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Purpose Reported prevalence of cancer-related fatigue (CRF) among childhood cancer survivors (CCS) varies widely, and evidence on factors associated with CRF among CCS is limited. We aimed to investigate the prevalence of CRF and its associated factors among adult CCS in Switzerland. Methods In a prospective cohort study, we invited adult CCS who survived at least 5 years since last cancer diagnosis, and were diagnosed when age 0–20 years and treated at Inselspital Bern between 1976 and 2015 to complete two fatigue-measuring instruments: the Checklist Individual Strength subjective fatigue subscale (CIS8R; increased fatigue 27–34, severe fatigue ≥ 35) and the numerical rating scale (NRS; moderate fatigue 4–6, severe fatigue 7–10). We collected information about previous cancer treatment and medical history, and calculated β coefficients for the association between CIS8R/NRS fatigue scores and potential determinants using multivariable linear regression. Results We included 158 CCS (participation rate: 30%) with a median age at study of 33 years (interquartile range 26–38). Based on CIS8R, 19% (N = 30) of CCS reported increased fatigue, yet none reported severe fatigue. CRF was associated with female sex, central nervous system (CNS) tumors, sleep disturbance, and endocrine disorders. Lower CRF levels were observed among CCS age 30–39 years compared to those younger. Conclusions A considerable proportion of adult CCS reported increased levels of CRF. Implications for Cancer Survivors CCS who are female and < 30 years old, have a history of CNS tumor, report sleep disturbance, or have an endocrine disorder should be screened for CRF. Keywords Fatigue · Childhood cancer · Survivors · Questionnaires · Late effects Nicolas X von der Weid and Christina Schindera contributed equally to this work (shared last authorship). * Christina Schindera Department of Health Sciences and Medicine, University email@example.com of Lucerne, Lucerne, Switzerland Department of Internal Medicine, Cantonal Hospital Baden, Childhood Cancer Research Group, Institute of Social Baden, Switzerland and Preventive Medicine, University of Bern, Bern, Switzerland Pediatric Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland Division of Pediatric Oncology/Hematology, University Children’s Hospital Basel, University of Basel, Basel, Center for Primary Care and Public Health (Unisanté), Switzerland University of Lausanne, Lausanne, Switzerland Graduate School for Health Sciences, University of Bern, Bern, Switzerland CANSEARCH Research Platform in Pediatric Oncology and Hematology, Department of Pediatrics, Gynecology and Obstetrics, University of Geneva, Geneva, Switzerland Vol.:(0123456789) 1 3 Journal of Cancer Survivorship Background Methods Cancer-related fatigue (CRF) is a common and disturbing Study design and population late effect in cancer patients and survivors which is often underdiagnosed and undertreated [1, 2]. CRF is defined Our study is part of the CardioOnco study investigating as “a distressing, persistent, subjective sense of physical, cardiovascular health among adult CCS set up within rou- emotional, and/or cognitive tiredness or exhaustion related tine care in a cardio-oncology clinic. Detailed information to cancer or cancer treatment that is not proportional to about the CardioOnco study design is available . It was recent activity and interferes with functioning” according initiated in 2016 as a single-center study involving Pedi- to the National Comprehensive Cancer Network (NCCN) atric Hematology and Oncology and Pediatric and Adult . CRF usually diminishes in the first year after treatment Cardiology at the University Hospital Bern, Inselspital, completion, yet a previous study has shown that 24% of in Switzerland. The study invited all CCS diagnosed with childhood cancer survivors continued to experience CRF childhood cancer since 1976, who survived at least 5 years up to two decades after cancer diagnosis . The etiology since diagnosis, were treated at the University Children’s of CRF is multi-factorial and poorly understood . Bio- Hospital Bern with any chemotherapy and/or heart-relevant logical, demographic, psychosocial, and behavioral factors radiotherapy, were older than age 18 years at the time of influence the development of CRF among cancer patients study, and who were registered in the Swiss Childhood and survivors . For this reason, there is no “gold stand- Cancer Registry (ChCR). The ChCR includes all patients ard” of treatment; however, several approaches, such as in Switzerland diagnosed before the age of 20 years with exercise, psychosocial interventions, and mind–body any childhood cancer coded according to the International interventions, showed positive effects reducing fatigue Classification of Childhood Cancer Third Edition (ICCC- . To accurately identify fatigued survivors, implement- 3) [11, 12]. We excluded survivors who were treated with ing regular screening for CRF in long-term follow-up care surgery only and/or radiotherapy other than heart-relevant of childhood and adolescent cancer survivors (CCS) is radiotherapy. We invited eligible survivors identified by the recommended . ChCR by post to visit the cardio-oncology clinic. During Reported prevalence of CRF in CCS varies widely in clinic visits, we took medical history, performed physical the literature—from 0 to 62% . Variability in preva- examinations and echocardiograms, and counselled survi- lence is due to differences in study designs, methodol- vors about their cardiovascular health. A few hours after the ogy, and fatigue-measuring instruments. Until 2020, there visit, survivors received an online survey link via email. This was no unified recommendation regarding which fatigue- online survey includes questionnaires on fatigue, physical measuring instrument to use in CCS . Therefore, a activity, nutrition, and quality of life. large number of instruments including the Checklist Individual Strength (CIS), or the numerical rating scale Population characteristics (NRS), were in use. Recent guidelines for surveillance of CRF among childhood, adolescent, and young adult Sociodemographic variables cancer survivors by the International Guideline Harmo- nization Group (IGHG) show knowledge gaps about fac- When taking medical history during the visit, we collected tors associated with CRF for this population . Many data on age at study, marital and employment status, and treatment-related, clinical, and sociodemographic factors parenting children. have been studied as contributors of cancer-related fatigue in CCS, such as anxiety, pain, and educational level [5, Lifestyle variables 7]. However, psychological distress is the only factor with high quality of evidence available . Other associated During the visit, we asked survivors about their smoking sta- factors, such as late effects, pain, older age, radiotherapy, tus. We also performed anthropometry to obtain survivors’ and sleep problems, have moderate or low levels of evi- body mass index (BMI) and waist–hip ratio. We defined and dence . It is likely that the etiology of cancer-related classified both variables according to World Health Organi- fatigue is multifactorial [1, 8, 9], and sufficient evidence zation cutoff points [13, 14]. on CRF prevalence and factors associated with it is cru- cial for establishing and updating clinical guidelines on Clinical variables CRF in CCS, such as those from the IGHG. Therefore, in this study, we aimed to evaluate the prevalence of CRF In March 2016, ChCR provided data about eligible survi- and factors associated with CRF among CCS. vors, such as age at cancer diagnosis, time since diagnosis, 1 3 Journal of Cancer Survivorship cancer diagnosis, and history of relapse. We asked survivors state on a scale from 0 to 10. We graded fatigue as moderate during clinic visits or later extracted from medical records with scores 4 to 6 and as severe with scores 7 to 10 . whether he/she has had second primary malignancy, sleep disturbance, endocrine disorders, and antidepressant use as a Statistical analysis proxy for depression. We also asked survivors about possible sleep disturbance using three yes–no questions: “Do you We calculated the prevalence of increased and severe CRF generally have problems falling asleep?”; “Do you gener- based on CIS8R and moderate and severe CRF based on ally wake up several times during the night?”; and “Do you NRS, overall and stratified by sex. We then fitted univariable generally have problems sleeping through the night?”. We linear regression models to identify associations between defined sleep disturbance as answering “yes” to one or more higher fatigue scores and sociodemographic, lifestyle, clini- questions similar to previous studies . cal, and treatment-related characteristics of the study popu- lation. In this model, we selected a priori all possible factors Treatment‑related variables associated with CRF known from the literature  which were available in our dataset. We then included variables From medical records, we collected information on anthra- associated with increased CRF scores in at least one of the cyclines (including cumulative doses), alkylating agents, two fatigue instruments at p < 0.1 in the multivariable analy- heart-relevant and/or cranial radiotherapy (CRT; including sis. To avoid overfitting, we performed a backward selection cumulative doses), and hematopoietic stem cell transplan- of variables for the multivariable analysis using corrected tation (HSCT). Heart-relevant radiotherapy was defined as Akaike’s information criterion (AICc) . All p values any therapeutic exposure of the chest, abdomen, spine (tho- are two-sided; we considered p < 0.05 statistically signifi- racic or whole), and total body irradiation (TBI) . If a cant. We calculated p values using likelihood-ratio tests. All survivor received TBI, we added the dose to heart-relevant analyses were performed using Stata software, version 16.1 radiotherapy and CRT. We also collected information about (StataCorp. 2019, Stata Statistical Software: Release 16, intrathoracic surgery and cancer treatment duration. College Station, TX: StataCorp LLC). We used the coefplot command for graphically presenting our multivariable linear Fatigue measuring instruments regression analysis . We used two different measuring instruments to assess CRF (see Supplementary Materials 1 and 2). On the day Results of their clinic visit, CCS participants were invited to take the online questionnaire, which included both instruments. Characteristics of study population The Checklist Individual Strength subjective fatigue sub- scale (CIS8R) is an 8-item self-reporting instrument. It is Between March 2016 and September 2021, we invited 529 one of four subscales of the Checklist Individual Strength eligible CCS to the CardioOnco study. Of those, 285 (54%) instrument introduced by Vercoulen et al. in 1994 which participated; 64 (12%) refused to participate; and 180 (34%) is a multidimensional measure of severity and behavioral did not respond. Of all invited survivors, 158 (30%) filled out consequences of fatigue [17–19]. Each item is scored on a questionnaires that included both fatigue-measuring instru- 7-point Likert scale (1 = “yes, that is true”; 7 = “no, that is ments (Fig. 1). We included slightly more females (51%; not true”) . Reversed scoring is applied to some items Table 1). The median age at time of study was 33 years . Statements of the questionnaire refer to aspects of (interquartile range [IQR] 26–38), and the median age at fatigue experienced during the previous 2 weeks; higher diagnosis was 7 years (IQR 2–13). The most frequent can- scores indicate higher degree of fatigue . We chose to cer diagnoses were leukemia (37%), lymphoma (22%), and analyze the results of CIS8R since it is a reliable and vali- malignant bone tumors (11%). Thirteen percent had expe- dated instrument for assessing CRF . The psychometric rienced a relapse. Criteria for sleep disturbance were ful- properties of the CIS are good among adult CCS popula- filled among 28% of CCS, while endocrine disorders were tion—it correlates highly with other fatigue measures—and observed in 22%. Radiotherapy had been administered to the CIS8R especially showed excellent internal consistency 35% of CCS. Twenty-nine percent of CCS received heart- . The range for CIS8R is 8–56 . Scores between 27 relevant radiotherapy with a median cumulative dose of 25.5 and 34 were defined as increased fatigue and a score of 35 or Gray (Gy; IQR 18–38.5); 15% received CRT with a median higher as severe fatigue [21, 24]. As a second instrument, we cumulative dose of 33 Gy (IQR 18–51.6); and 9% received used the NRS. We asked survivors “How intense/strong is both. In Supplementary Table 1, we show basic characteris- your fatigue at the moment?” We asked participants to mark tics of non-participating and participating CCS who did not the point best representing perception of their current fatigue complete fatigue-measuring instruments. The comparison of 1 3 Journal of Cancer Survivorship Discussion We found that about one-fifth of CCS reported increased CRF many years after cancer diagnosis, while none reported severe CRF. Female survivors, survivors of CNS tumors, and those with sleep disturbance or endocrine dis- orders had more CRF than others. Older age at study was associated with lower levels of CRF compared with those aged < 30 years. Since study populations differ by age, cancer treat- ments and diagnoses, and outcome definition, reported prevalence of CRF among adult CCS varies widely . Comparing results from current studies is also difficult because up to eight different questionnaires were used in CRF prevalence studies . Similar to our study, Lopez- Fig. 1 Flowchart of the study population. N, number Guerra et al. found no participant reported severe CRF , yet only included 17 long-term survivors of Ewing participants and non-participants of our study shows that age sarcoma with a median age at study of 19 years. Calami- at study, chemotherapeutic treatment, and HSCT differed. nus et al. found 4% of participants severely fatigued in a Younger CCS were more reluctant to participate. cohort of 725 Hodgkin lymphoma survivors with median age at study of 28 years . However, in large studies unrestricted by including survivors of only one cancer Prevalence and CRF severity diagnosis, the prevalence of severe CRF was higher . In the North America-based Childhood Cancer Survi- Based on CIS8R, 30 (19%; 95% confidence interval [CI] vor Study (CCSS), 14% of 1821 adult CCS (mean age at 13–26%) CCS had increased fatigue and no survivor had study: 35 years) were identified as severely fatigued using severe fatigue. In the whole cohort, median CIS8R scores the Functional Assessment of Chronic Illness Therapy- were 19 (IQR 14–25); 16 (IQR 13–21) for males; and 22 (IQR Fatigue (FACIT-F) instrument . In the Dutch CCS 16–26) for females. Based on NRS, we identified 33 survivors study (DCCSS-LATER), 26% of 2516 adult CCS (median (21%; 95% CI 15–28%) as moderately fatigued and 37 (23%; time since diagnosis: 22 years) were identified as severely 95% CI 17–31%) survivors as severely fatigued. NRS median fatigued using the Short Fatigue Questionnaire (SFQ) . scores were 3.1 (IQR 1.8–6.4) for the whole cohort, 2.2 (IQR In the British CCS study (BCCSS), 33% of 9920 adult 1.2–3.9) for males, and 5.3 (IQR 2.7–7.4) for females. Out of CCS (median age at study: 33 years) were identified as the 30 CCS identified by CIS8R with increased (or severe) severely fatigued using the Short Form 36 Health-status CRF, 27 CCS were also identified by NRS as moderately or Survey (SF-36) . Since these studies used different severely fatigued (Supplementary Figure 1). fatigue-measuring instruments, reported prevalences fluc- tuated strongly. The fluctuations emphasize the need for a harmonized assessment of CRF among CCS to better Factors associated with increased CRF understand CRF prevalence among adult CCS. Our study showed female sex was associated with We found that female sex (β coefficient [ β] 2.4; 95% CI higher CRF levels. This has been described before in CCS, 0.7–4.2), central nervous system (CNS) tumors (β 5.3; 95% but the overall level of evidence is very low according CI 0.7–9.9), sleep disturbance (β 4.6; 95% CI 2.7–6.6), and to IGHG criteria [5, 32–38]. In the general population, endocrine disorders (β 3.0; 95% CI 0.6–5.4) were asso- females also more often report CRF, yet the reason is ciated with more CRF in CIS8R in multivariable linear unclear [39, 40]. It does not appear solely attributable to regression analysis (Fig. 2; Supplementary Table 2). Survi- health conditions that have a higher prevalence in women vors with an age at study between 30 and 39 years (β − 2.6; and are known to be associated with fatigue (e.g., depres- 95% CI − 4.5 to − 0.7) experienced less CRF as measured sion) . We further saw higher CRF levels among CNS by CIS8R than younger CCS. We observed similar associa- tumor survivors when compared with survivors of leuke- tions in the model based on NRS scores (Supplementary mia. While the recently published article by van Deuren Table 2). We present results of univariable linear regres- et al. reports statistically significant association between sion in Supplementary Tables 3A–C. CRF and previous diagnosis of a CNS tumor in adult CCS, 1 3 Journal of Cancer Survivorship Table 1 Sociodemographic, Total Males Females lifestyle, clinical, and treatment- a a a N = 158 (%) N = 78 (%) N = 80 (%) related characteristics of participating adult survivors of Sociodemographic characteristics childhood cancer Age at study, years, median [IQR] 33 [26-38] 33 [27-38] 33 [24.5–38] < 30 59 (37%) 25 (32%) 34 (43%) 30–39 68 (43%) 38 (49%) 30 (38%) ≥ 40 31 (20%) 15 (19%) 16 (20%) Married, yes 53 (34%) 30 (38%) 23 (29%) Children, yes 42 (27%) 22 (28%) 20 (25%) Employment, yes 126 (80%) 69 (88%) 57 (71%) Lifestyle characteristics Smoking currently, yes 24 (15%) 13 (17%) 11 (14%) 2 b Body mass index, kg/m , median [IQR] 23.5 [21.3–26.4] 24.1 [22.1–26.9] 23.2 [20.7–25.9] Underweight 4 (3%) - 4 (5%) Normal weight 95 (60%) 47 (60%) 48 (60%) Overweight 43 (27%) 25 (32%) 18 (23%) Obese 16 (10%) 6 (8%) 10 (13%) Waist-hip ratio, median [IQR] 0.83 [0.78–0.91] 0.87 [0.81–0.93] 0.79 [0.76–0.86] No abdominal obesity 97 (61%) 44 (56%) 53 (66%) Abdominal obesity present 46 (29%) 26 (33%) 20 (25%) Missing measurements 15 (9%) 8 (10%) 7 (9%) Clinical characteristics Age at diagnosis, years, median [IQR] 7 [2-13] 6 [2-13] 9 [9-13] Time since diagnosis, years, median [IQR] 25 [18-32] 26 [19-34] 25 [17.5–31] ICCC-3 cancer diagnoses I Leukemias 58 (37%) 24 (31%) 34 (43%) II Lymphomas 34 (22%) 22 (28%) 12 (15%) III CNS tumors 8 (5%) 5 (6%) 3 (4%) IV Neuroblastoma 6 (4%) 3 (4%) 3 (4%) V Retinoblastoma 3 (2%) - 3 (4%) VI Renal tumors 11 (7%) 5 (6%) 6 (8%) VII Hepatic tumors 2 (1%) 2 (3%) - VIII Malignant bone tumors 18 (11%) 8 (10%) 10 (13%) IX Soft tissue sarcomas 10 (6%) 4 (5%) 6 (8%) X Germ cell tumors 1 (1%) - 1 (1%) XI–XII Other tumors 7 (4%) 5 (6%) 2 (3%) Total IV–XII 58 (37%) 27 (35%) 31 (39%) Relapse, yes 21 (13%) 15 (19%) 6 (8%) Second primary malignancy, yes 8 (5%) 3 (4%) 5 (6%) , yes 44 (28%) 15 (19%) 29 (36%) Sleep disturbance Endocrine disorders , yes 35 (22%) 17 (22%) 18 (23%) Intake of antidepressants, yes 11 (7%) 4 (5%) 7 (9%) Treatment-related characteristics Anthracyclines, yes 107 (68%) 59 (76%) 48 (60%) No 51 (32%) 19 (24%) 32 (40%) > 0 and < 250 mg/m 67 (42%) 37 (47%) 30 (38%) ≥ 250 mg/m 40 (25%) 22 (28%) 18 (23%) Alkylating agents, yes 96 (61%) 51 (65%) 45 (56%) Radiotherapy, yes 56 (35%) 29 (37%) 27 (34%) Heart-relevant radiotherapy, yes 46 (29%) 23 (29%) 23 (29%) > 0 and < 15 Gy 9/46 (6%) 5/23 (6%) 4/23 (5%) ≥ 15 and < 35 Gy 20/46 (13%) 10/23 (13%) 10/23 (13%) 1 3 Journal of Cancer Survivorship Table 1 (continued) Total Males Females a a a N = 158 (%) N = 78 (%) N = 80 (%) ≥ 35 Gy 17/46 (11%) 8/23 (10%) 9/23 (11%) Cranial radiotherapy, yes 24 (15%) 17 (22%) 7 (9%) > 0 and < 35 Gy 12/24 (8%) 10/17 (13%) 2/7 (3%) ≥ 35 Gy 12/24 (8%) 7/17 (9%) 5/7 (6%) Radiotherapy relevant to both brain and heart 14 (9%) 11 (14%) 3 (4%) Hematopoietic stem cell transplantation, yes 9 (6%) 8 (10%) 1 (1%) Intrathoracic surgery, yes 19 (12%) 6 (8%) 13 (16%) Treatment era 1976 to 1985 35 (22%) 22 (28%) 13 (16%) 1986 to 1995 62 (39%) 27 (35%) 35 (44%) 1996 to 2005 44 (28%) 20 (26%) 24 (30%) 2006 to 2015 17 (11%) 9 (12%) 8 (10%) Duration of treatment, months, median [IQR] 12 [6-31] 10 [5-29] 15 [6-31] ≤ 1 year 79 (50%) 42 (54%) 37 (46%) > 1 year 79 (50%) 36 (46%) 43 (54%) N, number; IQR, interquartile range; ICCC-3, International Classification of Childhood Cancer 3rd edition; CNS, central nervous system Column percentages are given b 2 2 Body mass index was classified as underweight (< 18.5 kg/m ), normal weight (≥ 18.5 – < 25 kg/m ), 2 2 overweight (≥ 25 – < 30 kg/m ), and obese (≥ 30 kg/m ) Abdominal obesity was defined according to WHO cutoff point as waist–hip ratio ≥ 0.90 cm in men and ≥ 0.85 cm in women Sleep disturbance deemed to be present if survivors answered “yes” to one or more of the following ques- tions: “Do you have problems falling asleep?”, “Do you have problems sleeping through the night?”, or “Do you wake up multiple times during the night?” Including hyperthyroidism, hypothyroidism, diabetes mellitus, diabetes insipidus, growth hormone defi- ciency, and any other hormonal disorder According to the Children’s Oncology Group Guidelines Version 5.0 (i.e., chest, abdomen, whole or tho- racic spine, total body irradiation)  Including survivors who received total body irradiation Including treatment of primary cancer and relapses Mulrooney et al. report association which is not statisti- mellitus and hypothyroidism had the strongest correlation cally significant, and Langeveld et al. report no association with CRF in subsequent multivariable linear regression [4, 35, 36]. models replacing the general endocrine disorder variable Sleep disturbance and endocrine disorders were associ- with individual endocrine disorders that we performed ex ated with increased CRF in our study. Meeske et al. also post (Supplementary Tables 4A–F). reported a significant association between sleep disturbance In our study, age at study was also associated with and CRF among 161 adult survivors of acute lymphoblastic CRF severity. The literature on the topic of age at study leukemia (OR = 6.15; 95% CI 2.3–16.2) . Since cluster- is conflicting. When looking at the available studies, it is ing of CRF and sleep problems is well documented among important to dier ff entiate whether this variable was assessed adult cancer survivors, the low level of evidence for associa- as continuous or categorical. As for age at study as a continuous tions between sleep disorders and CRF among adult CCS variable, Hamre et al. and Johansdottir et al. showed a weak that Christen et al. reported is surprising [5, 43–46]. As for but statistically significant positive association of older age endocrine disorders, the literature differs on the spectrum at study with CRF (OR 1.04; 95% CI 1.0–1.1 and 1.08; 95% of endocrine disorders considered. While Mulrooney et al. CI 1.01–1.16 respectively) [34, 48]. Two studies showed no and Hamre et al. showed no association of hypothyroidism significant association of older age with CRF which is in line with CRF, Sato et al. showed an association of endocrine with the finding of our univariable model [33, 36]. The weak abnormality with CRF among CCS [33, 35, 47]. Among association with age at study as a continuous variable might be endocrine disorders that we assessed in our study, diabetes caused by different levels of CRF expressed over the course of 1 3 Journal of Cancer Survivorship Fig. 2 Forest plot of β coef- ficients with 95% confidence intervals retrieved from multivariable linear regres- sion showing the association between CRF levels measured by CIS8R and sex, age at study, ICCC-3 cancer diagnosis, sleep disturbance, and endocrine disorders. Higher coefficients represent stronger associations of variables with increased CRF levels. Except for ICCC-3 cancer diagnoses, all p values were < 0.05. Abbreviations: CIS8R, Checklist Individual Strength subjective fatigue subscore; CRF, cancer-related fatigue; ICCC-3, International Classification of Childhood Cancer 3rd edition life. As we showed in our multivariable analysis, CRF follows obstacle for severely fatigued survivors and likely contributor a U-shaped pattern across the three age categories with lowest to the relatively low participation rate of 30%. For this reason, CRF among CCS aged 30–39 years. Paradoxically, the recent severely fatigued CCS are possibly underrepresented in our study by van Deuren et al. showed an upside-down U-shaped study. However, when comparing participants with those pattern across age categories in terms of CRF prevalence . who took part in the CardioOnco study but did not fill out This paradox could be caused by different study designs since fatigue-measuring instruments in the questionnaire, we can van Deuren et al. assessed prevalence of CRF in a national see that there are no significant differences between these two cohort whereas our study is a single-center study of survivors populations. The study design possibly introduces further at a cardio-oncology clinic. Further studies are needed to clarify selection bias, since CCS treated with surgery only were the course of CRF over lifetime. excluded, yet current research shows no effect of surgical treatment on CRF among CCS . CCS with shorter time Strengths and limitations since diagnosis, e.g., of 5 to 9 years, were less represented in our cohort than those with longer time since diagnosis. This Our study is the first study on prevalence and factors associated may have underrepresented the presented CRF prevalence with CRF among Swiss adult CCS. Since the study setting since the risk for CRF decreases with time since diagnosis . allowed gathering high-quality and reliable data on treatment exposures, current medical histories, anthropometry, and CCS lifestyles, the study setting was valuable. It allowed analyzing Conclusion details from a spectrum of possible factors associated with CRF when compared with studies with only self-reported We showed a substantial proportion of survivors suffer from data. However, the study setting was also a limitation since the increased levels of CRF that might interfere with their daily main study interest was assessing cardiovascular health during functioning. We identified demographic and clinical factors outpatient clinic visits. For this reason, survivors had to accept associated with increased CRF which could help to better the invitation and attend the outpatient clinic after which they identify CCS at risk for CRF. Identifying CRF-associated received the fatigue questionnaire—a potentially significant factors is important for the development of CRF surveillance 1 3 Journal of Cancer Survivorship Competing interests JR is meanwhile an employee of Novartis Pharma, guidelines and ensuring better tailored follow-up care of Switzerland. Other authors have no relevant financial or non-financial CCS. In summary, healthcare professionals need to be aware interests to disclose. of the increased risk of CRF among adult survivors of child- hood cancer and should actively screen CCS, particularly Open Access This article is licensed under a Creative Commons female survivors, < 30 years old, CNS tumor survivors, and Attribution 4.0 International License, which permits use, sharing, survivors with sleep disturbance or endocrine disorders. adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, Supplementary Information The online version contains supplementary provide a link to the Creative Commons licence, and indicate if changes material available at https:// doi. org/ 10. 1007/ s11764- 023- 01413-1. were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated Acknowledgements We thank all survivors for participating in our otherwise in a credit line to the material. If material is not included in the study, the study team of the Childhood Cancer Research Group (Luzius article's Creative Commons licence and your intended use is not permitted Mader, Selma Riedo, and Andrea Ziörjen), the data managers of the by statutory regulation or exceeds the permitted use, you will need to Swiss Pediatric Oncology Group (Claudia Althaus, Nadine Assbichler, obtain permission directly from the copyright holder. To view a copy of Pamela Balestra, Heike Baumeler, Nadine Beusch, Sarah Blanc, Susann this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. Drerup, Janine Garibay, Franziska Hochreutener, Friedgard Julmy, Eléna Lemmel, Rodolfo Lo Piccolo, Heike Markiewicz, Veneranda Mattielo, Annette Reinberg, Renate Siegenthaler, Astrid Schiltkne- cht, Beate Schwenke, Monika Imbach, and Verena Stahel), and the team of the Swiss Childhood Cancer Registry (Meltem Altun, Erika Brantschen, Katharina Flandera, Anna Glenck, Elisabeth Kiraly, Ursula References Kühnel, Eleftheria Michalopoulou, Erika Minder, Shelagh Redmond, and Cornelia Stadter). We also want to thank the author of the Checklist 1. Bower JE. Cancer-related fatigue–mechanisms, risk factors, and Individual Strength questionnaire—Jan Vercoulen—for answering our treatments. Nat Rev Clin Oncol. 2014;11(10):597–609. questions regarding the questionnaire. We thank Kristin Marie Bivens 2. James S, Wright P, Scarlett C, Young T, Jamal H, Verma R. 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Journal of Cancer Survivorship: Research and Practice – Springer Journals
Published: Jun 13, 2023
Keywords: Fatigue; Childhood cancer; Survivors; Questionnaires; Late effects
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