P11.41.B The Cost of Inpatient Care For Adult Primary Brain Tumour Patients in England

Background

Primary brain tumours are rare, but are the cause of the most life-years lost of any cancer. Given their poor prognosis, questions about their treatment and care costs are important especially in publicly-funded healthcare systems. There is currently very little robust data on the cost of care for brain tumour patients. Here we present up-to-date estimations of the direct inpatient care costs of all adult primary brain tumour patients in England, with a specific breakdown of costs attributed to cranial glioblastomas and cranial meningiomas, the commonest primary brain tumours.

Material and Methods

GlioCova uses a linked English national cancer data on over 50,000 adult primary brain tumour patients diagnosed between 2013-2018, with data on secondary healthcare activities three months before diagnosis - the last three months of 2012, and follow-up data after diagnosis - up to the last admission of 2019. We examined inpatient care with a breakdown of costs attributed to different treatment types: neurosurgery, chemotherapy and radiotherapy. We used the NHS HRG4+ Reference Costs Grouper 2017/2018 to assign costs matched from the National Schedule of Reference Costs 2017/2018. We converted all values to 2021 using the Health CPI Index.

Results

There were a total of 51,775 adult primary brain tumour patients diagnosed in England in the 6 year period between 2013 and 2018. 48,608 of these were admitted to hospital between the last three months of 2012 and the end of 2019, of which we were able to assign costs to 47,521 patients (98%). Total inpatient costs for the whole brain tumour cohort were over £973 million during the time period (34% attributed to inpatient care for neurosurgery, chemotherapy, and radiotherapy). 14,691 (31%) of patients were diagnosed with a cranial glioblastoma, and 9,501 (20%) of patients were diagnosed with a cranial meningioma. Total inpatient costs were £349 million and £163 million for glioblastoma and meningioma respectively, with 34% again devoted to direct treatment costs.

Conclusion

The estimated direct inpatient care costs for all 51,775 primary brain tumour patients diagnosed in England between 2013 and 2018 were nearly £1 billion (£166 million/year cohort), 2/3 of which was not for direct treatment. This does not include outpatient chemotherapy and radiotherapy costs, other outpatient appointments, patient out-of-pocket costs, primary care, social care, or end-of-life care costs. Future work will examine variation in care and costs and extend the analysis to include outpatients. We hope these data will help make an economic argument for improving care for brain tumour patients. More information on GlioCova: https://blogs.imperial.ac.uk/gliocova/about-gliocova/.

P08.13.A CaPaBLE - Assessing the Patient Generated Index Methodology in High Grade Glioma Patients and Caregivers

Background

CaPaBLE tests the feasibility and acceptability of assessing quality of life (QoL) using the patient-, or caregiver-generated index (PGI/CaGI) methodology in patients with HGG and their caregivers.

Material and Methods

CaPaBLE, (https://www.isrctn.com/ISRCTN45555598), followed patients and/ or their caregivers up to 6 months. Standard measures for patients were EORTC QLQ-C30/BN20, for caregivers the CarGOQOL questionnaire. The QoL topics raised through PGI/CaGI have been coded to the most relevant domain from their respective standard measure for an initial assessment of concordance.

Results

36 patients, 24 caregivers recruited to study; completing an average of 3 study assessment timepoints. PGI and CaGI generated 240 and 160 topics respectively. Patient concerns most frequently coded to EORTC domain of Role Functioning; Caregiver concerns mostly coded to CarGOQOL domain of Burden. Other topics frequently raised by patients such as the driving and sex life, and future planning by caregivers are not specifically raised in standard questionnaires.

Conclusion

Nearly all topics raised by patients and caregivers were mapped to the domains of their respective standard QoL measure. However, almost half of all topics raised by patients and caregivers mapped to a minority of the domains included in standard measures; whilst a notable number of topics are not specifically included in standard measures at all. This raises questions regarding the efficiency and relevance of such questionnaires to patient and caregivers’ daily lives.

P11.47.B A description of inpatient admissions of adult glioblastoma patients in England 2103 - 2018 from the GlioCova project

Background

The Gliocova dataset uses linked English national cancer data on all 51,775 adult primary brain tumour patients diagnosed between 2013-2018. Here we present early analysis of inpatient admissions of adult glioblastoma (GBM) patients.

Material and Methods

We identified all adults patients diagnosed with a GBM and extracted all the inpatient admissions for 1 night or more after the date of diagnosis. We focused on number and length of admissions, variation in those numbers, and place of discharge.

Results

Between 2013 and 2018, 15,294 patients were diagnosed with a glioblastoma in England (60% male) with a median age of 66, of whom, 12,441 (61% male) were admitted overnight with a total of 49,384 admissions post-diagnosis. Half of these patients were less than 64 at the time of their admission. The mean number of post-diagnosis admissions was 4, with a mean length of stay of 9.5 days. However, for half of the admissions, patients stayed 5 days or less in hospital (IQR = 10). Most of the procedures done were treatment-related, such as surgery for which patients stayed an average of 6.3 days (median = 4; IQR = 5). Patients who were admitted for non-treatment reasons stayed on average almost 10 days (median = 5; IQR = 11). Fewer than 3,000 admissions resulted in a patient death (5.5% of all admissions), whereas over 23,000 admissions for 10,426 patients ended with patients being discharged at home. About 2,000 patients were discharged to another hospital, hospice or a nursing home.

Conclusion

Most of the patients diagnosed with a glioblastoma will be admitted at some point after their diagnosis. Although the average length of stay is not that long, there is a considerable tail of longer-staying patients, for whom improved services and support might enable quicker discharge. To our knowledge, this is the first time inpatient admissions in adult brain patients are being looked at.GlioCova is supported by the Imperial/NIHR BRC, and the members of the GlioCova EAG. This work uses data provided by patients and collected by the NHS as part of their care and support.More information on the Gliocova project can be found on https://blogs.imperial.ac.uk/gliocova.

P14.27 Exploring end-of-life care in the GlioCova national brain tumour patient cohort

BACKGROUND

Brain tumours are the leading cause of cancer deaths in the under-40s. Research on end-of-life care, especially in brain tumour patients is rare, yet important to patients and carers. The GlioCova project holds data on all adult brain tumour patients in England diagnosed between 2013 and 2018. Using this linked data set, we performed preliminary analysis on end-of-life care, focusing on treatment close to death and place of death.

MATERIAL AND METHODS

We used data from the English National Cancer Registry and identified all patients with a primary CNS tumour (ICD-10: C70, C71, C72) who were diagnosed between 2013 - 2018. We examined demographics, tumour morphology and grade, primary cause of death, treatment received within the last 3 and 1 month of life, and the location of death. For patients with unclear location of death (‘unknown’, ‘other’, ‘NA’), we looked at their final destination of discharge recorded in their last inpatient admission.

RESULTS

We identified 26,239 brain tumour patients of whom 20,715 had died. 41.7% were female and median age was 68 (IQR=19). Most patients had a malignant neoplasm of brain (98.6%), followed by meninges (0.7%) and spinal cord, cranial nerves and other parts of central nervous system (0.7%). The most common primary cause of death was malignant neoplasm (70%). Of the 10,021(48.4%) patients who received radiotherapy at any time between diagnosis and death, 1,341 (6.5%) received it within the last three months of life and 254 (1.3%) received it within the last month of life. Of the 5,957 (28.8%) patients who received chemotherapy, 1,358 (6.6%) started a chemotherapy regimen 3 months and 200 (0.97%) 1 month before death. 36.0% of all patients died at home, 23.8% at hospital, 14.7% in a hospice and 8.8% in a nursing home. For 16.7% of patients with an unclear location of death, the most common destination of discharge during their last hospital admission was usual place of residence (54.5%), non-NHS run Care Home (13.9%), NHS run Care Home (11.2%).

CONCLUSION

To the best of our knowledge, this is the first national analysis of end-of-life care in brain tumour patients. Active treatment towards the end of life and in a hospital deaths appear lower in brain tumour patients than in studies of other cancer groups.

P14.18 Patient and Public Involvement to define patient-centred outcomes from National Cancer Datasets

BACKGROUND

GlioCova uses linked national cancer data on all 51 000 adult patients with a primary brain tumour in England (2013 - 2018) to understand patterns of care, treatment, and outcomes in patients with glioma (http://wwwf.imperial.ac.uk/blog/gliocova/). A key aim is the use of patient and carer input in defining patient-centered outcomes. We have held multiple Patient & Public Involvement (PPI) sessions with patients and carergivers and data analysts to understand what patient and caregivers want to know about brain tumours.

MATERIAL AND METHOD

We used a modified Delphi method. The online PPI sessions (Zoom) consisted of two presentations, open discussions, and Q&As. We made the sessions as interactive as possible by using Mentimeter and an interactive online white board (Explain Everything). Pre-reading material was circulated via email. Attendees (6–14 per session) covered a wide range of ages (30–75), diagnoses (GBM, recurrent gliomas, low grade gliomas, ependymoma); patients, caregivers, neuro-oncology staff, data analysts and basic scientists. Work was conducted in line with the INVOLVE PPI guidance.

RESULTS

We identified four questions that were of interest to patients and had correlates in the data:

Patients and caregivers were also interested in the impact of diet, quality of life, social life, and exercise. However, these data cannot be answered using the current national data.

CONCLUSION

Our PPI work has helped us to identify and prioritise questions to ask of the data. Ongoing PPI work will provide a wider perspective and identify knowledge gaps for future research. Patients and caregivers report feeling empowered, being part of a team, feeling like they had given something back and done something meaningful for the research community and other patients. Patients and caregivers also felt that they had an enriched understanding of the data that is collected. As this process is an iterative process, we will hold more PPI sessions to identify and prioritise topics to analyse.

OS14.6.A GlioCova: Defining patient safety events for brain tumour patients undergoing neurosurgery

BACKGROUND

Surgery is associated with a risk of adverse events (e.g. venous thrombosis). These have been used to define the OECD Patient Safety Event (PSE) indicators (41 diagnostic codes), but not in the brain tumour population. The GlioCova project uses English linked national cancer data on all 51,775 adult primary brain tumour patients (2013–2018).

MATERIAL AND METHODS

We identified all glioblastoma patients having surgery for their tumour and noted the 100 most common ICD-10 diagnostic codes within 30 days of surgery, excluding previous medical conditions, brain tumour diagnosis codes and OECD-defined codes. Potential post-surgical complications were reviewed by a group of experienced clinicians. We reviewed these “novel PSE codes” in all brain tumour patients re-admitted after surgery. We looked at the co-occurrence between our novel and OECD codes and combined them to form the final PSE list.Patients readmitted within 30 days were divided into those without codes (“PSE-free”), and those with at least one PSE code during admission or readmission. We examined age, length of stay, in-hospital and 30-day mortality and assessed statistical significance using Welch’s t-test and a two sample Z-test for proportions.

RESULTS

29,135 patients underwent neurosurgery, of whom 8,361 (28.7%) were readmitted within 30 days. We identified 32 novel PSE codes. 1,319 (16%) patients had an OECD code, 5,524 (66%) had a novel code, and 2,098 (25%) patients were PSE-free. 83% of patients who had an OECD PSE code also had a novel code. Patients in the PSE group were older (median age = 60 years) than the PSE-free group (57 years). Length of stay was longer in patients who had a PSE after surgery (median = 7 days) and after readmission (5 days) compared with PSE-free after surgery (4 days), at readmission (0 days). More patients died in hospital after readmission in the PSE group (4.7%) compared with no-PSE (2.7%). 30-day mortality after surgery was similar in both groups (2.5% PSE-free, 3.1% PSE group). All differences were highly statistically significant (p<0.0001).

CONCLUSION

We identified 32 novel patient safety event codes following surgery in the brain tumour population. Patients with these diagnostic codes had an elevated LOS and in-hospital death rate. Using brain tumour specific PSE codes captures many more events than the existing list of OECD codes.