Cancer-related fatigue in adolescents and young adults: A systematic review of the literature

Critical Reviews in Oncology / Hematology 118 (2017) 63–69

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Review article

Cancer-related fatigue in adolescents and young adults: A systematic review of the literature

MARK

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E. Nowea, , Y. Stöbel-Richterb, A. Sendera, K. Leuteritza, M. Friedricha, K. Geuea a b

Universitätsklinikum Leipzig, Medical Psychology and Medical Sociology, Philipp-Rosenthal-Str. 55, 04103 Leipzig, Germany University of Zittau/Goerlitz, Faculty of Management and Cultural Sciences, P. O. Box 30 06 48, Goerlitz 02811, Germany

A R T I C L E I N F O

A B S T R A C T

Keywords: Adolescents Young adults Cancer Cancer related fatigue Systematic review

Adolescents and young adults with cancer (AYA) represent a specific age cohort dealing with the disease in a stage of life characterized by development, upheavals, and establishment. The aim of this study was to point out the state of research on how AYA are affected by cancer-related fatigue (CRF). Results: Twelve articles were included. CRF was found to be higher in AYA than in either of the comparison groups, healthy peers and older cancer patients. Most included studies did not measure CRF with multidimensional, fatigue-specific instruments. Conclusion: We found a gap in research concerning CRF in AYA. The existing findings suggest that CRF is a significant issue for AYA cancer patients. However, less is known about the prevalence, severity, and impact of CRF in AYA, and their treatment. This should be considered in future research, and risk and prevention factors should be ascertained. Multidimensional and fatigue-specific measuring tools should be used to do this.

1. Introduction The cohort of Adolescents and Young Adults with cancer (AYA) is strongly underrepresented in cancer research (Reuben, 2017; National Cancer Institute, 2006) although the incidence of cancer in AYA in Europe, the USA, and Canada has increased over the last decades (Midtgaard and Quist, 2008). As the overall-survival rate in this cohort is about 80% (Borchmann et al., 2017), the number of cancer survivors who were first diagnosed during their adolescence or young adulthood is continually increasing. While the age definition of AYA is not consistent in research, the National Cancer Institute (NCI) has adopted the age range of 15–39 years (National Cancer Institute, 2006). Even though AYA are an inhomogeneous cohort with many different cancer entities, stages, and treatment protocols, they must cope with the same twofold burden: Adolescence and young adulthood are characterized by developmental challenges such as becoming financially and socially independent, moving out of the parental home, establishing a partnership, and starting a family and career (Warner et al., 2016; Ramphal et al., 2011; Zebrack, 2011). In addition to these tasks, AYA must deal with their illness, diagnostics, cancer treatment, follow up visits, and survivorship concerns as well as body image disruptions, sexual problems, obesity, and secondary malignancies (Cooke et al., 2011; Eiser et al., 2007; Thomas et al., 2006). One of the most common symptoms reported by both adults and

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children with cancer is cancer-related fatigue (CRF) (Barsevick et al., 2013). CRF affects almost all cancer patients, regardless of the specifics of their diagnosis (Bower et al., 2014; Brown and Kroenke, 2009). The National Comprehensive Cancer Network (NCCN) defined CRF as ‘a distressing, persistent, subjective sense of physical, emotional and/or cognitive tiredness or exhaustion related to cancer or cancer treatment that is not proportional to recent activity and interferes with usual functioning’ (Berger et al., 2010). Nowadays CRF is regarded as a multidimensional construct that encompasses physical, emotional, and cognitive fatigue (deRaaf et al., 2013; Scott et al., 2011). Both cancer and cancer treatment seem to influence fatigue (Brown and Kroenke, 2009; Bower et al., 2000). CRF has been found in patients before, during, and after treatment as well as years after complete remission (Bower et al., 2000). However, the state of knowledge about the prevalence of CRF specifically in the AYA cohort lags behind that for other groups (Barsevick et al., 2013; Curt et al., 2000). Many studies have focused on cancer-related fatigue in older patients (> 39 years) as several previous reviews have pointed out (Campos et al., 2011; Oh and Seo, 2011). Other reviews have shown that research on cancer-related fatigue is also more comprehensive in younger adolescents (< 18 years) (Erickson, 2004; Spathis et al., 2015). As early as 2004, Erickson found 15 studies dealing with CRF in younger adolescents (12–19 years) (Erickson, 2004), and Spathis et al. included 27 studies in their 2015 review that investigated CRF in young

Corresponding author. E-mail address: [email protected] (E. Nowe).

http://dx.doi.org/10.1016/j.critrevonc.2017.08.004 Received 27 September 2016; Received in revised form 3 August 2017; Accepted 18 August 2017 1040-8428/ © 2017 Elsevier B.V. All rights reserved.

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Thus, the highest possible quality score of an included study was 6 points and the lowest was 0 points.

adolescent cancer patients and long-term cancer survivors (13–24 years) (Spathis et al., 2015). However, to our knowledge, so far, no reviews have been done on CRF in AYA specifically in the age-range defined by the National Cancer Institute (National Cancer Institute, 2006). This is the case in spite of the fact that former research has recognized cancer patients 15–39 years old as a specific age cohort deeming investigation independent of other age groups (National Cancer Institute, 2006). The aims of this review were to show the current state of research on cancer-related fatigue in adolescents and young adults diagnosed with cancer. The analysis was based on the following questions:

3. Results Out of 2128 search results, 102 articles were preselected based on their title and abstract for full-text screening. In total, 12 studies were included in this review. Fig. 1 illustrates the selection strategy. 3.1. Characteristics of the 12 included studies Table 3 gives an overview of the characteristics of the articles included in the review: Seven studies were conducted in the USA (Erickson et al., 2014; Rabin et al., 2011; Rosenberg et al., 2013; Sanford et al., 2014; Smith et al., 2013a,b) while the other included studies were executed in Europe (Bifulco et al., 2012; Geue et al., 2014; Hauken et al., 2015; Heutte et al., 2009; Singer et al., 2011; Weiss et al., 2013) (Table 3). Six articles reported on AYA with all cancer entities (Erickson et al., 2014; Rabin et al., 2011; Geue et al., 2014; Hauken et al., 2015; Singer et al., 2011; Weiss et al., 2013). Regarding to the different cancer sites, the included studies reported on patients treated with different types of cancer therapy (e.g. surgery, chemotherapy, radiotherapy) (Table 3). Two studies (Smith et al., 2013a,b) used the same raw data derived from the AYA Hope Study (Harlan et al., 2011). The sample size of the included studies ranged from n = 14 to n = 484. Two of the selected studies only investigated cancer-related fatigue in women (Rosenberg et al., 2013; Bifulco et al., 2012). Seven studies had longitudinal designs (Erickson et al., 2014; Rabin et al., 2011; Sanford et al., 2014; Hauken et al., 2015; Heutte et al., 2009; Singer et al., 2011; Weiss et al., 2013) and three of those were interventional studies (Rabin et al., 2011; Hauken et al., 2015; Weiss et al., 2013). The time of enrolment differed greatly between the reviewed studies (Table 3). Four studies compared AYA to older cancer patients (Sanford et al., 2014; Bifulco et al., 2012; Heutte et al., 2009; Singer et al., 2011), and another three used comparisons with age-matched reference samples from the general population (Smith et al., 2013a; Geue et al., 2014; Hauken et al., 2015). Six of the 12 included studies got a quality score ≥4. The other 6 included studies used 1-Item-Scales to assess CRF (n = 2) or included too few participants (n = 4) (Table 3). The most commonly used instrument for measuring fatigue was the European Organisation for Research and Treatment of Cancer Quality of life Questionnaire Core 30 (EORTC-QLQ 30) (Bifulco et al., 2012; Geue et al., 2014; Hauken et al., 2015; Heutte et al., 2009; Singer et al., 2011; Weiss et al., 2013). Two studies used 1-item fatigue scales (Rosenberg et al., 2013; Sanford et al., 2014) and two studies used the Multidimensional Fatigue Inventory (MFI-20) (Heutte et al., 2009; Singer et al., 2011). All of the instruments used are described in Table 2.

• What is the prevalence and severity of CRF in AYA? • Which factors are associated with CRF in AYA? • Which interventions exist to effectively alleviate CRF symptoms in AYA?

2. Methods The databases PubMed, Web of Science, CINAHL, and PsychInfo were searched for articles in English or German published between January 1990 and September 2015. The publishing date filter was chosen based on the fact that most of the research that has been done on AYA has taken place in that time frame (National Cancer Institute, 2006). Thus, that parameter seemed most likely to yield appraisable results. The search string was applied to titles and abstracts. In addition to the word-for-word search, the Medical Subject Headings (MeSH) “fatigue”, “adolescent”, “young adult”, “medical oncology”, and “neoplasms” were integrated in the PubMed search. The terms used are shown in detail in Table 1. After removing duplicates, the titles and abstracts of the identified literature were first screened independently by two reviewers. Articles were then included if the studies they described:

• used quantitative methods, • focused on cancer patients diagnosed between 15 and 39 years of age, and • measured cancer-related fatigue. In the second screening, the full-text articles were assessed by two authors working together. The inclusion criteria were as stated above. Additionally, hand searches were carried out for the references of the assessed full-text articles (n = 102 screened; one article included (Singer et al., 2011)). To assess the quality of the included studies, we used a quality score computed as follows:

• Used scale:

• Number of participants:

1-Item-Scale (0 points) Scale with more than 1 item (2 points) Multidimensional fatigue instrument (4 points) n < 50 (0 points)

3.2. Prevalence of CRF in AYA Of the 12 included studies, one reported on the prevalence of CRF in all AYA cancer patients aged 20–39 years old, regardless of cancer site (Singer et al., 2011). Singer et al. (Singer et al., 2011) used the MFI to assess CRF. At the beginning of treatment (t1), the authors found a prevalence of CRF of 53.1% (95% CI: 43.1–63.1%) for the participants. This rate was seen to have increased at hospital discharge (t2) (Prevalence of CRF = 55.1%; p < 0.05) (Singer et al., 2011).

50 < n < 100 (1 point) n > 100 (2 points)

Table 1 Search terms. #1 AND #2 AND #3

3.3. CRF in AYA compared to healthy peers and older cancer patients AYA reported significantly higher fatigue scores compared with age matched healthy reference samples in two studies, one that reported on all cancer sites in patients having completed acute treatment (Geue et al., 2014), and another that only included patients with haematological cancer and sarcoma 6–14 months after their diagnoses (Smith et al., 2013a). Although the Hauken et al. (Hauken et al., 2015) results

fatigue OR CRF OR weariness OR weary OR tired* adoles* OR young adult OR young adults OR youth OR AYA OR teen* OR child* OR paediatric OR CCS oncolog* OR cancer OR neoplasm* OR tumour OR tumour OR malign*

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Fig. 1. Flow diagram illustrating the selection strategy for the included studies.

Table 2 Instruments for assessing fatigue of the included studies.

Multidimensional

Instrument

Items

Recall Period

Subscale(s) (No. of Items) and Response Scale

Multidimensional Fatigue Inventory

20

Previous days

Pediatric Quality of Life Inventory fatigue modulea (PedsQL) (Varni and Limbers (2008)

18

Right now

General (4), Physical (4) and Mental Fatigue, Reduced Activity (4), Reduced Motivation (4) 7-point Likert scale (“yes, that is true” to “no, that is not true”) General (6), Sleep/Rest (6) and Cognitive (6) Fatigue 5-point Likert scale (“Never” to “Almost always”)

Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) Minton and Stone (2009)

30

Past week

Profile of Mood States (POMS) Curran et al. (1995)

37

Past week

Patient-Reported Outcomes Measurement Information System (PROMIS) Garcia et al., (2007)

-b

Past 7 days

M.D. Anderson Symptom Inventory (MDASI) Cleeland et al., (2000) 1-Item-Fatigue Scale Rosenberg et al. (2013)

1

Past 24 h

1

Right now

(MFI-20) (Smets et al. (1995)

Subscale, several items

1-Item-Scales

a b

Fatigue Subscale (3) 4-point Likert scale (“Not at all” to “Very much”) Fatigue Subscale (7) 5-point Likert scale (“Not at all” to “Extremely”) Fatigue Short Forms (7) 5-point Likert scale (“Never” to “Always”)

Validated for 18–25 years of age. Contains several short forms for different variables.

65

11-point Likert scale (“Not present” to “As bad as you can imagine”) 4-point Likert scale (“Not at all” to “Extremely”)

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There is a paucity of research on CRF in AYA. As such, we were able to identify 12 relevant studies that met the inclusion criteria for this review, whereas only 6 of the 12 studies measured CRF with several items and were based on a sufficient sample sizes. The few included studies focused on very different problems. We reviewed studies that drew comparisons with other cohorts as well as articles describing special interventions and their association with cancer-relation fatigue.

should be interpreted carefully in light of the small sample size of the study (quality score = 2), it is notable that they also found AYA to be more burdened by CRF than other age groups. The results of comparisons between AYA and older cancer patients are not consistent. Using the MFI, Heutte et al. observed lower fatigue scores in Hodgkin lymphoma patients aged 15–29 years compared to those aged 30–49 and compared to cancer patients between 50 and 70 years of age using the MFI at the end of acute treatment (Heutte et al., 2009). Singer et al. showed that the mean MFI scores of CRF did not differ between younger and older cancer patients (20–39 versus 40–59 and 20–39 versus > 59 years) being on acute treatment (Singer et al., 2011). Indeed, prevalence rates of CRF in AYA were found to be significantly higher (OR = 4.0; p < 0.001) than in participants > 60 (Singer et al., 2011). Studies that used the EORTC QLQ-C30 have also found the fatigue scores of young adult gynaecological cancer patients to be significantly higher than those of older gynaecological cancer patients (46–65 years) 1–4 years after treatment completion (Bifulco et al., 2012). The Sanford et al. study, which had a quality score of 2 due to the 1-Item-Scale it used, found younger breast cancer patients to be more burdened by fatigue than their older counterparts (Sanford et al., 2014).

4.1. Discussion of main findings Although only one study that used a fatigue-specific measurement focused on the prevalence of CRF in AYA, the CRF prevalence rates of over 50% they found in this age group are an indication of the importance of this issue. This also becomes apparent when regarding CRF in AYA in comparison with healthy reference cohorts: CRF was found to be more severe and more common in AYA than in older cancer patients and healthy reference cohorts (Sanford et al., 2014; Smith et al., 2013a; Bifulco et al., 2012; Geue et al., 2014; Hauken et al., 2015). Probable explanations for cancer related fatigue are the cancer itself as well as treatment side effects and cancer symptoms such as poor sleep and depression (Barsevick et al., 2013). In light of these factors, it is not surprising that AYA reported higher fatigue scores than their healthy peers. Why do AYA report higher fatigue scores on average than older cancer patients do (despite having lower rates of comorbidity)? In contrast to their older counterparts, AYA must deal simultaneously with their illness and with watershed emotional, social, and vocational developments crucial to establishing their adult lives (Ramphal et al., 2011; Zebrack, 2011; Thomas et al., 2006). This heightened burden may increase CRF. Furthermore, possible gaps in services for meeting AYA patients’ psychosocial needs (Cooke et al., 2011; Zebrack, 2009) may aggravate symptoms of CRF. Singer et al. have postulated that younger cancer patients may compare their actual level of energy with healthy peers or their previous situation and thereby perceive a larger discrepancy than their older counterparts do (Singer et al., 2011). Additionally, age-specific cancer entities (Whelan et al., 2011), biology and path mechanism (Tricoli et al., 2016) may play an important role in CRF differences between age cohorts. However, the findings of Heutte et al. dispute the conclusion that AYA are more burdened by CRF than older cancer patients (Heutte et al., 2009). An explanation for these divergent findings may be the types of cancer present in their sample: Heutte et al. (Heutte et al., 2009) focused on Hodgkin lymphoma patients who may be especially vulnerable to CRF when diagnosed later in life. We assume that the specific therapy schemes (BEACOPP vs. ABVD) most used to treat Hodgkin Lymphoma may also explain this discrepancy. As stated above, other reviews addressed CRF in younger adolescents (Erickson, 2004; Spathis et al., 2015). Some of their findings are consistent with findings from the AYA cohort we studied, which has a more extensive age range. As in that group, CRF was also found to be a highly prevalent, severe, and distressing symptom in Adolescents with Cancer (Erickson, 2004; Spathis et al., 2015). Additionally, the correlation between additional symptoms (e.g. nausea) and higher CRF scores can be found in both adolescent (Spathis et al., 2015) and AYA cancer patients (Smith et al., 2013a). In contrast to the findings in AYA (Hauken et al., 2015; Weiss et al., 2013), activity interventions were found to be ineffective at treating CRF in adolescent cancer patients (Spathis et al., 2015). Moreover, chemotherapy in adolescents with cancer seems to increase fatigue scores, while the impact of medical variables may be negligible (Geue et al., 2014). Because of on age-overlap between AYA, adolescents with cancer, and paediatric patients, which becomes visible in the congruent findings, we recommend the use of the NCI’s age definition of AYA (15–39-year-olds) to differentiate from paediatric cancer patients in future research.

3.4. Variables associated with CRF Regarding gender differences, one of the 12 studies we reviewed was based on a sample that included patients with all types of cancer and it found that AYA women reported significantly higher CRF scores than AYA men (Geue et al., 2014). Heutte et al. identified greater age as a strong predictor for higher fatigue scores within their Hodgkin lymphoma AYA sample (Heutte et al., 2009). This seems to be the case as well in the Smith et al. (Smith et al., 2013a) study sample of haematological cancer and sarcoma patients (18–25 years vs. 26–39 years). However, one study found no association between CRF and the age of the AYA participants within their samples (Geue et al., 2014). Two studies that used the EORTC QLQ-C30 for patients with all types of cancer found fatigue to be independent of relationship status, number of children, and time since diagnosis (Geue et al., 2014). Moreover, CRF has been found to be strongly negatively correlated with all other dimensions of the EORTC QLQ-C30 except cognitive and emotional functioning (Geue et al., 2014). Further variables found to be associated with higher fatigue scores in haematological cancer and sarcoma patients (measuring CRF with PedsQL, same data set in both studies) were lack of health insurance, radiation therapy, current additional symptoms (e.g. nausea, diarrhoea, fever), being currently in treatment (Smith et al., 2013a) and need of a support group, mental health professional, and physical therapy (Smith et al., 2013b). 3.5. CRF in time course and intervention studies The prevalence of CRF in AYA with all types of cancer was found to be the highest after oncological treatment before hospital discharge and to have decreased six months after acute therapy completion (measured with MFI) (Singer et al., 2011). Heutte et al. also saw in a sample of Hodgkin lymphoma patients that CRF improved over time in all age groups (range 15–70 years) (using the MFI) (Heutte et al., 2009). The three included interventional studies showed that inter alia physical activity, peer support, and psycho-education all led to decreased CRF scores in the intervention groups (Rabin et al., 2011; Hauken et al., 2015; Weiss et al., 2013) (Table 3). 4. Discussion The aims of this systematic review were to outline the prevalence and associated variables of and existing interventions for CRF in AYA. 66

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Table 3 Articles included in the review.

n = sample size, IG = intervention group, CG = comparison group, MD = mean difference, OR = Odds ratio; level of significance: p < 0.5. S = surgery, RT = radio therapy, CT = chemotherapy, O = other. a Age at enrolment/first survey. b Age at diagnosis. c Self-conducted items for assessing unmet needs. d Except non-melanoma skin cancer. e Only patients who were ever employed. f Only the most common cancer treatments are shown (reported by more than 30% of the sample), combinations of treatments leads to percentages over 100%.

Rosenberg et al., 2013; Hauken et al., 2015; Weiss et al., 2013) hinder generalizing and comparing results. However, official data from German cancer registries shows that women in the AYA age cohort are diagnosed more often with cancer than men are (Robert Koch Institute). As such, gender differences in sample size are to be expected. Small sample sizes are common in AYA research in general (Smith et al., 2016) and may be due to difficulties specific to the recruitment of AYA (Hauken et al., 2015; Smith et al., 2016). The included studies used a wide range of measurement instruments for assessing CRF. As such, results cannot be easily compared and generalized. With the exception of two studies (Heutte et al., 2009; Singer et al., 2011), none of the included studies used measuring tools that are multidimensional, fatigue-specific, and validated specifically for use in the AYA age cohort. The PedsQL Multidimensional Fatigue Scale is only validated for patients up to 25 years of age (Varni and Limbers, 2008). The fatigue subscale of the EORTC-QLQ C30 and the PROMIS, POMS and MDASI measure fatigue but are only single subscales with a small number of items that do not distinguish between different dimensions of fatigue (see also Table 2). In our opinion, the reason those instruments were chosen is probably that CRF was neither the main outcome nor the focus of research in those studies (see also Table 3). As stated in a systematic review of fatigue measurement scales (Minton and Stone, 2009) some very different fatigue-specific instruments exist (Weis et al., 2017). We prioritise and recommend the recently developed EORTC-QLQ FA12 (Weis et al., 2017) because of its statistical quality, the fact that it is conducted based on content, and its incorporation of the current CRF definition (Berger et al., 2010).

The number of studies that have examined associations between cancer and CRF in AYA is too small to draw any final conclusions on the matter. The only variable that was assessed by more than one included study with a quality score of ≥4 points was age within the AYA sample. Two studies found no differences between younger and older AYA (Smith et al., 2013a; Geue et al., 2014), a fact that can be explained by similar cancer-related, psychosocial, and developmental factors (Ramphal et al., 2011; Zebrack, 2011; Cooke et al., 2011; Thomas et al., 2006; Zebrack, 2009). This supports the concept of researching and treating adolescents and young adult cancer patients as one specific cohort. Although one study did find that older AYA are more burdened by CRF. That result may be due to the fact that particular assessment focused exclusively on Hodgkin lymphoma patients (Heutte et al., 2009). Findings on the time-dependent course of fatigue in AYA are inconsistent (Erickson et al., 2014; Sanford et al., 2014; Singer et al., 2011). Understanding how CRF changes over time is important for improving clinical care and further research, and for interpreting the results of the intervention studies we included in this review. The reports recorded decreases in CRF over the course of the interventions (Rabin et al., 2011; Hauken et al., 2015; Weiss et al., 2013). As far as the probability of decreases in CRF over time (Corey et al., 2008; Erickson et al., 2013) is concerned, it is necessary to distinguish between the effects of interventions and normal courses of fatigue. Nevertheless, the interventional study results do suggest that CRF in AYA seems to be treatable. 4.2. Limitations of the included studies

4.3. Limitations and strengths of the review The predominately small sample sizes with an above average rate of female participation (Erickson et al., 2014; Rabin et al., 2011;

We only included articles written in German or English found in 67

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current concept and principally treatable character of CRF. With this understanding, they can better educate young patients and support them in coping with their symptoms.

four databases. Hence there might be a language and publication bias, and studies presenting data on our topic may have been excluded. Furthermore, there might be articles that deal with CRF in AYA but do not declare this specific cohort. Because of the broadly defined inclusion criteria, the included studies differed widely in instruments used, time of measurement, and purpose. Therefore, its comparability is severely restricted. As a gap in research on CRF in AYA persists, it seems appropriate to summarize the existing findings, since despite being potentially imperfect or incomplete; they nevertheless point out the importance of this issue and provide initial insights for clinicians and further research. Moreover, the variety of cancer diagnoses and treatments of the included studies may be another bias. However, the unique developmental and disease and treatment associated challenges AYA have to meet (Ramphal et al., 2011; Zebrack, 2011; Cooke et al., 2011; Thomas et al., 2006; Zebrack, 2009) may diminish the importance of cancer sites regarding CRF. The strength of this review is our systematic approach, whereby we searched in different databases with wide-ranging search terms and drew on the efforts of two independent authors. This review points out the current research status on CRF of AYA between the ages of 15 and 39 years old. It also outlines that future research should focus on closing current gaps in our knowledge about CRF in AYA. Furthermore, this review proves that CRF in AYA cannot be assessed incidentally, but must become a distinct focus in further research in order to further advance AYA cancer care.

5. Conclusion This review reveals that, despite our improving knowledge about CRF in general, we still do not know very much about this issue in AYA. The included studies suggest that cancer-related fatigue is a very common and highly-scored symptom in AYA and must be taken seriously into account by researchers and clinicians. AYA appear to be more burdened by CRF than older patients and healthy peers. CRF in AYA can be treated with targeted programmes. More research is needed to clarify the prevalence and severity of CRF in AYA and to further identify CRF related risk and protective factors. Furthermore, future studies should investigate the impact of CRF on quality of life, daily life, and the reintegration of AYA into normal life post-cancer. In doing so, they should use multidimensional and fatigue-specific instruments. Conflict of interest statement None of the authors has a conflict of interests to declare. Acknowledgments This study was supported by the German Cancer Aid (Grant No: 110948). The study sponsor was not involved in the study design, in the collection, analysis and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.

4.4. Implications for future research and clinical practice First, CRF in AYA should be measured with valid, fatigue-specific, multidimensional questionnaires. The EORTC quality of life fatigue module (EORTC QLQ-FA12) could improve the precision and comparability of future research on CRF in AYA (Weis et al., 2017) and should be used. Further research should ascertain the prevalence and severity of CRF in AYA. In going forward, we think it would be reasonable to use different ways of setting cut-off scores for fatigue scales. For example, using additional questionnaires rather than setting a defined percentile of the general population scores may help to approximate the real intensity and frequency of CRF in AYA. Establishing reliable cut-off scores may not only improve research on this issue, it could also help clinicians to assess the severity of CRF in AYA and tailor their treatment and receipt of services accordingly. Second, we need to better understand the impact of CRF on AYA. CRF is probably a symptom that worsens quality of life and represents an important barrier to AYA resuming their professional and social lives after cancer. In other age cohorts, CRF has been found to be a significant barrier to returning to normal life (Charlier et al., 2013) and seems to complicate daily routines (Corey et al., 2008). Third, further research should identify risk groups of AYA patients for CRF to implement need-based professional support in a targeted way. Factors should be also identified that could potentially protect against or help relieve CRF. The findings of this review, for example, indicate that women and patients with additional symptoms should be given more careful attention. Ultimately, further research must lead to the development of different kinds of interventions for supporting AYA in dealing with CRF. Existing studies (Rabin et al., 2011; Hauken et al., 2015; Weiss et al., 2013) suggest that CRF is indeed a treatable condition. The initial results indicate that physical activity interventions may be particularly effective. The existing findings suggest that clinicians and caregivers should be sensitized to the issue of CRF, particularly in AYA, as it seems to have an outsized impact on this cohort. Pending further research on the treatment of CRF in AYA, clinicians may recommend physical activity to their young patients based on initial intervention studies’ results. Most importantly, for the time being, clinicians need to know about the

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