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Background Maintenance of functioning and well-being during the progression-free survival (PFS) period is important for glioma patients. This study aimed to determine whether health-related quality of life (HRQoL) can be maintained during progression-free time, and factors associated with HRQoL deterioration in this period. Methods We included longitudinal HRQoL data from previously published clinical trials in glioma. The percentage of patients with stable HRQoL until progression was determined per scale and at the individual patient level (i.e. considering all scales simultaneously). We assessed time to a clinically relevant deterioration in HRQoL, expressed in deterioration-free survival and time-to-deterioration (the first including progression as an event). We also determined the association between sociodemographic and clinical factors and HRQoL deterioration in the progression-free period. Results Five thousand five hundred and thirty-nine patients with at least baseline HRQoL scores had a median time from randomization to progression of 7.6 months. Between 9-29% of the patients deteriorated before disease progression on the evaluated HRQoL scales. When considering all scales simultaneously, 47% of patients deteriorated on >= 1 scale. Median deterioration-free survival period ranged between 3.8-5.4 months, and median time-to-deterioration between 8.2-11.9 months. For most scales, only poor performance status was independently associated with clinically relevant HRQoL deterioration in the progression-free period. Conclusions HRQoL was maintained in only 53% of patients in their progression-free period, and treatment was not independently associated with this deterioration in HRQoL. Routine monitoring of the patients functioning and well-being during the entire disease course is therefore important, so that interventions can be initiated when problems are signaled., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [RP 1515]

Background Maintenance of functioning and well-being during the progression-free survival (PFS) period is important for glioma patients. This study aimed to determine whether health-related quality of life (HRQoL) can be maintained during progression-free time, and factors associated with HRQoL deterioration in this period. Methods We included longitudinal HRQoL data from previously published clinical trials in glioma. The percentage of patients with stable HRQoL until progression was determined per scale and at the individual patient level (i.e. considering all scales simultaneously). We assessed time to a clinically relevant deterioration in HRQoL, expressed in deterioration-free survival and time-to-deterioration (the first including progression as an event). We also determined the association between sociodemographic and clinical factors and HRQoL deterioration in the progression-free period. Results Five thousand five hundred and thirty-nine patients with at least baseline HRQoL scores had a median time from randomization to progression of 7.6 months. Between 9-29% of the patients deteriorated before disease progression on the evaluated HRQoL scales. When considering all scales simultaneously, 47% of patients deteriorated on >= 1 scale. Median deterioration-free survival period ranged between 3.8-5.4 months, and median time-to-deterioration between 8.2-11.9 months. For most scales, only poor performance status was independently associated with clinically relevant HRQoL deterioration in the progression-free period. Conclusions HRQoL was maintained in only 53% of patients in their progression-free period, and treatment was not independently associated with this deterioration in HRQoL. Routine monitoring of the patients functioning and well-being during the entire disease course is therefore important, so that interventions can be initiated when problems are signaled., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [RP 1515]

Background Maintenance of functioning and well-being during the progression-free survival (PFS) period is important for glioma patients. This study aimed to determine whether health-related quality of life (HRQoL) can be maintained during progression-free time, and factors associated with HRQoL deterioration in this period. Methods We included longitudinal HRQoL data from previously published clinical trials in glioma. The percentage of patients with stable HRQoL until progression was determined per scale and at the individual patient level (i.e. considering all scales simultaneously). We assessed time to a clinically relevant deterioration in HRQoL, expressed in deterioration-free survival and time-to-deterioration (the first including progression as an event). We also determined the association between sociodemographic and clinical factors and HRQoL deterioration in the progression-free period. Results Five thousand five hundred and thirty-nine patients with at least baseline HRQoL scores had a median time from randomization to progression of 7.6 months. Between 9-29% of the patients deteriorated before disease progression on the evaluated HRQoL scales. When considering all scales simultaneously, 47% of patients deteriorated on >= 1 scale. Median deterioration-free survival period ranged between 3.8-5.4 months, and median time-to-deterioration between 8.2-11.9 months. For most scales, only poor performance status was independently associated with clinically relevant HRQoL deterioration in the progression-free period. Conclusions HRQoL was maintained in only 53% of patients in their progression-free period, and treatment was not independently associated with this deterioration in HRQoL. Routine monitoring of the patients functioning and well-being during the entire disease course is therefore important, so that interventions can be initiated when problems are signaled., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [RP 1515]

Background Maintenance of functioning and well-being during the progression-free survival (PFS) period is important for glioma patients. This study aimed to determine whether health-related quality of life (HRQoL) can be maintained during progression-free time, and factors associated with HRQoL deterioration in this period. Methods We included longitudinal HRQoL data from previously published clinical trials in glioma. The percentage of patients with stable HRQoL until progression was determined per scale and at the individual patient level (i.e. considering all scales simultaneously). We assessed time to a clinically relevant deterioration in HRQoL, expressed in deterioration-free survival and time-to-deterioration (the first including progression as an event). We also determined the association between sociodemographic and clinical factors and HRQoL deterioration in the progression-free period. Results Five thousand five hundred and thirty-nine patients with at least baseline HRQoL scores had a median time from randomization to progression of 7.6 months. Between 9-29% of the patients deteriorated before disease progression on the evaluated HRQoL scales. When considering all scales simultaneously, 47% of patients deteriorated on >= 1 scale. Median deterioration-free survival period ranged between 3.8-5.4 months, and median time-to-deterioration between 8.2-11.9 months. For most scales, only poor performance status was independently associated with clinically relevant HRQoL deterioration in the progression-free period. Conclusions HRQoL was maintained in only 53% of patients in their progression-free period, and treatment was not independently associated with this deterioration in HRQoL. Routine monitoring of the patients functioning and well-being during the entire disease course is therefore important, so that interventions can be initiated when problems are signaled., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [RP 1515]

Background Maintenance of functioning and well-being during the progression-free survival (PFS) period is important for glioma patients. This study aimed to determine whether health-related quality of life (HRQoL) can be maintained during progression-free time, and factors associated with HRQoL deterioration in this period. Methods We included longitudinal HRQoL data from previously published clinical trials in glioma. The percentage of patients with stable HRQoL until progression was determined per scale and at the individual patient level (i.e. considering all scales simultaneously). We assessed time to a clinically relevant deterioration in HRQoL, expressed in deterioration-free survival and time-to-deterioration (the first including progression as an event). We also determined the association between sociodemographic and clinical factors and HRQoL deterioration in the progression-free period. Results Five thousand five hundred and thirty-nine patients with at least baseline HRQoL scores had a median time from randomization to progression of 7.6 months. Between 9-29% of the patients deteriorated before disease progression on the evaluated HRQoL scales. When considering all scales simultaneously, 47% of patients deteriorated on >= 1 scale. Median deterioration-free survival period ranged between 3.8-5.4 months, and median time-to-deterioration between 8.2-11.9 months. For most scales, only poor performance status was independently associated with clinically relevant HRQoL deterioration in the progression-free period. Conclusions HRQoL was maintained in only 53% of patients in their progression-free period, and treatment was not independently associated with this deterioration in HRQoL. Routine monitoring of the patients functioning and well-being during the entire disease course is therefore important, so that interventions can be initiated when problems are signaled., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [RP 1515]

Background. Different analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions. Methods. HRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items. Results. Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item "hair loss" showed a significant and clinically relevant change (ie, >= 10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P <.001; range in change score, 0.1-6.2). Although a large proportion of patients had stable HRQoL over time (range, 27%-84%) on the patient level per scale/item, many patients deteriorated (range, 6%-43%) or improved (range, 8%-32%) on a specific scale/item. At the individual patient level, the majority of patients (86%) showed both deterioration and improvement, whereas only 1% remained stable on all scales. Conclusions. Different analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [1515]

Background. Different analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions. Methods. HRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items. Results. Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item "hair loss" showed a significant and clinically relevant change (ie, >= 10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P <.001; range in change score, 0.1-6.2). Although a large proportion of patients had stable HRQoL over time (range, 27%-84%) on the patient level per scale/item, many patients deteriorated (range, 6%-43%) or improved (range, 8%-32%) on a specific scale/item. At the individual patient level, the majority of patients (86%) showed both deterioration and improvement, whereas only 1% remained stable on all scales. Conclusions. Different analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [1515]

Background. Different analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions. Methods. HRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items. Results. Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item "hair loss" showed a significant and clinically relevant change (ie, >= 10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P <.001; range in change score, 0.1-6.2). Although a large proportion of patients had stable HRQoL over time (range, 27%-84%) on the patient level per scale/item, many patients deteriorated (range, 6%-43%) or improved (range, 8%-32%) on a specific scale/item. At the individual patient level, the majority of patients (86%) showed both deterioration and improvement, whereas only 1% remained stable on all scales. Conclusions. Different analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [1515]

Background. Different analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions. Methods. HRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items. Results. Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item "hair loss" showed a significant and clinically relevant change (ie, >= 10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P <.001; range in change score, 0.1-6.2). Although a large proportion of patients had stable HRQoL over time (range, 27%-84%) on the patient level per scale/item, many patients deteriorated (range, 6%-43%) or improved (range, 8%-32%) on a specific scale/item. At the individual patient level, the majority of patients (86%) showed both deterioration and improvement, whereas only 1% remained stable on all scales. Conclusions. Different analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [1515]

Background. Different analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions. Methods. HRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items. Results. Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item "hair loss" showed a significant and clinically relevant change (ie, >= 10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P <.001; range in change score, 0.1-6.2). Although a large proportion of patients had stable HRQoL over time (range, 27%-84%) on the patient level per scale/item, many patients deteriorated (range, 6%-43%) or improved (range, 8%-32%) on a specific scale/item. At the individual patient level, the majority of patients (86%) showed both deterioration and improvement, whereas only 1% remained stable on all scales. Conclusions. Different analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group [1515]

Background. Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients functioning. Methods. Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders. Results. Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5-10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (amp;gt;= 10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P amp;lt; 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of -12.3, P amp;lt; 0.001), independent of other factors. Conclusions. Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients functioning as measured with a self-report qu, Funding Agencies|EORTC Quality of Life Group

Background. Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients functioning. Methods. Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders. Results. Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5-10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (amp;gt;= 10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P amp;lt; 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of -12.3, P amp;lt; 0.001), independent of other factors. Conclusions. Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients functioning as measured with a self-report qu, Funding Agencies|EORTC Quality of Life Group

Background. Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients functioning. Methods. Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders. Results. Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5-10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (amp;gt;= 10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P amp;lt; 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of -12.3, P amp;lt; 0.001), independent of other factors. Conclusions. Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients functioning as measured with a self-report qu, Funding Agencies|EORTC Quality of Life Group

Background. Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients functioning. Methods. Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders. Results. Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5-10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (amp;gt;= 10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P amp;lt; 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of -12.3, P amp;lt; 0.001), independent of other factors. Conclusions. Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients functioning as measured with a self-report qu, Funding Agencies|EORTC Quality of Life Group

Background. Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients functioning. Methods. Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders. Results. Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5-10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (amp;gt;= 10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P amp;lt; 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of -12.3, P amp;lt; 0.001), independent of other factors. Conclusions. Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients functioning as measured with a self-report qu, Funding Agencies|EORTC Quality of Life Group

Objective: Prognostic value of health-related quality of life (HRQoL) data may be important to inform patients in clinical practice and to guide clinical decision-making. Our study investigated the added prognostic value of HRQoL for overall survival (OS) and progression-free survival (PFS) in a large heterogeneous sample of glioma patients, besides known prognostic factors. Methods: We included individual baseline data from previously published randomised controlled trials (RCTs) in glioma patients in which HRQoL was assessed through the European Organisation for Research and Treatment of Cancer QLQ-C30 and QLQ-BN20 questionnaires. Multivariable Cox regression models (stratified for newly diagnosed versus recurrent disease) were constructed, first with clinical variables (age, sex, tumour type, performance status, allocated treatment and extent of resection) only and subsequently with HRQoL variables added, separately for OS and PFS. The added prognostic value of HRQoL was calculated using C-indices. Results: Baseline HRQoL and clinical data from 15 RCTs were included, comprising 5217 patients. In the model including both clinical and HRQoL variables, better cognitive and role functioning and less motor dysfunction were independently associated with longer OS, whereas better role and cognitive functioning, less nausea and vomiting and more appetite loss were independently associated with prolonged PFS. However, C-indices indicated only a small prognostic improvement of the models for OS and PFS when adding HRQoL to the clinical prognostic variables (+1.1% for OS and +.7% for PFS). Conclusion: Our findings demonstrate that several baseline HRQoL variables are independently prognostic for OS and PFS, yet the added value of HRQoL to the known clinical prognostic variables was small. (C) 2019 Elsevier Ltd. All rights reserved., Funding Agencies|European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group

Background. Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients functioning. Methods. Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders. Results. Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5-10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (amp;gt;= 10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P amp;lt; 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of -12.3, P amp;lt; 0.001), independent of other factors. Conclusions. Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients functioning as measured with a self-report qu, Funding Agencies|EORTC Quality of Life Group