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Toward unraveling the correlates of fatigue in glioma

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Abstract Background Even though fatigue is one of the most prevalent and burdensome symptoms in patients with glioma, its etiology and determinants are still poorly understood. We aimed to identify which demographic, tumor- and treatment-related characteristics and patient-reported outcome measures (PROMs) are associated with or are predictors of fatigue in glioma. Methods In this retrospective observational study, we included glioma patients with preoperative and postoperative assessments including PROMs on fatigue, depression, cognitive functioning, and health-related quality of life (HRQoL). Linear mixed models were used to identify which clinical factors and PROMs were associated with fatigue and linear multiple regression was used to detect predictors of postoperative fatigue. Results In this study, 222 patients were included (78% grade II–III glioma, 22% grade IV). These patients had performed 333 assessments (193 preoperative and 116 one year postoperatively). Of all assessments, 39% was indicative of severe fatigue. Several HRQoL domains, depression, and right-sided tumors were significantly associated with fatigue (marginal R2 = 0.63). Contrary to common expectations, tumor type, treatment-related factors, and timing of the assessment, were not associated with fatigue. In a subgroup of 70 patients with follow-up assessments, preoperative fatigue, and physical functioning were predictors of postoperative fatigue (adjusted R2 = 0.31). Conclusion Fatigue is a complex symptom, which should not solely be attributed to the tumor or its treatment, but is instead related to different aspects of mood and HRQoL. These insights are important in understanding fatigue and could guide symptom management, especially in patients with lower-grade tumors.
Title: Toward unraveling the correlates of fatigue in glioma
Description:
Abstract Background Even though fatigue is one of the most prevalent and burdensome symptoms in patients with glioma, its etiology and determinants are still poorly understood.
We aimed to identify which demographic, tumor- and treatment-related characteristics and patient-reported outcome measures (PROMs) are associated with or are predictors of fatigue in glioma.
Methods In this retrospective observational study, we included glioma patients with preoperative and postoperative assessments including PROMs on fatigue, depression, cognitive functioning, and health-related quality of life (HRQoL).
Linear mixed models were used to identify which clinical factors and PROMs were associated with fatigue and linear multiple regression was used to detect predictors of postoperative fatigue.
Results In this study, 222 patients were included (78% grade II–III glioma, 22% grade IV).
These patients had performed 333 assessments (193 preoperative and 116 one year postoperatively).
Of all assessments, 39% was indicative of severe fatigue.
Several HRQoL domains, depression, and right-sided tumors were significantly associated with fatigue (marginal R2 = 0.
63).
Contrary to common expectations, tumor type, treatment-related factors, and timing of the assessment, were not associated with fatigue.
In a subgroup of 70 patients with follow-up assessments, preoperative fatigue, and physical functioning were predictors of postoperative fatigue (adjusted R2 = 0.
31).
Conclusion Fatigue is a complex symptom, which should not solely be attributed to the tumor or its treatment, but is instead related to different aspects of mood and HRQoL.
These insights are important in understanding fatigue and could guide symptom management, especially in patients with lower-grade tumors.

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