Relationship between symptom burden and health status: analysis of the MDASI-BT and EQ-5D

High costs, low quality of life, reduced survival, and room for improving treatment: an analysis of burden and unmet needs in glioma

Gliomas are a group of heterogeneous tumors that account for substantial morbidity, mortality, and costs to patients and healthcare systems globally. Survival varies considerably by grade, histology, biomarkers, and genetic alterations such as IDH mutations and MGMT promoter methylation, and treatment, but is poor for some grades and histologies, with many patients with glioblastoma surviving less than a year from diagnosis. The present review provides an introduction to glioma, including its classification, epidemiology, economic and humanistic burden, as well as treatment options. Another focus is on treatment recommendations for IDH-mutant astrocytoma, IDH-mutant oligodendroglioma, and glioblastoma, which were synthesized from recent guidelines. While recommendations are nuanced and reflect the complexity of the disease, maximum safe resection is typically the first step in treatment, followed by radiotherapy and/or chemotherapy using temozolomide or procarbazine, lomustine, and vincristine. Immunotherapies and targeted therapies currently have only a limited role due to disappointing clinical trial results, including in recurrent glioblastoma, for which the nitrosourea lomustine remains the de facto standard of care. The lack of treatment options is compounded by frequently suboptimal clinical practice, in which patients do not receive adequate therapy after resection, including delayed, shortened, or discontinued radiotherapy and chemotherapy courses due to treatment side effects. These unmet needs will require significant efforts to address, including a continued search for novel treatment options, increased awareness of clinical guidelines, improved toxicity management for chemotherapy, and the generation of additional and more robust clinical and health economic evidence.

Discovery of clinical and demographic determinants of symptom burden in primary brain tumor patients using network analysis and unsupervised clustering

Background

Precision health approaches to managing symptom burden in primary brain tumor (PBT) patients are imperative to improving patient outcomes and quality of life, but require tackling the complexity and heterogeneity of the symptom experience. Network Analysis (NA) can identify complex symptom co-severity patterns, and unsupervised clustering can unbiasedly stratify patients into clinically relevant subgroups based on symptom patterns. We combined these approaches in a novel study seeking to understand PBT patients' clinical and demographic determinants of symptom burden.

Methods

MDASI-BT symptom severity data from a two-institutional cohort of 1128 PBT patients were analyzed. Gaussian Graphical Model networks were constructed for the all-patient cohort and subgroups identified by unsupervised clustering based on co-severity patterns. Network characteristics were analyzed and compared using permutation-based statistical tests.

Results

NA of the all-patient cohort revealed 4 core dimensions that drive the overall symptom burden of PBT patients: Cognitive, physical, focal neurologic, and affective. Fatigue/drowsiness was identified as pivotal to the symptom experience based on the network characteristics. Unsupervised clustering discovered 4 patient subgroups: PC1 (n = 683), PC2 (n = 244), PC3 (n = 92), and PC4 (n = 109). Moderately accurate networks could be constructed for PC1 and PC2. The PC1 patients had the highest interference scores among the subgroups and their network resembled the all-patient network. The PC2 patients were older and their symptom burden was driven by cognitive symptoms.

Conclusions

In the future, the proposed framework might be able to prioritize symptoms for targeting individual patients, informing more personalized symptom management.

Characteristics of health-related quality of life and related factors in patients with brain tumors treated with rehabilitation therapy

Background

Rehabilitation therapy during hospitalization is effective in improving activities of daily living (ADL) and physical function in patients with brain tumors. However, there are few studies on the effect of rehabilitation therapy on health-related quality of life (HRQOL) in patients with brain tumors. Additionally, the EuroQol-5Dimension-5Level (EQ-5D-5L) index score has not been reported as an outcome. This study aimed to investigate the HRQOL of patients with brain tumors who underwent rehabilitation therapy and investigated the factors affecting the EQ-5D-5L index score from various perspectives, including various brain tumor type and recurrence. In addition, we examined the relationship between the EQ-5D-5L index score, disease-specific HRQOL scale, and ADL.

Methods

Patients with brain tumors who underwent treatment and rehabilitation at Single tertiary care academic medical center were included in this cross-sectional study. We used the EQ-5D-5L, European Organisation for Research and Treatment of Cancer (EORTC) quality of life questionnaire core 30, and EORTC quality of life questionnaire brain cancer module to evaluate HRQOL. ADL were assessed using the functional independence measure (FIM). The relationship between each HRQOL assessment score and the FIM was analyzed, and the influence of related factors was assessed by multiple regression analysis.

Results

This study included 76 patients. The EQ-5D-5L index score was 0.689 for all patients with brain tumors and 0.574 for those with glioblastomas, which was the lowest value. There was a moderate correlation between the EQ-5D-5L index score and FIM (r = 0.627, p < 0.001). In addition, the EQ-5D-5L index score was significantly correlated with most of the items of the disease-specific HRQOL scale. Multiple regression analysis revealed that glioblastoma histology (coefficient: − 0.373, p = 0.005) and recurrence (coefficient: − 0.273, p = 0.020) were independent factors affecting the EQ-5D-5L index score.

Conclusions

Patients with glioblastoma undergoing rehabilitation have reduced HRQOL, which was influenced by glioblastoma histology and recurrence.

Laser Ablation of Abnormal Neurological Tissue Using Robotic NeuroBlate System (LAANTERN): 12-Month Outcomes and Quality of Life After Brain Tumor Ablation

BACKGROUND

Laser Ablation of Abnormal Neurological Tissue using Robotic NeuroBlate System (LAANTERN) is an ongoing multicenter prospective NeuroBlate (Monteris Medical) LITT (laser interstitial thermal therapy) registry collecting real-world outcomes and quality-of-life (QoL) data.

OBJECTIVE

To compare 12-mo outcomes from all subjects undergoing LITT for intracranial tumors/neoplasms.

METHODS

Demographics, intraprocedural data, adverse events, QoL, hospitalizations, health economics, and survival data are collected; standard data management and monitoring occur.

RESULTS

A total of 14 centers enrolled 223 subjects; the median follow-up was 223 d. There were 119 (53.4%) females and 104 (46.6%) males. The median age was 54.3 yr (range 3-86) and 72.6% had at least 1 baseline comorbidity. The median baseline Karnofsky Performance Score (KPS) was 90. Of the ablated tumors, 131 were primary and 92 were metastatic. Most patients with primary tumors had high-grade gliomas (80.9%). Patients with metastatic cancer had recurrence (50.6%) or radiation necrosis (40%). The median postprocedure hospital stay was 33.4 h (12.7-733.4). The 1-yr estimated survival rate was 73%, and this was not impacted by disease etiology. Patient-reported QoL as assessed by the Functional Assessment of Cancer Therapy-Brain was stabilized postprocedure. KPS declined by an average of 5.7 to 10.5 points postprocedure; however, 50.5% had stabilized/improved KPS at 6 mo. There were no significant differences in KPS or QoL between patients with metastatic vs primary tumors.

CONCLUSION

Results from the ongoing LAANTERN registry demonstrate that LITT stabilizes and improves QoL from baseline levels in a malignant brain tumor patient population with high rates of comorbidities. Overall survival was better than anticipated for a real-world registry and comparative to published literature.

Economic evaluation of GPs' direct access to computed tomography for identification of brain tumours

BACKGROUND

When GPs suspect a brain tumour, a referral for specialist assessment and subsequent brain imaging is generally the first option. NICE has recommended that GPs have rapid direct access to brain imaging for adults with progressive sub-acute loss of central nervous function; however, no studies have evaluated the cost-effectiveness.

METHODS

We developed a cost-effectiveness model based on data from one region of the UK with direct access computed tomography (DACT), routine data from GP records and the literature, to explore whether unrestricted DACT for patients with suspected brain tumour might be more cost-effective than criteria-based DACT or no DACT.

RESULTS

Although criteria-based DACT allows some patients without brain tumour to avoid imaging, our model suggests this may increase costs of diagnosis due to non-specific risk criteria and high costs of diagnosing or 'ruling out' brain tumours by other pathways. For patients diagnosed with tumours, differences in outcomes between the three diagnostic strategies are small.

CONCLUSIONS

Unrestricted DACT may reduce diagnostic costs; however, the evidence is not strong and further controlled studies are required. Criteria-based access to CT for GPs might reduce demand for DACT, but imperfect sensitivity and specificity of current risk stratification mean that it will not necessarily be cost-effective.

An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values

BACKGROUND

Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values (HSUVs) from data obtained from another health-related quality of life (HRQoL) measure. There have been several methodological developments in this area since a previous review up to 2007.

OBJECTIVE

To provide an updated review of all mapping studies that map from HRQoL measures to target generic preference-based measures (EQ-5D measures, SF-6D, HUI measures, QWB, AQoL measures, 15D/16D/17D, CHU-9D) published from January 2007 to October 2018.

DATA SOURCES

A systematic review of English language articles using a variety of approaches: searching electronic and utilities databases, citation searching, targeted journal and website searches.

STUDY SELECTION

Full papers of studies that mapped from one health measure to a target preference-based measure using formal statistical regression techniques.

DATA EXTRACTION

Undertaken by four authors using predefined data fields including measures, data used, econometric models and assessment of predictive ability.

RESULTS

There were 180 papers with 233 mapping functions in total. Mapping functions were generated to obtain EQ-5D-3L/EQ-5D-5L-EQ-5D-Y (n = 147), SF-6D (n = 45), AQoL-4D/AQoL-8D (n = 12), HUI2/HUI3 (n = 13), 15D (n = 8) CHU-9D (n = 4) and QWB-SA (n = 4) HSUVs. A large number of different regression methods were used with ordinary least squares (OLS) still being the most common approach (used ≥ 75% times within each preference-based measure). The majority of studies assessed the predictive ability of the mapping functions using mean absolute or root mean squared errors (n = 192, 82%), but this was lower when considering errors across different categories of severity (n = 92, 39%) and plots of predictions (n = 120, 52%).

CONCLUSIONS

The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions.