This study examines the association between symptoms of fatigue and DLA and evaluates their relationships in terms of subgroups in PCS. The results of scales were evaluated as VAS, Borg and PedsQL MFS; and DLA with WeeFIM.
According to our results, the important risk factors affecting fatigue were; age, gender, BMI, tumor type, time after completion of treatment, CT and RT. Younger age was found to be associated with higher level of fatigue. We cannot definitely find out the reason, but this is probably due to presence of large sample size of children with CNS tumor in whom their ages were younger than the leukemia group; becouse it is established that patients with CNS tumors were more tired than ALL group in our study. We did not find an association between age at diagnosis and fatigue in our study like that of the [14–16]. Girls had high fatigue scores in our study. This is also probably related to the larger sample of CNS group in our study. This demographic finding was consistent with other various studies [14–18]. Higher BMI was associated with higher levels of fatigue in our study. Although Karimi et al. [4], having a sample of recent survivors like that of us did not report such association, Johnson et al. [19] reported clinically significant relationship with fatigue and weight. This study included brain tumor survivors of ages 8–12 years who were less than 6 years posttreatment, that is like our brain tumor study group. Studies with adult survivors of childhood cancers revealed an increased risk of fatigue with higher BMI [7, 14]. Time after completion of treatment was 28.35 ± 11.27 months in our study. Our study time point was relatively an earlier time after completion of treatment than that of the literature, but our findings are in concordant with Johnson et al. [19], Karimi et al. [4], and Nagai et al [17]. in which those studies are also the studies performed just recent years after treatment. Fatigue scores decreased with time elapsed in those studies. According to our study, in terms of CNS vs ALL group, probably because ALL group was older in age and a longer period of time had passed since the end of the treatment, a lower level of fatigue was detected in that ALL group. The average time since diagnosis was under 10 years in our study and those aformentioned studies [4, 17, 19]. This is a shorter time than that of Langeveld et al. [15], Meeske et al. [7] and Mulroney et al [14] in which fatigue levels declined over time during the long follow up of survivors. Tumor type, in our study, which indicates high number of patients with CNS tumor (40% of total) was found to be associated with higher fatigue scores. Johnson et al. [19], pointed the significance of fatigue in their brain study group of 21 patients. However, no significant effect was found between fatigue and primary cancer diagnosis in the literature. [4, 14–18]. Treatment modalities of both CT and RT were found to be significantly associated with higher levels of fatigue in this study. This might be probably due to large sample size of patients with CNS tumors in our study in whom all of them were treated with both CT and cranial RT. Johnson et al. [19] established a clinically significant relationship between fatigue and CT and cranial RT. Forty-two of 142 (30%) CNS tumor survivors were identified as having clinically significant fatigue in the study of Brand’s et al [20]. Although an increased risk was detected with any RT [4, 15, 16, 18], there is conflicting evidence of the risk after cranial irradiation [15–17]. In contrary to our findings, no significant effect of CT was found in the literaure [4, 14, 16, 18]. The International Late Effects of Childhood cancer guideline harmonization group (IGHG), in 2020, graded the strength of the fatigue recommendations according to published evidence-based methods [3] and reported that survivors are at increased risk for cancer-related fatigue (Level A evidence). They found the prevalance of fatigue ranging from 10.2 to 85% in 24 studies.
After measurement of fatigue in our study, we investigated the outcome of fatigue in cancer survivors in terms of impact on quality of life, mobility, self-care, locomotion, communication and cognition. Many studies used and recommended the scales which called PROMIS Pediatric Fatigue Measure and PedsQL MFS [21–25] in children with cancer. It is suggested that PROMIS pediatric fatigue measures, and the PedsQL MFS are valid and reliable measures to evaluate fatigue in patients with cancer (level B) [3]. In our study, we used PedsQL MFS which correlated the fatigue scales significantly. We found a statistically significant relationship between VAS score and WeeFIM self-care, social cognition, motor control, cognitive and total control. WeeFIM total, cognitive and motor total score average was found at “modified independence” level. Although these children perform no-help activities in DLA, they are not at completely “independent-complete independence” level. This shows that their levels are below the levels of healthy normal children [26]. It was seen that not only physical but also mental fatigue of children was reflected in their DLA. Patients with higher VAS scores (high fatigue score) did low performance of WeeFim self-care, social cognition, motor control, cognitive and total control. Patients with high MFS scores (low fatigue scores) had high performance in locomotion, social cognition and cognitive subscale. We found higher scores of fatigue in CNS tumor group than ALL group, in our study, and there was a significant association in terms of WeeFIM locomotion, communication, cognition, but not with sphincter control, transfers and motor total between these groups. CNS tumor group, with younger ages and having high risk of neurocognitive sequela due to surgery, cranial RT and CT, showed low WeeFim scores on communication and cognition. Hence, fatigue has not only physical impact but also neurocognitive adverse effect. DLA are more hampered in patients with CNS tumor in terms of self-care, socialization and cognition rather than locomotion. These results indicate that symptom profiles may be important to understand the variation between individuals in terms of impact of symptoms on functioning.
Our study has several clinical implications and limitations. First, PCS attending pediatric oncology centers should be screened for fatigue and would benefit from routine assessment of fatigue. Risk factors according to each patient should be identified and possible physical, social and cognitive impact should be screened by way of measurements of DLA. There should be interventions and solutions in management of symptoms of fatigue after ruling out other medical reasons. Given our study on self-reported data, information about past/current symptoms and other medical information may have been affected by recall bias. This study is cross-sectional with a wide age range of patients with heterogeinity. However, we suggest survivors with CNS tumor needs more attention and care in terms of fatigue and its outcome.
Future cohort studies with specific and detailed evaluations are needed to improve surveillance and/or screening for fatigue, and mobility and of potential relevances like the maintenance of overweight. Future studies may benefit from assessments of symptomatic treatments according to tumor types. Christen et al. [3] mentioned that interventions that are useful are physical activity (level B evidence), education about cancer-related fatigue (level B evidence), relaxation and mindfullness (level C evidence, existing guidelines), cognitive behavioral therapy (level C evidence, existing guidelines), and adventure-based training (level C evidence). Growing evidence advocates physical activity interventions as beneficial, as well as feasible and safe, in managing cancer-related fatigue, and also improve quality of life and functional status during and after treatment in PCS [27].