Glioblastoma treatment patterns, survival, and healthcare resource use in real-world clinical practice in the USA

Extraction of Unstructured Electronic Health Records to Evaluate Glioblastoma Treatment Patterns

PURPOSE

Data on lines of therapy (LOTs) for cancer treatment are important for clinical oncology research, but LOTs are not explicitly recorded in electronic health records (EHRs). We present an efficient approach for clinical data abstraction and a flexible algorithm to derive LOTs from EHR-based medication data on patients with glioblastoma multiforme (GBM).

METHODS

Nonclinicians were trained to abstract the diagnosis of GBM from EHRs, and their accuracy was compared with abstraction performed by clinicians. The resulting data were used to build a cohort of patients with confirmed GBM diagnosis. An algorithm was developed to derive LOTs using structured medication data, accounting for the addition and discontinuation of therapies and drug class. Descriptive statistics were calculated and time-to-next-treatment (TTNT) analysis was performed using the Kaplan-Meier method.

RESULTS

Treating clinicians as the gold standard, nonclinicians abstracted GBM diagnosis with a sensitivity of 0.98, specificity 1.00, positive predictive value 1.00, and negative predictive value 0.90, suggesting that nonclinician abstraction of GBM diagnosis was comparable with clinician abstraction. Of 693 patients with a confirmed diagnosis of GBM, 246 patients contained structured information about the types of medications received. Of them, 165 (67.1%) received a first-line therapy (1L) of temozolomide, and the median TTNT from the start of 1L was 179 days.

CONCLUSION

We described a workflow for extracting diagnosis of GBM and LOT from EHR data that combines nonclinician abstraction with algorithmic processing, demonstrating comparable accuracy with clinician abstraction and highlighting the potential for scalable and efficient EHR-based oncology research.

Preclinical models of glioblastoma: limitations of current models and the promise of new developments

Glioblastoma (GBM) is the most common and aggressive primary brain tumour, yet little progress has been made towards providing better treatment options for patients diagnosed with this devastating condition over the last few decades. The complex nature of the disease, heterogeneity, highly invasive potential of GBM tumours and until recently, reduced investment in research funding compared with other cancer types, are contributing factors to few advancements in disease management. Survival rates remain low with less than 5% of patients surviving 5 years. Another important contributing factor is the use of preclinical models that fail to fully recapitulate GBM pathophysiology, preventing efficient translation from the lab into successful therapies in the clinic. This review critically evaluates current preclinical GBM models, highlighting advantages and disadvantages of using such models, and outlines several emerging techniques in GBM modelling using animal-free approaches. These novel approaches to a highly complex disease such as GBM show evidence of a more truthful recapitulation of GBM pathobiology with high reproducibility. The resulting advancements in this field will offer new biological insights into GBM and its aetiology with potential to contribute towards the development of much needed improved treatments for GBM in future.

Survival, costs, and health care resource use by line of therapy in US Medicare patients with newly diagnosed glioblastoma: a retrospective observational study

BACKGROUND

Glioblastoma (GBM) is associated with poor prognosis, large morbidity burden, and limited treatment options. This analysis evaluated real-world treatment patterns, overall survival, resource use, and costs among Medicare patients with GBM.

METHODS

This retrospective observational study evaluated Medicare patients age 66 years or older with newly diagnosed GBM using the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data from 2007 through 2013. Patients were followed from diagnosis to death or end of follow-up. An algorithm defined treatment patterns as lines of therapy (LOTs). The Kaplan-Meier method was used to estimate overall survival for the full sample as well as by LOT, surgical resection, Charlson Comorbidity Index (CCI), tumor size, and age. Resource use and costs during the follow-up period were reported in terms of total and per-patient-per-month (PPPM) estimates.

RESULTS

A total of 4308 patients with GBM were identified (median age, 74 years; CCI of 0, 52%). The most commonly used first LOT was temozolomide (82%), whereas chemotherapy + bevacizumab was most prevalent for second-line (42%) and third-line (58%) therapy. The median overall survival was 5.9 months for resected patients and 3 months for unresected patients, with considerable heterogeneity depending on patient characteristics. A great proportion of patients had claims for an ICU admission (86.2%), skilled nursing facility (76.9%), and home health (56.0%) in the postdiagnosis period. The cumulative mean cost was $95 377 per patient and $18 053 PPPM, mostly attributed to hospitalizations.

CONCLUSIONS

Limited treatment options, poor survival, and economic burden emphasize the need for novel interventions to improve care for Medicare patients with GBM.

A Real-World Claims Analysis of Costs and Patterns of Care in Treated Patients with Glioblastoma Multiforme in the United States

BACKGROUND

Patients with glioblastoma multiforme (GBM) have a poor prognosis and high likelihood of recurrence. Routine care for incident cases in the United States involves surgical resection, followed by radiation therapy (RT) with concurrent and adjuvant temozolomide. Real-world data reporting the treatments and health care burden associated with GBM are limited.

OBJECTIVE

To assess patterns of care, health care resource utilization (HCRU), and costs associated with treatment of GBM in the United States.

METHODS

This study is a retrospective claims database analysis. Adult patients with a GBM diagnosis (index date) between January 1, 2010, and June 30, 2016, who had undergone brain surgery within 90 days of the index date, had received temozolomide and/or RT up to 90 days after index date, and had at least 6 months of continuous enrollment before the index date, were identified. Patients were excluded if they had (a) another primary cancer within 6 months pre-index, (b) secondary brain metastases, or (c) received temozolomide and/or RT pre-index. Baseline characteristics, treatments, HCRU, and costs were reported. First-line therapy began upon first receipt of RT and/or temozolomide after index date; second-line therapy began when a new drug was added > 28 days after initiation of first-line therapy or when there was a treatment gap > 90 days. Treatment regimens, duration of treatment (corrected group prognosis method), HCRU, and costs were reported descriptively in the 0- to 6-month and 7- to 12-month periods following initiation of first-line and second-line therapy.

RESULTS

Baseline characteristics were comparable between patients receiving temozolomide and/or RT. Patients receiving RT without chemotherapy tended to be older, be retired, and have more baseline comorbidities. Of the 4,071 patients receiving first-line therapy for GBM, most (73.0%) received temozolomide + RT; 24.4% received RT; and 2.5% received temozolomide monotherapy. Of those receiving first-line therapy, 1,283 (31.5%) patients subsequently received second-line therapy: 39.4% received bevacizumab monotherapy; 28.9% received bevacizumab combination therapy (temozolomide, 45.2% of patients; irinotecan, 24.3%; and temozolomide + lomustine, 15.4%); 15.5% received temozolomide monotherapy; and 13.7% received other systemic cancer therapies. The proportion of patients with hospitalizations increased from 2.9% (4-6 months pre-index) to 20.8% in the 3 months before the index date (likely due to diagnostic procedures) and 28.1% in the first 6 months after index (likely due to surgery) and then decreased to 13.3% in the 7- to 12-month period after index. Mean total per-patient costs at 6 and 12 months were $117,325 and $162,550 (first line) and $126,128 and $243,833 (second line). Costs in all time periods were largely driven by costs of RT/systemic cancer therapy.

CONCLUSIONS

Most patients with newly diagnosed GBM received treatment according to recommendations. However, relatively few patients received second-line therapy, and the HCRU burden and costs associated with both lines of therapy were substantial. Novel therapies for GBM are required to improve treatment options and outcomes in these patients.

DISCLOSURES

This study was funded by Bristol-Myers Squibb (Princeton Pike, NJ). Neither honoraria nor payments were provided for authorship. Norden received consultancy fees relating to this study from Bristol-Myers Squibb. Dastani, Korytowsky, Le, Singh, and You are employees of Bristol-Myers Squibb. Dastani and Korytowsky are shareholders of Bristol-Myers Squibb. Bobiak was an employee of Bristol-Myers Squibb at the time of this study. Preliminary data from this study were previously presented at the International Society for Pharmacoeconomics and Outcomes Research 22nd Annual International Meeting in Boston, MA, May 20-24, 2017.

Single-institution retrospective review of patients with recurrent glioblastoma treated with bevacizumab in clinical practice

BACKGROUND AND AIMS

This retrospective review of patients with recurrent glioblastoma treated at the Preston Robert Tisch Brain Tumor Center investigated treatment patterns, survival, and safety with bevacizumab in a real-world setting.

METHODS

Adult patients with glioblastoma who initiated bevacizumab at disease progression between January 1, 2009, and May 14, 2012, were included. A Kaplan-Meier estimator was used to describe overall survival (OS), progression-free survival (PFS), and time to greater than or equal to 20% reduction in Karnofsky Performance Status (KPS). The effect of baseline demographic and clinical factors on survival was examined using a Cox proportional hazards model. Adverse event (AE) data were collected.

RESULTS

Seventy-four patients, with a median age of 59 years, were included in this cohort. Between bevacizumab initiation and first failure, defined as the first disease progression after bevacizumab initiation, biweekly bevacizumab and bevacizumab/irinotecan were the most frequently prescribed regimens. Median duration of bevacizumab treatment until failure was 6.4 months (range, 0.5-58.7). Median OS and PFS from bevacizumab initiation were 11.1 months (95% confidence interval [CI], 7.3-13.4) and 6.4 months (95% CI, 3.9-8.5), respectively. Median time to greater than or equal to 20% reduction in KPS was 29.3 months (95% CI, 13.8-∞). Lack of corticosteroid usage at the start of bevacizumab therapy was associated with both longer OS and PFS, with a median OS of 13.2 months (95% CI, 8.6-16.6) in patients who did not initially require corticosteroids versus 7.2 months (95% CI, 4.8-12.5) in those who did (P = 0.0382, log-rank), while median PFS values were 8.6 months (95% CI, 4.6-9.7) and 3.7 months (95% CI, 2.7-6.6), respectively (P = 0.0243, log-rank). Treatment failure occurred in 70 patients; 47 of whom received salvage therapy, and most frequently bevacizumab/carboplatin (7/47; 14.9%). Thirteen patients (18%) experienced a grade 3 AE of special interest for bevacizumab.

CONCLUSIONS

Treatment patterns and outcomes for patients with recurrent glioblastoma receiving bevacizumab in a real-world setting were comparable with those reported in prospective clinical trials.

Survival in elderly glioblastoma patients treated with bevacizumab-based regimens in the United States

BACKGROUND

The efficacy of bevacizumab (BEV) in elderly patients with glioblastoma remains unclear. We evaluated the effect of BEV on survival in this patient population using the Survival, Epidemiology, and End Results (SEER)-Medicare database.

METHODS

This retrospective, cohort study analyzed SEER-Medicare data for patients (aged ≥66 years) diagnosed with glioblastoma from 2006 to 2011. Two cohorts were constructed: one comprised patients who had received BEV (BEV cohort); the other comprised patients who had received any anticancer treatment other than BEV (NBEV cohort). The primary analysis used a multivariate Cox proportional hazards model to compare overall survival in the BEV and NBEV cohorts with initiation of BEV as a time-dependent variable, adjusting for potential confounders (age, gender, Charlson comorbidity index, region, race, radiotherapy after initial surgery, and diagnosis of coronary artery disease). Sensitivity analyses were conducted using landmark survival, propensity score modeling, and the impact of poor Karnofsky Performance Status.

RESULTS

We identified 2603 patients (BEV, n = 597; NBEV, n = 2006). In the BEV cohort, most patients were Caucasian males and were younger with fewer comorbidities and more initial resections. In the primary analysis, the BEV cohort showed a lower risk of death compared with the NBEV cohort (hazard ratio, 0.80; 95% confidence interval, 0.72-0.89; P < .01). The survival benefit of BEV appeared independent of the number of temozolomide cycles or frontline treatment with radiotherapy and temozolomide.

CONCLUSION

BEV exposure was associated with a lower risk of death, providing evidence that there might be a potential benefit of BEV in elderly patients with glioblastoma.

Overall survival in patients with glioblastoma before and after bevacizumab approval

OBJECTIVE

Glioblastoma (GBM) is an aggressive disease with limited therapeutic options. While bevacizumab was approved in 2009 for the treatment of patients with progressive GBM, its impact on overall survival (OS) remains unclear. Using US population-based cancer registry data (SEER), this study compared OS of patients diagnosed with GBM before and after bevacizumab approval.

METHODS

Adult patients from SEER with a GBM diagnosis were divided into two cohorts: patients diagnosed in 2006-2008 (pre-bevacizumab cohort, n = 6,120) and patients diagnosed in 2010-2012 (post-bevacizumab cohort, n = 6,753). Patients were included irrespective of the treatments received. OS post-diagnosis was compared between the study cohorts utilizing Kaplan-Meier analyses and multivariate Cox proportional hazards regression.

RESULTS

Among 12,873 patients with GBM, the median age was 62 years, 41% were women, 31% underwent gross total resection, and 75% received radiation therapy. Survival was stable within the 2006-2008 period (median survival = 9 months for each year), but increased after year 2009 (median survival = 10 and 11 months for years 2010/2011 and 2012, respectively). The adjusted hazard of death was significantly lower in the post-bevacizumab approval cohort (hazard ratio = 0.91, p < .01).

CONCLUSIONS

The results of this large population-based study suggested an improvement in OS among patients with a GBM diagnosis in 2010-2012 compared to 2006-2008. While the cause of this improvement cannot be proven in a retrospective analysis, the timing of the survival increase coincides with the approval of bevacizumab for the treatment of patients with progressive GBM, indicating a possible benefit of bevacizumab in this population.

Changes in Cognition and Decision Making Capacity Following Brain Tumour Resection: Illustrated with Two Cases

Changes in cognition, behaviour and emotion frequently occur in patients with primary and secondary brain tumours. This impacts the ability to make considered decisions, especially following surgical resection, which is often overlooked in the management of patients. Moreover, the impact of cognitive deficits on decision making ability affects activities of daily living and functional independence. The assessment process to ascertain decision making capacity remains a matter of debate. One avenue for evaluating a patient’s ability to make informed decisions in the context of brain tumour resection is neuropsychological assessment. This involves the assessment of a wide range of cognitive abilities on standard measurement tools, providing a robust approach to ascertaining capacity. Evidence has shown that a comprehensive and tailored neuropsychological assessment has greater sensitivity than brief cognitive screening tools to detect subtle and/or specific cognitive deficits in brain tumours. It is the precise nature and severity of any cognitive deficits that determines any implications for decision making capacity. This paper focuses on cognitive deficits and decision making capacity following surgical resection of both benign and malignant, and primary and secondary brain tumours in adult patients, and the implications for patients’ ability to consent to future medical treatment and make decisions related to everyday activities.

Multiscale Modeling of Glioblastoma Suggests that the Partial Disruption of Vessel/Cancer Stem Cell Crosstalk Can Promote Tumor Regression Without Increasing Invasiveness

OBJECTIVE

In glioblastoma, the crosstalk between vascular endothelial cells (VECs) and glioma stem cells (GSCs) has been shown to enhance tumor growth. We propose a multiscale mathematical model to study this mechanism, explore tumor growth under various initial and microenvironmental conditions, and investigate the effects of blocking this crosstalk.

METHODS

We develop a hybrid continuum-discrete model of highly organized vascularized tumors. VEC-GSC crosstalk is modeled via vascular endothelial growth factor (VEGF) production by tumor cells and by secretion of soluble factors by VECs that promote GSC self-renewal and proliferation.

RESULTS

VEC-GSC crosstalk increases both tumor size and GSC fraction by enhancing GSC activity and neovascular development. VEGF promotes vessel formation, and larger VEGF sources typically increase vessel numbers, which enhances tumor growth and stabilizes the tumor shape. Increasing the initial GSC fraction has a similar effect. Partially disrupting the crosstalk by blocking VEC secretion of GSC promoters reduces tumor size but does not increase invasiveness, which is in contrast to antiangiogenic therapies, which reduce tumor size but may significantly increase tumor invasiveness.

SIGNIFICANCE

Multiscale modeling supports the targeting of VEC-GSC crosstalk as a promising approach for cancer therapy.

Hyaluronic acid-conjugated liposome nanoparticles for targeted delivery to CD44 overexpressing glioblastoma cells

Glioblastoma Multiforme (GBM) is a highly prevalent and deadly brain malignancy characterized by poor prognosis and restricted disease management potential. Despite the success of nanocarrier systems to improve drug/gene therapy for cancer, active targeting specificity remains a major hurdle for GBM. Additionally, since the brain is a multi-cell type organ, there is a critical need to develop an approach to distinguish between GBM cells and healthy brain cells for safe and successful treatment. In this report, we have incorporated hyaluronic acid (HA) as an active targeting ligand for GBM. To do so, we employed HA conjugated liposomes (HALNPs) to study the uptake pathway in key cells in the brain including primary astrocytes, microglia, and human GBM cells. We observed that the HALNPs specifically target GBM cells over other brain cells due to higher expression of CD44 in tumor cells. Furthermore, CD44 driven HALNP uptake into GBM cells resulted in lysosomal evasion and increased efficacy of Doxorubicin, a model anti-neoplastic agent, while the astrocytes and microglia cells exhibited extensive HALNP-lysosome co-localization and decreased antineoplastic potency. In summary, novel CD44 targeted lipid based nanocarriers appear to be proficient in mediating site-specific delivery of drugs via CD44 receptors in GBM cells, with an improved therapeutic margin and safety.