Factors associated with health-related quality of life (HRQoL) deterioration in glioma patients during the progression-free survival period.

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.

Research Objectives, Statistical Analyses and Interpretation of Health-Related Quality of Life Data in Glioma Research: A Systematic Review.

BACKGROUND: Health-related quality of life (HRQoL) has become an increasingly important patient-reported outcome in glioma studies. Ideally, collected HRQoL data should be exploited to the full, with proper analytical methods. This systematic review aimed to provide an overview on how HRQoL data is currently evaluated in glioma studies, focusing on the research objectives and statistical analyses of HRQoL data. METHODS: A systematic literature search in the databases PubMed, Embase, Web of Science and Cochrane was conducted up to 5 June 2020. Articles were selected based on predetermined inclusion criteria and information on study design, HRQoL instrument, HRQoL research objective and statistical methods were extracted. RESULTS: A total of 170 articles describing 154 unique studies were eligible, in which 17 different HRQoL instruments were used. HRQoL was the primary outcome in 62% of the included articles, and 51% investigated ≥1 research question with respect to HRQoL, for which various analytical methods were used. In only 42% of the articles analyzing HRQoL results over time, the minimally clinical important difference was reported and interpreted. Eighty-six percent of articles reported HRQoL results at a group level only, and not at the individual patient level. CONCLUSION: Currently, the assessment and analysis of HRQoL outcomes in glioma studies is highly variable. Opportunities to maximize information obtained with HRQoL data include appropriate and complementary analyses at both the group and individual level, comprehensive reporting of HRQoL results in separate articles or supplementary material, and adherence to existing guidelines about the assessment, analysis and reporting of patient-reported outcomes.

Measuring change in health-related quality of life: the impact of different analytical methods on the interpretation of treatment effects in glioma patients.

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.

Calculating the net clinical benefit in neuro-oncology clinical trials using two methods: quality-adjusted survival effect sizes and joint modeling.

BACKGROUND: Two methods combining survival and health-related quality of life (HRQoL) data in glioma trials to calculate the "net clinical benefit" were evaluated: Quality-adjusted effect sizes (QASES) and joint modeling (JM). METHODS: The net clinical benefit in two trials was calculated as proof of concept for other trials. With the QASES method, effect sizes for differences in progression-free survival (PFS) or overall survival (OS) and HRQoL between the experimental arm and standard treatment arm were calculated, while the relative emphasis placed on survival/HRQoL varied. JM allows simultaneous modeling of HRQoL and OS/PFS. RESULTS: In the EORTC 26951 trial, combined radiochemotherapy significantly prolonged OS (difference 11.7 months), but also resulted in more patients experiencing clinically relevant worsening (≥10 points) in appetite loss and nausea/vomiting shortly after treatment. Using QASES, the survival benefit of additional procarbazine, lomustine, and vincristine (PCV) decreased from 42.3 months to 29.5 and 28.2 months when accounting for appetite loss and nausea/vomiting, respectively. JM analyses resulted in a loss of the beneficial effect of additional PCV between 13% and 24% when adjusting for different HRQoL parameters. The EORTC 22033 trial showed no significant PFS difference between radiotherapy or temozolomide alone (46 vs 39 months), nor clinically relevant differences in HRQoL. JM analyses also showed no significant association between PFS and HRQoL scales/items, whereas QASES showed that temozolomide alone was more favorable when considering symptom burden (47-49 instead of 39 months). CONCLUSIONS: Both methods resulted in different outcomes, but adjusting for the impact of treatment on HRQoL resulted in theoretically reduced survival benefits.

Symptom clusters in newly diagnosed glioma patients: which symptom clusters are independently associated with functioning and global health status?

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 (≥10 points difference) physical, role, and social functioning (betas ranged from -11.3 to -15.9, all P < 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 < 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 questionnaire.

Treatment of cognitive deficits in brain tumour patients: current status and future directions.

PURPOSE OF REVIEW: Increased life expectancy in brain tumour patients had led to the need for strategies that preserve and improve cognitive functioning, as many patients suffer from cognitive deficits. The tumour itself, as well as antitumor treatment including surgery, radiotherapy and chemotherapy, supportive treatment and individual patient factors are associated with cognitive problems. Here, we review the recent literature on approaches that preserve and improve cognitive functioning, including pharmacological agents and rehabilitation programs. RECENT FINDINGS: Minimizing cognitive dysfunction and improving cognitive functioning in brain tumour patients may be achieved both by preserving cognitive functioning during antitumor treatment, including techniques such as awake brain surgery, less invasive radiation therapies such as stereotactic radiotherapy and proton therapy, as well as with interventions including cognitive rehabilitation programmes. Novel rehabilitation programs including computer-based cognitive rehabilitation therapy (CRT) programmes that can be adjusted to the specific patient needs and can be administered at home are promising. Furthermore, personalized/precision medicine approaches to identify patients who are at risk for cognitive decline may facilitate effective treatment strategies in the future. SUMMARY: Cognitive functioning has gained greater awareness in the neuro-oncological community, and methods to preserve and improve cognitive functioning have been explored. Rehabilitation programmes for brain tumour patients should be further developed and referred to in clinical practice.

Fatigue in patients with low grade glioma: systematic evaluation of assessment and prevalence.

Fatigue is the most prevalent and disabling symptom in cancer patients. Yet, scientific literature on this topic is scarce and reports disparate results. This study systematically reviews how fatigue is assessed in patients with low-grade glioma and evaluates its prevalence in LGG patients. A systematic literature search was performed in PubMed, Embase and PsychINFO for articles reporting on fatigue in patients with LGG. Two reviewers independently extracted data from selected articles. Inclusion criteria were: (1) patients with suspected or confirmed LGG; (2) fatigue was assessed as primary or secondary outcome measure; (3) age≥ 18 years; (4) full-length article written in English or Dutch. In total, 19 articles were selected, including 971 patients. Seven self-assessment instruments were identified. Prevalence rates ranged from 39 to 77%. Fatigue was found to be a common side effect of treatment. The prevalence rates ranged from 20 to 76% when fatigue was reported as a mild or moderate side effect and fatigue was prevalent in 4% when reported as a severe side effect. Fatigue is a common problem in LGG patients that warrants more therapeutic and scientific attention. Gaining deeper insight in the underlying mechanisms of fatigue is essential in targeting therapy to individual patients.