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. 2023 Apr 30;10(8):4892–4906. doi: 10.1002/nop2.1795

Symptom management in adult brain tumours: A literature review

Rong Zhang 1,2, Dong‐Mei Wang 2, Yong‐Li Liu 3, Man‐Li Tian 4, Ling Zhu 2, Jing Chen 2, Jun Zhang 1,✉
PMCID: PMC10333888  PMID: 37120840

Abstract

Aim

To review the literature related to symptom management, clinical significance and related theoretical framework systems in adult patients with brain tumours.

Background

As understanding of symptoms or symptom clusters and underlying biologic mechanisms has grown, it is apparent that symptom science is moving forward. Although some progress has been made in the symptom science of solid tumours such as breast and lung neoplasms, insufficient attention has been paid to symptom management for patients suffering from brain tumours. Further research is needed to achieve effective symptom management for these patients.

Design

A literature review with a systematic search of symptom management in adult brain tumours.

Methods

Electronic data bases were searched to obtain relevant published literature on symptom management in adults with brain tumours. This was then analysed and a synthesis of relevant findings is presented.

Findings

Four significant general themes relating to symptom management of brain tumours in adults were identified: (1) The potential theoretical foundation related to symptom management was revealed. (2) Widely accepted validated scales or questionnaires for the assessment of single symptoms or symptom clusters were recommended. (3) Several symptom clusters and the underlying biologic mechanisms have been reported. (4) Specific symptom interventions for adults with brain tumours were collected and classified as evidence‐based or insufficient evidence.

Conclusion

There are still many challenges in the effective management of symptoms in adults with brain tumours. The guiding role of theoretical frameworks or models related to symptom management should be utilized in future research. Using the concept of symptom clustering for research into symptoms found in patients with brain tumours, exploring common biological mechanisms for specific symptom clusters and making full use of modern big data resources to build a strong evidence base for an effective intervention or management program may inform the management of symptoms among these patients leading to better results.

No Patient or Public Contribution

This is a literature review.

Implications for Symptom Management

The ultimate goal is obviously not only improving the survival rate of patients with brain tumours, but also enhancing their quality of life. Several important findings from our review include the theoretical foundations, validated assessment tools, the assessment of symptom clusters and the underlying biologic mechanism, and the identification of the evidence base for symptom interventions. These are of relevance for managers, researchers and practitioners and may function as a reference to help the effective symptom management for adults with brain tumours.

Keywords: brain tumours, symptom clusters, symptom management

What does this paper contribute to the wider global clinical community?

  • Several important areas in the effective management of symptoms of brain tumour in adults have been reviewed.

  • The gaps in symptom management in adults with brain tumours have been highlighted, identifying areas for further research.

1. INTRODUCTION

Patients with tumours have to contend with both the effects of the tumour itself and those symptoms brought about by the therapeutic modalities used in its treatment. These symptoms can affect their functional status and can vary over the period of the disease in relation to stage and location of the disease and the therapy used to treat it. Effective symptom management has long been a top priority for healthcare professionals, patients and families. Symptom management is defined by the National Cancer Institute (NCI) as “Care given to help relieve the symptoms of a disease, such as cancer, and the side effects caused by treatment of the disease. Symptom management may help a person feel more comfortable, but it does not treat or cure the disease. It may involve taking certain medicines to relieve pain or nausea or using guided imagery or deep breathing exercises to reduce stress or anxiety” (NCI, 2022). Symptom management is an essential part of nursing care and is crucial to supporting patients. Patients with malignancy causing solid tumours normally experience multiple symptoms at one time rather than one symptom in isolation. Research into symptom management has changed direction to focus on symptom clusters and underlying biological mechanisms, and includes longitudinal studies that examine symptom pathways and the effects of interventions on patient outcomes (Brant et al., 2010).

Brain tumours make a significant contribution to global morbidity and mortality (Bray et al., 2018; Ostrom et al., 2020; Patel et al., 2019), involving a neoplasm of the intracranial components of the central nervous system, including the cerebral hemispheres, basal ganglia, hypothalamus, thalamus, brain stem, and cerebellum. And its account for 90% of all CNS cancers in adults (Zhang et al., 2012). Brain tumours are divided into primary or secondary. Primary tumours are those derived directly from brain tissue while secondary tumours are caused by metastases. Primary tumours are described as benign or malignant. Brain tumour patients generally present with a series of neurological and/or cognitive symptoms during treatment, recovery and even at the end of life, depending on the size and location of the lesion. The highest incidence of central nervous system (CNS) cancer is found in the East Asian region for both sexes, followed by Western Europe and South Asia (Patel et al., 2019; Wang, 2019). China, the USA and India have the highest number of incident cases (Patel et al., 2019; Wang, 2019). According to CBTRUS (Central Brain Tumour Registry of the United States), 70,000 new brain tumours are diagnosed each year causing 14,000 deaths in the United States (CBTRUS., 2021). In China, there were 652,024 new cases of brain tumour diagnosed in 2020 (NCCC, 2022). It ranks eighth in the number of cancer deaths in China and accounts for 2.2% of the total deaths (National Cancer Center in China, 2022). Brain tumour patients typically experience symptoms of various kinds with differences in frequency, intensity, quantity and quality which significantly affect individuals' quality of life (Rha et al., 2020). The tumours are challenging to treat because of the brain's delicate and complicated structure and function, leading to a high incidence of recurrence and a low long‐term survival rate (Cahill et al., 2012). As these tumours grow and invade the delicate tissues and spaces of the brain, patients will be likely to experience a number of symptoms including visual impairment, weakness of extremities, issues with speech and communication, loss of sensory perception, urinary and faecal incontinence, insomnia, pain, fatigue, cognitive impairment, distress and changes in behaviour and personality (Fox et al., 2007; Gleason et al., 2007; Tankumpuan et al., 2015; Wen & Kesari, 2008). Existing measures for management, including surgery, radiation therapy and chemotherapy, mainly target neurological symptoms by killing tumour cells and preventing further growth. In majority of the cases, clinicians may overlook symptoms such as fatigue, cognitive impairment, sleep disturbances and distress as their primary focus is on major neurological deficiencies (Fox et al., 2007). Professional nursing practice with its clear focus on identifying and alleviating symptoms experienced by patients has made a key contribution in this area. The nurses on the symptom management team perform a vital function in symptom assessment, the implementation of specialized symptom management strategies, team coordination and patient health education. Improving the survival rate of patients with brain tumours is obviously not the ultimate goal, and it is hoped that effective interventions can improve patients' quality of survival. The aim of this study is to conduct a literature review about the current status of symptom management, clinical significance and related theoretical framework systems in adult patients with brain tumours. Finally, we hope that this study is helpful to managers, researchers and practitioners, and, by functioning as a reference, can contribute to further research.

2. METHODS

2.1. Approach

The methodology for this literature review was based on the recommendations for Systematic Reviews guidelines, and reporting of the methods and findings were guided by the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) criteria. Therefore, the PRISMA‐2020‐checklist has been used during this literature review process. The preparatory phase included a literature search with data extracted to meet the review's aims, and the inclusion criteria were designated according to the following research questions: (1) What are the theories involved in guiding brain tumour symptom management? (2) What are the widely accepted instruments used in assessment of brain tumour symptoms? (3) What are the common symptom clusters and the underlying biologic mechanisms in adults with brain tumours? (4) What are the symptom interventions which have been shown to be effective in managing brain tumour symptoms?

2.2. Search strategy

Web of Science, PubMed, EMBASE and CINAHL were searched to obtain relevant published literature on symptom management in adults with brain tumours, using the following keywords: cancer, glioma, neoplasm, tumour, symptom, symptom cluster and symptom management. We searched for these terms in title/abstract fields from inception until September 2022. The search parameters included peer reviewed research studies using quantitative, qualitative or mixed methods published in English. Inclusion criteria included studies conducted with participants aged over 18 with brain tumours. Articles related to brain tumour symptoms or symptom cluster management including theoretical guidance, the exploration of underlying biological mechanisms of symptom clusters, symptom assessment and symptom interventions were also considered. Additionally, literature reviews and authoritative guidelines were also included. Title/abstract screening was performed by 2 reviewers working independently and irrelevant literature was excluded. Then, two others screened again by reading the full text independently. Any disagreement was resolved through arbitration with a third researcher.

3. FINDINGS

Four important general themes were identified for management of symptoms in adults suffering with brain tumours: (1) The potential theoretical foundation related to symptom management was identified. (2) Widely accepted validated scales or questionnaires for the assessment of single symptoms or symptom clusters were recommended. (3) Several symptom clusters in brain tumours and the underlying biologic mechanisms have been reported. (4) Specific symptom interventions for adults with brain tumours were collected and classified as evidence‐based or insufficient evidence. Relevant papers were analysed and a synthesis of the findings is presented.

3.1. Theoretical foundations related to symptom management

The main theoretical frameworks or conceptual models include the Theory of Symptom Management (TSM) (Larson et al., 1994), the Theory of Unpleasant Symptoms (TUS) (Lenz et al., 1997), the Symptom Experience Model (SEM) (Armstrong, 2003), the Symptom Experience in Time Model (SETM) (Henly et al., 2003), the Symptom Cluster in Children and Adolescents with Cancer (Xiao, 2010), the Dynamic Symptoms Model (DSM) (Brant et al., 2010, 2016), and the National Institutes of Health Symptom Science Model (NIH‐SSM) (Cashion & Grady, 2015). The application of these theoretical frameworks or models has some limitations. In spite of the introduction of symptom clusters into TSM theory this has not been developed to include the relationships between the different symptoms and no mention is made of suitable interventions for these clusters of symptoms (Dodd, Janson, et al., 2001; Feng & Lou, 2012). The TUS is a middle‐range theory useful for understanding the multidimensional nature of symptoms, and their interaction, synergy and complexity, but it does not specify physical symptoms and how to recognize the presence of a symptom cluster (Blakeman, 2019; Lenz et al., 1997). Lenz et al maintained that the TUS can be used to develop preventive interventions for improving the management of patient symptoms (Lenz et al., 1997), however, the intervention component is not further explained or described by them and is not included in the TUS model (Lee et al., 2017; Moore, 2022). According to the SEM, the interaction of symptoms can make the patient's symptom perception show a tendency to multiply, but the presentation of symptoms is influenced by patients' personal emotions which are subjective rather than objective (Armstrong, 2003). The SETM focuses more on longitudinal studies in symptom experience and symptom management, so it relies on the measurement of multiple time dimensions (Henly et al., 2003). Although the symptom cluster theory for children and adolescents with cancer can provide useful guidance for research into symptom clusters relating to pain, sleep and fatigue in children and adolescents, it is not possible to apply this to the adult and senior populations. The DSM is a new ideal symptom model developed by scientists at the National Institute of Nursing Research (NINR), an internal research program of the National Institutes of Health (NIH). This model is able to cope with complexity, co‐occurring and interacting symptoms, and longitudinal symptom changes over a time trajectory (Brant et al., 2016). But the application of the model requires further revision due to symptom complexity. The NIH‐SSM model is a product of the successful research program run by the NINR focusing on designing and implementing methods for looking at symptoms and symptom clusters (Cashion & Grady, 2015). Its focus is on developing and testing new symptom management interventions and so provides a useful blueprint to use when taking forward precise personalized clinical interventions so promoting the development of symptom management science.

3.1.1. Scientific model of symptoms (NIH‐SSM)

The NIH‐SSM, which begins with the presentation of a symptom, identifies characteristic symptom phenotypes, identifies and tests biomarkers, and ultimately develops clinical interventions in the research process (Cashion & Grady, 2015; Saligan, 2019). It provides the nursing science community with a clear framework for applying research into phenotypes and omics in the study of health interventions and shows the lead given by nursing science to the wider scientific community. This has the potential for developing specific and tailored interventions to manage and treat diseases resulting in health improvements. This model has currently led scientists in the wider community to discover knowledge in the areas of cancer‐related fatigue (CRF), irritable bowel syndrome (IBS) and related complex gastrointestinal (GI) symptoms, and traumatic brain injury (TBI) symptoms and cognitive changes and insomnia (Cashion & Grady, 2015). CRF which is shown in Figure 1 has been explored by the research team at the NINR intramural research program led by Dr. Leorey Saligan who used the NIH‐SSM to develop precise and personalized interventions to target CRF by focusing on the underlying biologic mechanisms (Cashion & Grady, 2015). They give a comprehensive account of the way various factors contribute to the experience of fatigue (high vs. low CRF based on FACT‐F score changes, changes in body weight and haemoglobin levels) to identify characterizing symptom phenotypes. Then biomarkers (genes, proteins such as apolipoprotein E and A1, neurotrophic factors) were identified and tested by Dr. Lukkahatai and Leorey Saligan's team (Lukkahatai et al., 2014; Saligan et al., 2016). Findings from their work investigating genomics and proteomics have enabled the development of a series of clinical interventions including N‐methyl‐D‐aspartate receptor antagonist which is currently being tested in a clinical trial at the NIH Clinical Centre. Nutritional supplements, dietary modifications, physical activity, energy conservation and cognitive behavioural strategies are other promising interventions. Despite the positive exploration of complex symptoms of neurological trauma based on the NIH‐SSM, symptoms in patients having brain tumours has not been studied very widely. Studies in this direction should be conducted in the future. As can be seen, the NIH‐SSM model shows tremendous potential in advancing the science of symptom management.

FIGURE 1.

FIGURE 1

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The National Institutes of Health Symptom Science Model (NIH‐SSM), in the case of cancer‐related fatigue (CRF).

3.2. Assessment and identification of brain tumour symptoms

The measurements used to assess and identify symptoms include patient self‐report outcomes (PROs) and objective‐reported outcomes from a healthcare professional. At present, there are widely accepted validated scales and questionnaires for the assessment of single symptoms. Common instruments for symptom assessment in adults with brain tumour are summarized in Table 1, and reliability/internal consistency of these tools were good. It is unusual for patients with cancers manifesting as solid tumours to report single symptoms but they commonly report a range of symptoms occurring concurrently and these related symptoms then form symptom clusters. Compared with single symptoms, symptom clusters lead to more detrimental effects for the patient due to their complicated and synergetic effects (Dodd, Miaskowski, & Paul, 2001; Gift et al., 2004). Instruments have evaluated many brain tumour‐specific symptoms including Functional Assessment of Cancer Therapy‐Brain (FACT‐Br) (Lien et al., 2011), the National Comprehensive Cancer Network & Functional Assessment of Cancer Therapy Brain Symptom Index (NFBrSI‐24) (Lai et al., 2014) and MD Anderson Symptom Inventory‐Brain Tumour (MDASI‐BT) (Armstrong et al., 2006). The assessment of the instrument FACT‐Br covers symptoms of an emotional and cognitive nature, but it exclusively concerns brain tumour‐specific quality of life (Lien et al., 2011). The NFBrSI‐24 is a novel tool for assessing symptoms in patients with advanced brain tumours (Lai et al., 2014), and the current evidence is insufficient to identify its functional role in symptom cluster recognition. The MDASI‐BT developed by T.S.Armstrong’ team (Armstrong et al., 2006) from the M.D. Anderson Cancer Center has been used to describe symptoms occurring throughout the pathway of the disease, identifying whether specific symptoms occur in clusters, and evaluates interventions designed for symptom management of brain tumours (Acquaye et al., 2019; Armstrong et al., 2016). It facilitates measurement of the symptom burden consisting of 22 symptoms and 6 items about interference with daily life, including six underlying constructs such as affective, cognitive, focal neurologic deficit, constitutional, generalized symptom and a gastrointestinal related factor. The internal consistency (reliability) of MDASI‐BT was 0.91 (Armstrong et al., 2006), and its psychometric validity and reliability has been validated in China, Denmark and Japan, including 468 patients with brain tumours (most commonly gliomas) (Piil et al., 2021; Pu et al., 2021; Tanaka et al., 2020). This tool can be employed both in clinical care and for screening and measurement where longitudinal evaluation is needed in clinical trials (Siegel & Armstrong, 2018).

TABLE 1.

Common assessment tools and interventions for symptom management in adults with brain tumours.

Symptom Assessment tools Type of scale, point‐Likert/No. of items Reference Reliability/internal consistency Evidence‐based interventions Interventions with insufficient evidence
Fatigue Visual‐analogue fatigue scale (VAS‐F) self‐reported, 11/13 Lee et al. (1991) α = 0.91–0.96

  • Exercise

  • ECTs

  • Yoga

  • Tai chi, qigong

  • Distraction: music, reading, meditating

  • Acupuncture
Multidimensional Fatigue Symptom Inventory (MFI) self‐reported, 5/20 Smets et al. (1995) α = 0.65–0.80
Fatigue Assessment Questionnaire (FAS) self‐reported, 4/20 Michielsen et al. (2003) α = 0.90–0.95
Cancer‐Related Fatigue Distress Scale (CRFDS) self‐reported, 11/20 Hinds et al. (2007) α = 0.91
Brief (Modified) Fatigue Inventory (MBFI) self‐reported, 11/9 Aynehchi et al. (2013) α = 0.82–0.97
The patient reported outcomes measurement information system (PROMIS) self‐reported, 6/Up to 20 Leung et al. (2016) α = 0.92–0.94
EORTC quality of Life module measuring cancer‐related fatigue (EORTC QLQ‐Fa12) self‐reported, 4/12 Weis et al. (2017) α = 0.79–0.90
Revised Piper Fatigue Scale (PFS‐R) self‐reported, 11/22 Jang et al. (2017) r = 0.87–0.89
Functional Assessment of Chronic Illness Therapy‐fatigue (FACIT‐F) self‐reported, 5/13 Machado et al. (2021)

r = 0.90

α = 0.93–0.95
Cognitive deficits Mini‐Mental State Examination (MMSE) self‐reported, 7/5 Werner et al. (1999)

r = 0.68

α = 0.71

  • Structured cognitive rehabilitation program

  • Virtual reality technology

  • Exercise
Montreal Cognitive Assessment (MoCA) objective‐reported, / Nasreddine et al. (2005)

r = 0.87

α = 0.64
Trail Making Test (TMT‐A/B) objective‐reported, / Bracken et al. (2019) α = 0.90–0.91
Neuropsychiatric Inventory (NPI) objective‐reported, 2/10 Resnick et al. (2022)

r = 0.68–0.95

α = 0.92–0.97
California Verbal Learning Test (CVLT) objective‐reported, 2–7/12 Woodard et al. (1999)

r = 0.85

α = 0.92
Hopkins Verbal Learning Test‐Revised (HVLT‐R) objective‐reported, 2/4 Shapiro et al. (1999) α = 0.90–0.96
Rey‐Osterrieth complex figure (ROCF) objective‐reported, 3/18 Ashendorf (2019)

r = 0.32–0.64

α = 0.74–0.96
Functional Assessment of Cancer Therapy‐Brain Cognitive Index (FACT‐Br‐CI) self‐reported, 5/9 Zarrella et al. (2021)

r = 0.68–0.78

α = 0.87
Functional Independence Measure‐Cognitive (FIM‐ COG) objective‐reported, 2/91 Kidd et al. (1995) N/A
Sleep–wake disturbances Insomnia Severity Index (ISI) self‐reported, 5/7 Bastien et al. (2001) α = 0.90–0.91

  • CBT‐I

  • MBSR

  • Exercise
Epworth Sleepiness Scale (ESS) self‐reported, 4/8 Beiske et al. (2009) α = 0.75–0.85
The patient reported outcomes measurement information system (PROMIS) self‐reported, 6/Up to 20 Leung et al. (2016) α = 0.92–0.94
Polysomnography (PSG) objective‐reported, / Murata et al. (2020)

r = 0.50–0.90

α = 0.91
Pittsburgh Insomnia Quality Index (PSQI) self‐reported, 4/9 Zhang et al. (2020) α = 0.82
Distress Cancer‐Related Fatigue Distress Scale (CRFDS) self‐reported, 11/20 Hinds et al. (2007) α = 0.91

  • Support groups

  • Support courses

  • CBT

  • Supportive psychotherapy

  • Psychoeducation

  • Acceptance and commitment therapy

  • Mindfulness

  • Exercise
NCCN distress thermometer (NCCN‐DT) self‐reported, 11/39 O'Donnell (2013) r = 0.67–0.88
The Problem List self‐reported, 2/42 NCCN, (2022b) N/A
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Abbreviations: EORTC, the European Organization for Research and Treatment of Cancer; NCCN, National Comprehensive Cancer Network.

3.3. Symptom clusters in brain tumours and the underlying biologic mechanisms

Since the concept of “symptom cluster” was described by Dr. Dodd (Dodd, Janson, et al., 2001), the implications of symptom management in adults suffering from brain tumours has been further explored, including the presence of symptom clusters, biological mechanisms and effective interventions. Symptom clusters in adults suffering from brain tumours have been reported, including “depression, fatigue, sleep disturbance, and cognitive impairment” cluster, “fatigue and sleep disturbance” cluster (Saligan, 2019), “motor dysfunction and weakness” cluster and “nausea and vomiting, diarrhea, seizures, and bladder control” cluster (Coomans et al., 2019). It is suggested by current models that symptoms such as insomnia and fatigue are the result of changes in melatonin production which in turn leads to alterations in the bodies molecular clock, resulting in aberrant neurotransmitter and cytokine production which in turn then produces these symptoms (Hrushesky et al., 2009; Scheff et al., 2010). Additionally, cytokines including interleukin (IL‐1 and IL‐6) also have an active role in the production of these symptoms (Ji et al., 2017). A recent study reported six symptom clusters during concurrent chemoradiotherapy (CCRT) including “negative emotion” and “neurocognitive” clusters before CCRT, “negative emotion and decreased vitality” and “gastrointestinal and decreased sensory” clusters at 2 ~ 3 weeks, and “body image and decreased vitality” and “gastrointestinal” clusters at 4 ~ 6 weeks (Kim & Byun, 2018). Additionally, another study from their team found that at three time points during CCRT these symptom clusters were correlated with ratios of lipid profile, representing lipid peroxidation (Kim, 2018). These findings may be useful indicators of symptoms in adult patients suffering from brain tumours. Significantly there is no general agreement on how to assess or identify symptom clusters or which instrument to use, and Kim S et al.'s finding of the biological mechanism of symptom clusters was also based on a small sample (only 48). Thus, the real‐world effect of these findings is currently limited. It is more difficult clinically, to detect, symptom clusters in brain tumour patients than in patients with other organ tumours. Although several studies have been done in the field of symptom clusters and the underlying biologic mechanisms in brain tumours, further studies to confirm these findings are needed, active challenges are faced and questions identified that need to be answered.

3.4. Specific symptom interventions

Survival without an acceptable quality of life is not an acceptable treatment outcome. Equal attention needs to be given to effective interventions which will improve both survival time and quality of life for brain tumour sufferers. The development of specific interventions based on underlying biologic mechanisms for effective symptom management remains to be explored. Therefore, the current symptomatic interventions for brain‐tumour patients' symptoms still consist of a comprehensive intervention for a single symptom, including pharmacological and nonpharmacological modalities. Nonpharmacological interventions for symptoms ignored by clinical professionals have been collected and classified, hoping to provide a reference for healthcare professionals.

3.4.1. Fatigue

Fatigue is defined as “a distressing, persistent, subjective sense of physical, emotional and/or cognitive tiredness or exhaustion that is not proportional to recent activity and interferes with usual functioning” (Lin et al., 2018). The prevalence of fatigue in brain tumour patients is higher than that in the general cancer population and has been reported as being between 50% and 100% (Xiao et al., 2014). The main clinical manifestations are weakness, fatigue, lethargy, inability to concentrate, physical discomfort and lack of motivation. Interventions for fatigue can be addressed in a variety of ways, but assessing pathogenic factors of fatigue is the core step. The National Comprehensive Cancer Network (NCCN) guidelines recommend that antiepileptic medication should be medically changed if it causes excessive fatigue (NCCN, 2022a), especially during the period of diagnosis, after surgical treatment, during radiotherapy or chemotherapy and in the rehabilitation phase after hospital discharge. Accurate assessment of patient fatigue factors can help with preventative measures for early intervention to avoid exacerbation of fatigue symptoms.

Fatigue interventions for the patients with brain tumours are based on those used for patients with other types of solid tumours. For example, exercise has been recommended for practice in fatigue from both society and guidelines networks (Bower et al., 2014; NCCN, 2022a; ONS, 2022). The sources of evidence for this recommendation are lacking studies demonstrating its effectiveness in patients with brain tumours. To date, there are no randomized controlled clinical trials of exercise in the adult neuro‐oncology population with fatigue; the only study is in patients with stable glioma by Gehring et al who found that exercise had a weak effect on fatigue when studying its effectiveness on cognitive performance (Gehring et al., 2018). It is important that patients have individualized exercise programs matched to their age, gender, type and stage of cancer, and personal fitness level (Sandler et al., 2021). Practical interventions recommended in the NCCN guidelines (NCCN, 2022a) include energy conservation techniques (ECTs) (Vatwani & Margonis, 2019), yoga (Lin et al., 2018), tai chi, qigong (Wayne et al., 2018), distraction, listening to music, reading or meditating (Gok et al., 2019). However, the efficacy of these strategies has only been validated in other solid tumours. A recent Cochrane systematic review showed that the available evidence was insufficient to make authoritative recommendations on possible effectiveness of any nonpharmacological interventions for fatigue in people suffering from brain tumours (Day et al., 2016). Acupuncture is of interest to a wide range of researchers and cancer patients as a complementary or alternative therapy, and the National Cancer Institute Division of Complementary and Alternative Medicine for Cancer held a symposium on “Acupuncture for Cancer Symptom Management” in June 16–17, 2016 (Zia et al., 2017). The effectiveness of acupuncture therapy for fatigue has been demonstrated in patients with other solid tumours, and the treatment of cancer pain and cancer‐related fatigue using acupuncture in adults has been clearly recommended in the NCCN Guidelines (NCCN, 2022a), however, this requires a trained therapist to treat the patient. Similarly, the effectiveness of this promising intervention needs to be further validated in patients with brain tumours.

3.4.2. Cognitive deficits

Patients suffering from brain tumours frequently suffer from a variety of cognitive deficits, including dysfunction in the domains of information processing, attention span, memory, executive functions, visuospatial and constructional abilities, intellect, sensory perceptual functions and language, this is especially marked among those having gliomas with a wide range of prevalence reported (29% to 90%) (Maschio et al., 2015; Mukand et al., 2001; van Loon et al., 2015).There is only one new insight regarding nonpharmacologic intervention that being a structured cognitive rehabilitation programme. This intervention which has been recommended to help patients with cognitive impairment following treatment for brain tumours includes explicit instruction in cognitive compensatory strategies and the use of various devices to assist with the functions of daily living (Bergo et al., 2016; Koekkoek et al., 2023; Parsons & Dietrich, 2021). Cognitive function is thought to be improved by Exercise (Cormie et al., 2015; Gehring et al., 2020), but there is limited evidence for the use of this intervention to improve cognitive dysfunction in patients suffering from brain tumours. Nonetheless, a series of methods were inserted into “exercise your brain” cards to alleviate some symptoms of cognitive deficits by the National Brain Tumour Society, including using puzzles, games, playing an instrument, and reading to improve memory and thinking abilities see “www.CancerSupportCommunity.org/brain” for more information (NBTS, 2022). It is important to note that the use of virtual reality to allow patients with brain tumours to experience a totally relaxing situation as part of a cognitive rehabilitation program has potential in reversing or at least improving cognitive impairment (Amidei, 2018; Faria et al., 2016; Leggiero et al., 2020; Yang et al., 2014).

3.4.3. Sleep–wake disturbances

Sleep–wake disturbances (both insomnia and hypersomnia) are defined by the American Academy of Sleep Medicine as “sleep alterations in patients with impaired functioning of normal daytime activities that can be consciously or unconsciously perceived” (Sateia, 2014). It is one of the most severe and common symptoms reported by patients suffering from primary brain‐tumours, especially when undergoing radiation therapy (Gustafsson et al., 2006; Mulrooney et al., 2008; Powell et al., 2011). Sleep wake disturbances can also be found alongside other symptoms such as fatigue, depression and cognitive impairment to form a symptom cluster (Armstrong et al., 2017; Hu et al., 2020; Mulrooney et al., 2008; Saligan, 2019). Its severity should be routinely assessed as it is related to disease progression and may significantly affect patients' daily living function, quality of life, and general health (Yavas et al., 2012). The disordered physiology associated with sleep–wake rhythm disturbance in patients having and receiving treatments for brain tumours has been known for many years (Chen et al., 2013; Faithfull & Brada, 1998). However, this has not been studied to the same degree as in other cancers in relationship to how interventions function across the disease progression pathway. From the existing evidence it can be concluded that interventions such as cognitive behavioural therapy insomnia (CBT‐I), mindfulness‐based stress reduction (MBSR) and exercise that are useful for improving sleep and reducing other associated symptoms in patients with other solid tumours should be the subject of further studies to evaluate their utility for patients suffering from brain tumours (Armstrong et al., 2017; Bower et al., 2015; Chiu et al., 2014). At the present time these interventions can only be used as alternative therapies for management of sleep–wake disturbances in adults with brain tumours.

3.4.4. Distress

Distress has been defined as a “multifactorial unpleasant experience of a psychological (cognitive, behavioural, emotional), social, spiritual or physical nature that may interfere with the ability to cope effectively with cancer, its physical symptoms, and its treatments” (NCCN, 2022b), which has also been termed a “psychological burden” in the literature (Teke et al., 2016). The prevalence of distress was has been reported as 35% ~ 74% in brain tumour patients (Randazzo et al., 2017; Teke et al., 2016), while it is estimated that 15% ~ 20% of patients (especially the patients with malignant glioma) will go on to suffer from a serious depressive disorder during the first year after diagnosis (Goebel et al., 2011; Rooney et al., 2011).

Online or face‐to‐face support groups and support courses designed to decrease distress have recently been proved clinically meaningful for patients suffering from brain tumours (Huber et al., 2018; Ownsworth et al., 2015). Brain tumour support groups provide different ways to help old or young patients to benefit by managing distress. Other interventions that have already been demonstrated to be evidence‐based in other groups of patients include cognitive‐behavioural therapy, supportive psychotherapy, psychoeducation (Li et al., 2017), acceptance and commitment therapy (Ruiz, 2010), mindfulness (Bohlmeijer et al., 2010), and prescriptive exercise (Mustian et al., 2016) are all potential ways to relieve the symptom of distress or depression in patients with brain tumours. In assessing the effectiveness of online or face‐to‐face support groups and support courses, it is important to remember that during the follow‐up process, patients with brain tumours were faced with the problem of tumour recurrence and functional decline, so caution is needed in interpreting the effectiveness of these measures. Further research will be needed with a more intensive program to validate their effectiveness in this target population.

4. DISCUSSION

Patients suffering from brain tumour face the fact that they have a fatal disease with a limited prognosis and many unpleasant symptoms, this is particularly so for patients with gliomas which have a high degree of malignancy. It is necessary to assess symptoms frequently and manage them proactively throughout all stages of the illness. A truly patient and family‐centred symptom management system needs to be comprehensive, continuous, structured and responsive. Symptom management research needs to consider the aspects of symptom interactions, symptom clusters, assessment and effective interventions as essential components of ongoing studies. This study has reviewed the literature on the current status of symptom management, clinical significance and related theoretical framework systems in adult brain tumours. Several theoretical frameworks or models have been briefly introduced and we have highlighted the potential clinical significance of the NIH‐SSM model in symptom science. Models and theories resulting in symptom reduction and improved patient outcomes are seen to include self‐care, self‐efficacy, nursing and other healthcare interventions (Henly et al., 2003). Although the abovementioned models and theories contain elements that support the new paradigm in symptom management research, there is a need for more comprehensive models and theories to explore symptom clusters, the experience of symptoms over time and the effects on patient outcomes of symptom management interventions. The NIH‐SSM commences with the identification of a symptom, or symptom cluster then describes the sequence for an investigative in symptom science research. It progresses to guide the design and implementation of study methods for characterizing phenotypes, identifying and testing biomarkers. By focusing on developing and testing new symptom management interventions it provides a valuable model that can be applied and used by bringing forward individualized and precise clinical interventions. This model is well positioned to catch up with the age of precision medicine, which has been defined by the NCI as “a form of medicine that uses information about a person's genes, proteins, and environment to prevent, diagnose, and treat disease.” (NCI, 2021). The use of the concept of symptom clustering in symptom research and understanding the underlying mechanisms in patients suffering from brain tumours will improve the effectiveness of symptom management and lead to the development of novel strategies to manage patient symptoms. However, we currently have only limited understanding of the pathobiology of clustering of symptoms in brain tumours. Much of our understanding of the underlying biological mechanisms of symptom clusters comes from studies of other solid tumours especially lung and breast cancer. For example, the biomarker “IL‐6, C‐Reactive Protein and Tumor Necrosis Factor‐α” were proved to be significantly correlated with the symptom cluster “Fatigue‐ Sleep‐wake disturbances” (Kwekkeboom et al., 2018; Laird et al., 2011; Wei, 2017). Obviously, identifying symptom clusters and exploring their common biological mechanisms in brain tumours is still a long way off.

If we are to improve the survival experience for patients with brain tumours, we not only need to grasp the underlying biological mechanisms but also recognize and intervene when patients are experiencing symptoms. Improved patient outcomes is the ultimate goal of symptom management research. While most patients in the present study struggle with their symptoms described in the literature as fatigue, cognitive deficits, sleep‐week disturbance and distress, these are often ignored and left clinically untreated. Brain tumour patients' mood, functional ability and quality of life are all negatively affected by unrelieved symptoms (Miaskowski et al., 2004). Symptomatic patients should be identified and have routine symptom monitoring and management. Using the assessment instruments shown in Table 1 might also allow researchers and clinicians to better detect and manage symptoms, but the MDASI‐BT is a patient reported outcome multi‐symptom assessment tool developed specifically for symptoms or symptom clusters that occur in patients with primary brain tumours. Building on the core MDASI assessment and using the literature as a guide, symptoms specific to brain tumour patients have been identified and content validated by a panel of experts from healthcare professionals, patients and family members (Armstrong et al., 2005). Using this disease‐specific instrument for such a complex population helps in providing best care practices.

Developing evidence based interventions for patients surviving brain tumours provides many challenges. Interventions for symptoms in patients suffering from brain tumours make use of significant amounts of work done in other areas of solid tumour care. Nonetheless, researchers are making unremitting explorations for effective interventions. As seen from the studies presented here, exercise is the intervention having the most potential in brain tumour patients with the symptoms or symptom clusters mentioned above, although more evidence is still needed to prove its effectiveness in this population. In the face of the complex physiological and psychological problems commonly found in these patients, high‐level tailored prescriptions for exercise and its monitoring are necessary. Therefore, it is very important that exercise prescription employs an individualized tailored approach which takes into account the ever changing nature of symptoms and the patient's unique situation, (e.g., stage of diseases, functional capacity and treatment toxicity) which could maximize safety and patient benefits (Hayes et al., 2019; Sandler et al., 2020; Spence et al., 2020). The realization and continuous improvement of smart healthcare and service systems can not only improve the efficiency of medical staff in symptom management but also improve patients' experience of medical services. Smart healthcare is built on various information‐technological modalities including Internet of Things, mobile Internet, 5G, cloud computing, artificial intelligence and big data together with biotechnology (Tian, 2019). Virtual reality which is a product of this era along with technology seems to be an ideal delivery approach to alleviate some of the psychological symptoms patients experience. In the current era researchers in symptom science must capitalize on the reality of “Big Data”, identify and utilize its capacity to gather, store and share symptoms information to assist in finding the most effective interventions to help patients with brain tumours. Mobile‐health and patient‐facing technologies, for example smartphone apps and telerehabilitation show great potential for this population. Additionally, complementary or alternative therapy such as acupuncture, yoga and mindfulness‐based stress reduction will expand research on symptom interventions or treatment strategies for patients with brain tumours. There are some limited interventions to ameliorate or reduce symptoms associated with brain tumours but these are lacking in scope and efficiency. Continued development of focused tailored treatment modalities that promote a good quality of life for survivors, while posing a significant challenges also presents the greatest opportunity to have a lasting effect on our patients’ lives.

Even though research focused on single symptoms needs to continue, the science of symptom management has thus evolved from a focus on separate symptoms to the exploration of symptom clusters. Tumour patients rarely present with a single symptom, and the symptom cluster concept suggests that co‐occurring symptoms may be related and interact with each other and group together in a systematic way (Aktas, 2013; Dodd, Janson, et al., 2001). Although the study and understanding of symptom cluster in brain tumour patients is still limited, the future direction of symptom science should be on how to manage symptom clusters as a whole instead of focusing on separate symptoms. Firstly, the selection of a sound theoretical framework or model can provide scientific guidance for the management of symptom clusters. Second, the method of symptom cluster identification needs to be determined, and this has been analysed in detail by Xiao's team (Xiao et al., 2014). Reliable screening measurement can allow researchers and clinicians to better detect the clusters. Third, a greater awareness of the common biological mechanisms involved in symptom clusters can inform the development of effective interventions. Emerging evidence indicates that incorporating proteomics, metabolomics and transcriptomics into symptom science research are important ways to advance this area as these provide additional information to guide the identification of the pathways involved in the clustering of symptoms (Mathew et al., 2021). Therefore, targeting a single intervention to manage multiple symptoms within a cluster with a common mechanism becomes a possibility. Additionally, the use of methods utilizing big data and multi‐centre cooperation to collect, store, detect and share symptom cluster and biomarker information on brain tumour patients is also one of the potential symptom cluster management methods. In this era of precision health, nursing science should be focused on biopsychosocial research to move the field of symptom science forward and foster the delivery of high‐quality care to patients with brain tumour.

There are several limitations to this report. Common tools for symptom assessment in adults with brain tumours have been listed, but the advantages and disadvantages of these different tools have not been given an exhaustive overview. Although drug treatments are an indispensable part of effective symptoms management, the present paper has only reviewed a series of nonpharmacological interventions for symptoms including fatigue, cognitive impairment, sleep disturbances and distress which are frequently ignored in routine clinical practice. What we have to acknowledge is that these interventions have not linked the timing of the interventions with the staging of patients' metastatic brain tumours.

5. CONCLUSION

Currently, many challenges in the effective symptom management of patients with brain tumour still remain, but both patients and family caregivers will experience substantial gains as a result of our efforts. The guiding role of theoretical frameworks or models related to symptom management should be valued in future research. Using the paradigm of symptom clustering in symptom research in patients with brain tumours, exploring common biological mechanisms for specific symptom clusters, making full use of modern big data resources to ensure that interventions and management systems are both effective and firmly evidence based will result in the development of better symptom management interventions for these patients.

6. IMPLICATIONS FOR SYMPTOM MANAGEMENT

In the present study, most brain tumour patients struggle with their symptoms and many clinicians face the complexity of dealing with physiological and psychological impairments found in these patients, especially the symptoms which have often been ignored. The current study presents 4 themes including the importance of using a potential theoretical foundation, the presence of widely accepted validated assessment scales, the importance of identifying symptom clusters rather than simply focusing on individual symptoms and an assessment of the evidence base for various specific symptom interventions for symptom management in adult brain tumours. At same time, the gaps in symptom management for adults with brain tumours have been highlighted. We hope that this study is helpful to managers, researchers and practitioners and, by functioning as a reference, can contribute to further research.

AUTHOR CONTRIBUTIONS

JZ and RZ designed the study and formulated inclusion criteria. RZ and D‐mW searched and identified eligible articles. Y‐lL and M‐lT extracted important information. RZ, Y‐lL, LZ contributed to discussion of the findings. RZ, JC and JZ developed the final manuscript. All the authors have read and approved the manuscript.

FUNDING INFORMATION

This work was supported (in part) by the Natural Science Foundation of Hubei Province in China (Grant No. 2018CFB598). The research funds have mainly been used to provide the labour expenses of researchers and the expenses for the publication of articles.

CONFLICT OF INTEREST STATEMENT

All the authors have declared no financial conflicts of interest.

ETHICAL CONSIDERATIONS

Because this study was a literature review, ethical review was not required.

7.

ACKNOWLEDGEMENTS

We express our gratitude to Jean Glover from Tianjin Golden Framework Consulting for English editing.

Zhang, R. , Wang, D.‐M. , Liu, Y.‐L. , Tian, M.‐L. , Zhu, L. , Chen, J. , & Zhang, J. (2023). Symptom management in adult brain tumours: A literature review. Nursing Open, 10, 4892–4906. 10.1002/nop2.1795

Rong Zhang, Dong‐Mei Wang and Yong‐Li Liu contributed equally to this work and share first authorship.

7.1. DATA AVAILABILITY STATEMENT

The supporting data can be accessed from the corresponding author on reasonable request.

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