melatonin, may also be considered for short-term relief, though they should be prescribed cautiously due to potential side effects. Additionally, healthcare professionals should educate patients on sleep hygiene practices, including maintaining a regular sleep schedule, creating a calm sleep environment and avoiding stimulants before bedtime. Relaxation techniques, such as mindfulness meditation, progressive muscle relaxation and deep breathing exercises, can also help reduce stress and improve sleep quality.

Secondly, improving sleep quality in cancer patients requires emotional, practical and social support. Emotional well-being plays a crucial role in sleep regulation, and family members can help by providing reassurance, reducing stress and fostering a positive environment. Open communication about fears and anxieties can alleviate emotional distress, which often contributes to sleep disturbances. Encouraging relaxation techniques such as meditation, deep breathing or bedtime storytelling can also create a soothing atmosphere conducive to better sleep. Practical support is equally important. Family members can assist in maintaining a consistent sleep routine, ensuring a comfortable sleeping environment and minimising nighttime disturbances. This includes adjusting lighting, reducing noise, and helping with relaxation techniques before bedtime. Additionally, social relationships outside the immediate family also play a significant role. Support groups and community networks provide cancer patients with emotional validation, reducing feelings of isolation and anxiety that can negatively impact sleep. Engaging in social activities during the day can also promote better sleep–wake cycles. By fostering emotional stability, offering practical support and encouraging social engagement, family members and social networks can significantly enhance the sleep quality and overall well-being of cancer patients.

Thirdly, artificial intelligence (AI) (Fiorillo et al. 2019; Ganglberger et al. 2023) can play a significant role in improving sleep quality for cancer patients by offering personalised, data-driven interventions. One of the most promising applications of AI is the development of predictive models that identify individuals at higher risk for sleep disturbances. By analysing patient data, such as medical history, treatment regimens and psychological factors, AI can predict sleep patterns and provide early intervention strategies. This proactive approach allows healthcare providers to tailor treatments to the specific needs of each patient. AI can also assist in monitoring sleep in real-time through wearable devices that track sleep quality, heart rate and movement. These devices collect valuable data, which AI algorithms can analyse to identify patterns and offer personalised recommendations for improving sleep hygiene. Additionally, AI-powered virtual assistants can guide patients through relaxation techniques such as mindfulness, deep breathing or guided imagery, all of which have been shown to promote better sleep. Furthermore, AI can help optimise the scheduling of treatments like chemotherapy or pain management, minimising their impact on sleep. By providing more accurate and individualised insights into how treatments affect sleep, AI can assist clinicians in adjusting care plans to improve overall sleep quality.

The authors declare no conflicts of interest.

The authors have nothing to report.