National Cancer Intelligence Network data usage 17 November 2015 – Veronique Poirier – Principal Cancer Analyst – NCIN

Overview Data sources Data collection for brain tumours in England Incidence Mortality Life expectancy Routes to Diagnosis Prevalence Routes from Diagnosis Service Profiles CHI 2National Cancer Intelligence Network data usage

Strengths of the data Population-level cancer data covering the whole country Some countries only register a sample Population-based registration since 1960s Population registration reduces bias / positive sampling of cancer cases Centralisation of English cancer data – ENCORE. Hosted by the National Cancer Registration Service at Public Health England 3National Cancer Intelligence Network data usage

4 Data Sources

5National Cancer Intelligence Network data usage

Data Analysis 6National Cancer Intelligence Network data usage Cancer Analysis System – CAS (incl: cancer registry data, SATC, RTD, WT) (restricted use) Cancerstat – for NHS/PHE users (cancer incidence, mortality, survival, COSD and CHI) Cancer Commissioning Toolkit, NCIN Fingertips, PHE NCIN projects: Cancer by deprivation, Routes to Diagnosis, Macmillan- NCIN Partnership Macmillan Cancer Support, Routes from Diagnosis sofwork/Routesfromdiagnosis.aspx sofwork/Routesfromdiagnosis.aspx Cancer Research UK: wide range of key statistics

Access to data 7National Cancer Intelligence Network data usage

Cancer Outcome Service Dataset 8National Cancer Intelligence Network data usage

9National Cancer Intelligence Network data usage National Cancer Registration Service (NCRS) Public Health England ( ENCORE) Using the WHO International Classification of Diseases, version 10 (ICD- 10) ICD-10 codes grouped: (i) malignant (or invasive, or C-codes) (ii) benign and uncertain or unknown behaviour types (or non-invasive, or D-codes). Inconsistent historical collection of benign tumour data, improved from early 2000s WHO classification changes expected in 2016 will impact on the way some brain tumours are coded, details not yet confirmed Brain tumour data collection

Weaknesses – non-invasive tumours 10 National Cancer Intelligence Network data usage All brain tumours are a registrable condition National statistics have historically focused on invasive tumours When the data are not being used, it is hard to identify data quality issues “One regional registry stopped submitting D32 (benign neoplasm of meninges) to ONS for over 10 years, and this wasn’t spotted as no-one was analysing the data!” Pituitary tumours: reported incidence rates strongly depend on:  Amount of imaging being done, leading to incidental findings  Access of cancer registries to imaging data – better data, higher incidence rate

Weaknesses – brain metastases 11 National Cancer Intelligence Network data usage Primary brain tumours only part of workload Metastases of other primary cancers to the brain are a significant proportion of all tumours in the brain National data on metastases historically poor – site missing Reviewing the data we collect on recurrence and metastases now COSD data is being collected COSD Progressive Cancers project by Macmillan and the National Cancer Intelligence Network, assessing second cancers, recurrence and metastases for selected cancer sitesProgressive Cancers project

Weaknesses – CNS bucket codes 12National Cancer Intelligence Network data usage Different brain cancers have very different care pathways and outcomes Cannot identify type of brain cancer without good morphological coding Historically, many brain cancers have been given bucket diagnoses 2005 tumours – over 1 in 10 coded as Neoplasm NOS InvasiveBenign / Uncertain Neoplasm NOS Specific code

Brain and Central Nervous System ICD 10 codes Cancer typeICD10 to be included Brain & Central Nervous System C700, C701, C709, C710, C711, C712, C713, C714, C715, C716, C717, C718, C719, C720, C721, C722, C723, C724, C725, C728, C729, C751, C752, C753, D320, D321, D329, D330, D331, D332, D333, D334, D337, D339, D352, D353, D354, D420, D421, D429, D430, D431, D432, D433, D434, D437, D439, D443, D444, D445 13National Cancer Intelligence Network data usage

14National Cancer Intelligence Network data usage Age standardised incidence rate: Malignant tumours of the Brain and CNS by sex in England, Source: Cancerstat (C70 to 72) Incidence ratio male to female

Age standardised incidence rate: Benign tumours of the Brain and CNS by sex in England, National Cancer Intelligence Network data usage Source: Cancerstat (D42 and 43)

Number of malignant and benign cases: Brain and CNS by Strategic Clinical Network by sex in England National Cancer Intelligence Network data usage Source: Cancerstat, (C70, 71and 72, and D42 and 43)

Age standardised incidence rate for males diagnosed with a Brain and CNS tumour by SCN in England, National Cancer Intelligence Network data usage Source: Cancerstat, C70-72

18National Cancer Intelligence Network data usage Source: Cancerstat, C70-72 Age standardised incidence rate for females diagnosed with a Brain and CNS tumour by SCN in England,

COSD Conformance Summary Level Diagnosis Counts - Invasive Brain and Central Nervous System 19National Cancer Intelligence Network data usage Source: Cancerstat -COSD

Age standardised mortality rate: Malignant tumours of the Brain and CNS by sex in England, National Cancer Intelligence Network data usage Source: Cancerstat (C70 to 72) Death Ratio male to female 1.3:1

Glioblastoma: Age specific incidence rate and number of cases – Malignant tumours of the brain (C71) – by age and sex in England, 2009 to National Cancer Intelligence Network data usage Source: National Cancer Registration Service Morphology codes for Glioblastoma : 9440/3,9441/3,9442/3

Percentage of Glioblastoma among Astrocytoma (C70- 72) by Strategic Clinical Network in England, National Cancer Intelligence Network data usage Source: National Cancer Registration Service

Glioblastoma in England - median life expectancy in months by regions National Cancer Intelligence Network data usage RegionsMaleFemalePersons North East8.2 (6.7 to 9.2)5.0 (4.2 to 6.0)6.7(5.7 to 7.9) North West6.0 (5.4 to 6.8)5.3 (4.7 to 5.9)5.7 (5.3 to 6.1) Yorkshire and the Humber6.9 (6.0 to 8.0)5.1 (4.3 to 6.1)6.1 (5.6 to 7.0) East Midlands5.9 (5.3 to 6.8)6.0(5.1 to 6.8)5.9 (5.4 to 6.6) West Midlands6.8 (6.1 to 7.6)5.9 (5.1 to 7.4)6.6 (5.9 to 7.3) East of England6.4 (5.6 to 7.0)5.2 (4.4 to 5.9)5.8 (5.3 to 6.4) London6.9 (6.0 to 8.0)6.2 (5.1 to 7.3)6.7 (5.9 to 7.3) South East5.9 (5.4 to 6.5)5.2 (4.7 to 5.8)5.7 (5.3 to 6.0) South West7.2 (6.3 to 8.1)6.4 (5.2 to 7.6)6.9 (6.2 to 7.7) England6.5 (6.2 to 6.8)5.6 (5.3 to 5.8)6.1 (5.9 to 6.3) Source: Brodbelt A et al: Glioblastoma in England: European Journal of Cancer (2015) 51,

Routes to diagnosis data – England 24National Cancer Intelligence Network data usage Source: Routes to Diagnosis workbook ASource: Routes to Diagnosis workbook A

25National Cancer Intelligence Network data usage Source: Routes to Diagnosis workbook ASource: Routes to Diagnosis workbook A Routes to diagnosis data – England

26National Cancer Intelligence Network data usage Source: Routes to Diagnosis workbook ASource: Routes to Diagnosis workbook A Routes to diagnosis data – England Relative survival 12 month

27National Cancer Intelligence Network data usage Survivorship – what are the pathways after diagnosis? Report focused on: glioblastoma, meningioma and nerve sheath tumours Patients with meningioma and nerve sheath tumours = notably better outcomes: Majority survive 7+ years (63.8% and 87.2% respectively) Group 7: major long-term health service demands Over half (55%) of cancer patients with glioblastoma tumours did not survive past 6 months Show similar short-term survival outcomes to lung cancer patients Routes from Diagnosis what is the CNS survivorship pathway ? Source: Macmillan Cancer Support, Accessed February 2015

20-year cancer prevalence – Brain and CNS tumours in England, National Cancer Intelligence Network data usage Source Macmillan-NCIN

Clinical Headline Indicators 29National Cancer Intelligence Network data usage Source: Cancerstat –CHI demo

Conclusions NCRS data is a good resource world leading data set understand and improve patient care across the country There are known weaknesses in the available cancer data. Important to consider during data analysis Recent developments - one English National Cancer Registration Service, COSD, SACT, Radiotherapy, DID 30National Cancer Intelligence Network data usage

Contact Sarah Miller – Senior Cancer Analyst – lead analyst for Brain and CNS Chair of CNS NCIN SSCRG: Professor Peter Collins Next meeting/workshop dates have been provisionally set for : 4 th and 5 th February central_nervous_system_cancers / 31National Cancer Intelligence Network data usage