This statistic shows the amount of registrations of newly diagnosed cases of brain cancer in England in 2022, by age group. In this year, *** new cases were reported among men aged 70 to 74 years of age, and *** cases among women in this age group.

In 2022, 10.2 males and 6.5 females per 100,000 population in England were registered as newly diagnosed with brain cancer. Compared to the previous year, a slight increase in the newly diagnosed thyroid cancer rates was seen for male individuals, while the female diagnose rate remained stable. This statistic shows the rate of newly diagnosed cases of brain cancer per 100,000 population in England from 1995 to 2022, by gender.

This registry contains data on Age-Adjusted Incidence Rates and 95% Confidence Intervals for Brain and Other Nervous System Tumors by Histologic Grouping , Age, and Behavior. Rates are per 100,000 persons and are age-adjusted to the 2000 U.S. standard population (19 age groups - Census P25-1130). CDC’s National Program of Cancer Registries (NPCR) has funded state cancer registries to collect population-based cancer incidence data under Public Law 102-515, the Cancer Registries Amendment Act.

In 2022, around ****** people in their sixties were brain tumor patients in South Korea. They were the largest age group in the country to suffer from the disease, with younger age groups in general recording less cases than older age groups. Brain tumors form when a mass of abnormal cells grow in or around the brain and may be either malignant or benign.

Number of exposed cases (Ca) and controls (Co) are given. Adjustment was made for age at diagnoses, SEI-code (socio-economic index; blue-collar worker, white-collar worker, self-employed, unemployed), and year for diagnosis. Overall results (all ages) have previously been published [12].

The global brain tumor therapeutics market is a rapidly evolving landscape, characterized by significant growth driven by increasing incidence rates of brain tumors, advancements in diagnostic technologies, and the emergence of novel therapeutic approaches. The market, estimated at $15 billion in 2025, is projected to experience a robust Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $25 billion by 2033. This growth is fueled by several key factors, including the rising prevalence of primary and secondary brain tumors across various age groups, improved patient survival rates due to early detection and targeted therapies, and a burgeoning pipeline of innovative treatments, such as immunotherapies, gene therapies, and oncolytic viruses. Key players like Pfizer, Novartis, Roche, Merck, and AstraZeneca are heavily investing in research and development to expand their product portfolios and capture market share within this lucrative segment. However, the market faces certain challenges. High treatment costs, limited treatment efficacy in certain tumor types, and the inherent complexity of the central nervous system pose significant hurdles. Furthermore, regulatory approvals for novel therapies can be lengthy and demanding, potentially delaying market entry. Despite these restraints, ongoing research into personalized medicine, biomarker-driven therapies, and improved surgical techniques are expected to propel market expansion. The segmentation of the market (likely by tumor type, therapy type, and geography) will also influence growth dynamics, with some segments exhibiting faster growth rates than others. This market will also be segmented by major geographical regions, with North America and Europe likely representing major revenue contributors in the foreseeable future, due to higher healthcare expenditure and advanced medical infrastructure.

This is a dataset corresponding to data utilized in the publication titled "Social cognition and adjustment in adult survivors of pediatric central nervous system tumors" reported in Papini et al., 2023 (DOI: 10.1002/cncr.34889).

The file contains:

• demographic variables: sex and age at assessment (in years)
• clinical variables: clinical group, age at diagnosis (in years), time since diagnosis (in years), intelligence score (in standard score), tumor location, dose of cranial radiation (in Gy), chemotherapy agents (yes/no) and doses (in mg/m²), neurosurgery type, diagnosis, and presence of stoke, seizure and hearing loss
• functional outcomes: independent living, marital status, education, and employment
• social cognition measures (in scaled scores): Social Perception, Affect Naming, Prosody, Prosody Pair Matching, Faces Immediate, Faces Delayed, Faces Content, Faces Spatial, Names Immediate, Names Delayed, Proper Names, Activity
• social adjustment measures (in T-scores): Companionship, Instrumental Support, Emotional Support, Informational Support, Social Isolation, Ability to Participate in Social Roles and Activities, and Satisfaction with Social Roles and Activities
• neurocognitive functioning measures: executive function impairment (yes/no), non-verbal reasoning impairment (yes/no) and the BRIEF Global Executive Composite score (in T-score)

Please note that the time variables (i.e., age at assessment, age at diagnosis, and time since diagnosis) were rounded to whole years to ensure deidentification for sharing purposes.

Please cite the appropriate publications (this repository and corresponding publication above) in any communications or publications arising directly or indirectly from these data.

Funding

The study was supported by National Cancer Institute (U01 CA195547, Hudson and Ness) and St. Baldrick’s Foundation (Research Scholar Award, Brinkman). Support to St Jude Children’s Research Hospital was also provided by the National Cancer Institute Cancer Center Support Grant (CORE) Grant (P30 CA21765, Roberts) and the American Lebanese Syrian Associated Charities.

This statistic shows the registrations of newly diagnosed cases of brain cancer in England from 1995 to 2022, by gender. In 2022, 2,806 men and 2,004 women were diagnosed with brain cancer in England.

This dataset includes brain MRI scans of adult brain glioma patients, comprising of 4 structural modalities (i.e., T1, T1c, T2, T2-FLAIR) and associated manually generated ground truth labels for each tumor sub-region (enhancement, necrosis, edema), as well as their MGMT promoter methylation status. These scans are a collection of data from existing TCIA collections, but also cases provided by individual institutions and willing to share with a cc-by license. The BraTS dataset describes a retrospective collection of brain tumor structural mpMRI scans of 2,040 patients (1,480 here), acquired from multiple different institutions under standard clinical conditions, but with different equipment and imaging protocols, resulting in a vastly heterogeneous image quality reflecting diverse clinical practice across different institutions. The 4 structural mpMRI scans included in the BraTS challenge describe a) native (T1) and b) post-contrast T1-weighted (T1Gd (Gadolinium)), c) T2-weighted (T2), and d) T2 Fluid Attenuated Inversion Recovery (T2-FLAIR) volumes, acquired with different protocols and various scanners from multiple institutions. Furthermore, data on the O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status is provided as a binary label. Notably, MGMT is a DNA repair enzyme that the methylation of its promoter in newly diagnosed glioblastoma has been identified as a favorable prognostic factor and a predictor of chemotherapy response. It is curated for computational image analysis of segmentation and prediction of the MGMT promoter methylation status.

A note about available TCIA data which were converted for use in this Challenge: (Training, Validation, Test)

Dr. Bakas's group here provides brain-extracted Segmentation task BraTS 2021 challenge TRAINING and VALIDATION set data in NIfTI that do not pose DUA-level risk of potential facial reidentification, and segmentations to go with them. This group has provided some of the brain-extracted BraTS challenge TEST data in NIfTI, and segmentations to go with them (here and here, from the 2018 challenge, request via TCIA's Helpdesk. This group here provides brain-extracted Classification task BraTS 2021 challenge TRAINING and VALIDATION set data includes DICOM→ NIfTI→ dcm files, registered to original orientation, data files that do not strictly adhere to the DICOM standard. BraTS 2021 Classification challenge TEST files are unavailable at this time. You may want the original corresponding DICOM-format files drawn from TCIA Collections; please note that these original data are not brain-extracted and may pose enough reidentification risk that TCIA must keep them behind an explicit usage agreement. Please also note that specificity of which exact series in DICOM became which exact volume in NIfTI has, unfortunately, been lost to time but the available lists below represent our best effort at reconstructing the link to the BraTS source files.

This dataset contains data about 73 patients with a diagnosis of brain tumor in developmental age. This cohort includs subjects between 6-18 years at assessment, accessing to a pediatric rehabilitation center in Italy, the Scientific Institute I.R.C.C.S. . E. Medea, Bosisio Parini, Italy. The original dataset was composed of 78 subjects, but 5 patients were excluded because they were identified as outliers.

The data were used to explore the possible clinical and cognitive predictors of the adaptive functioning in this clinical population. The related papaer is currently under submission.

The clinical collected measures are:

• age_at_diagnosis: age of the patient at diagnosis, expressed in month;
• tumor_site: the location of the tumor, classified as supratentorial or infratentorial;
• tumor_type: the histopathological tumor type, classified as astrocytoma, ependymoma, medulloblastoma or other (meaning more rare tumors, such as theratoid rabdoid tumor, brainstem gliomas…)
• chemiotherapy: scored yes or not, whether the child underwent chemotherapy treatment or not;
• radiotherapy: scored yes or not, whether the child underwent radiotherapy treatment or not;
• surgery: scored yes or not, whether the child underwent neurosurgery treatment or not;
• hydrocephalus: scored present or absent, whether the child developed hydrocephalus or not;
• time_since_diagnosis: the time (expressed in months) passed through the diagnosis to the functional evaluation.
• age_at_assessment: age of the patient at assessment, expressed in month.

The cognitive collected measures from the Wechsler Intelligence Scale for Children, 4th Edition are:

• VCI: Verbal Comprehension Index;
• VSI: Visual Spatial Index;
• FSIQ: Full Scale Intelligent Quotient;
• WMI: Working Memory Index;
• PSI: Processing Speed Index.

The adaptive functioning measures collected from the Functional Independence Measure for children (WeeFIM, version 5.0) are:

• WeeFIM_selfcare: score ranges from 8 to 56;
• WeeFIM_mobility: score ranges from 5 to 35;
• WeeFIM_cognition: score ranges from 5 to 35.

Higher scores expressed better independence and less need of assistance.

Moreover the score of each of the 18 items composing the scale and divided in the 3 domains were collected. All item scores ranged between 1 to 7, with higher scores expressing better independence and less need of assistance.

• selfcare_eating, _grooming, _bathing, _dressing (upper), _dressing (lower), _toileting, _bladder, _bowel
• mobility_bed, chair, wheelchair transfer, _toilet transfer, _tub/shower transfer, _walk/wheelchair, _stairs
• cognition_comprehension, _expression, _social interaction, _problem solving, _memory

Purpose: Plasma volume and blood volume are imaging-derived parameters that are often used to evaluation intracranial tumors. Physiologically, these parameters are directly related, but their two different methods of measurements, T1-dynamic contrast enhanced (DCE)- and T2-dynamic susceptibility contrast (DSC)-MR utilize different model assumptions and approaches. This poses the question of whether the interchangeable use of T1-DCE-MRI derived fractionated plasma volume (vp) and relative cerebral blood volume (rCBV) assessed using DSC-MRI, particularly in glioblastoma, is reliable, and if this relationship can be generalized to other types of brain tumors. Our goal was to examine the hypothetical correlation between these parameters in three most common intracranial tumor types. Methods: Twenty-four newly diagnosed, treatment naïve brain tumor patients, who had undergone DCE- and DSC-MRI, were classified in three histologically proven groups: glioblastoma (n=7), meningioma (n=9), and intraparenchymal metastases (n=8). The rCBV was obtained from DSC after normalization with the normal-appearing anatomically symmetrical contralateral white matter. Correlations between these parameters were evaluated using Pearson (r), Spearman's (ρ) and Kendall’s tau-b (τB) rank correlation coefficient. Results: The Pearson, Spearman and Kendall’s correlation between vp with rCBV were r=0.193, ρ=0.253 and τB=0.33 (p-Pearson=0.326, p-Spearman=0.814 and p-Kendall=0.823) in glioblastoma, r=-0.007, ρ=0.051 and τB=0.135 (p-Pearson=0.970, p-Spearman=0.765 and p-Kendall=0.358) in meningiomas, and r= 0.289, ρ=0.228 and τB= 0.239 (p-Pearson=0.109, p-Spearman=0.210 and p-Kendall=0.095) in metastasis. Conclusion: Results indicate that no correlation exists between vp with rCBV in glioblastomas, meningiomas and intraparenchymal metastatic lesions. Consequently, these parameters, as calculated in this study, should not be used interchangeably in either research or clinical practice. Plos_one_SB_dataThe age column is deleted.

Mouse Glioblastoma Atlas (snRNA-seq) Dataset

  Dataset Overview

This dataset comprises single-nucleus RNA sequencing (snRNA-seq) data from the brain (glioblastoma tumors and their microenvironment) of both young and aged mice. It provides a high-resolution cellular and molecular census of glioblastoma, a highly aggressive brain tumor, with crucial insights into its age-related characteristics. The original data was sourced from a CELLxGENE Discover collection titled… See the full description on the dataset page: https://huggingface.co/datasets/longevity-db/mouse-glioblastoma-snRNAseq.

Objective: Perform a longitudinal analysis of clinical features associated with Neurofibromatosis Type 1 (NF1) based on demographic and clinical characteristics, and to apply a machine learning strategy to determine feasibility of developing exploratory predictive models of optic pathway glioma (OPG) and attention-deficit/hyperactivity disorder (ADHD) in a pediatric NF1 cohort.

Methods: Using NF1 as a model system, we perform retrospective data analyses utilizing a manually-curated NF1 clinical registry and electronic health record (EHR) information, and develop machine-learning models. Data for 798 individuals were available, with 578 comprising the pediatric cohort used for analysis.

Results: Males and females were evenly represented in the cohort. White children were more likely to develop OPG (OR: 2.11, 95%CI: 1.11-4.00, p=0.02) relative to their non-white peers. Median age at diagnosis of OPG was 6.5 years (1.7-17.0), irrespective of sex. Males were more likely than females t...

Background: We explored the association between ionizing radiation (IR) from pre-natal and post-natal radio-diagnostic procedures and brain cancer risk within the MOBI-kids study. Methods: MOBI-kids is an international (Australia, Austria, Canada, France, Germany, Greece, India, Israel, Italy, Japan, Korea, New Zealand, Spain, The Netherlands) case-control study including 899 brain tumor (645 neuroepithelial) cases aged 10–24 years and 1,910 sex-, age-, country-matched controls. Medical radiological history was collected through personal interview. We estimated brain IR dose for each procedure, building a look-up table by age and time period. Lifetime cumulative doses were calculated using 2 and 5 years lags from the diagnostic date. Risk was estimated using conditional logistic regression. Neurological, psychological and genetic conditions were evaluated as potential confounders. The main analyses focused on neuroepithelial tumors. Results: Overall, doses were very low, with a skewed distribution (median 0.02 mGy, maximum 217 mGy). ORs for post-natal exposure were generally below 1. ORs were increased in the highest dose categories both for post and pre-natal exposures: 1.63 (95% CI 0.44–6.00) and 1.55 (0.57–4.23), respectively, based on very small numbers of cases. The change in risk estimates after adjustment for medical conditions was modest. Conclusions: There was little evidence for an association between IR from radio-diagnostic procedures and brain tumor risk in children and adolescents. Though doses were very low, our results suggest a higher risk for pre-natal and early life exposure, in line with current evidence.

The Erasmus Glioma Database (EGD) contains structural magnetic resonance imaging (MRI) scans, genetic and histological features (specifying the WHO 2016 subtype), and whole tumour segmentations of patients with glioma. Pre-operative MRI data of 774 patients with glioma (281 female, 492 male, 1 unknown, age range 19–86 years) treated at the Erasmus MC between 2008 and 2018 is available. For all patients a pre-contrast T1-weighted, post-contrast T1-weighted, T2-weighted, and T2-weighted FLAIR scan are available, made on a variety of scanners from four different vendors. All scans are registered to a common atlas and defaced. Genetic and histological data consists of the IDH mutation status (available for 467 patients), 1p/19q co-deletion status (available for 259 patients), and grade (available for 716 patients). The full WHO 2016 subtype is available for 415 patients. Manual segmentations are available for 374 patients and automatically generated segmentations are available for 400 patients. The dataset can be used to relate the visual appearance of the tumor on the scan with the genetic and histological features, and to develop automatic segmentation methods.

See also: https://github.com/Svdvoort/egd-downloader

BackgroundChildhood primary brain tumors (CPBT) are the second largest group of childhood malignancies and associated with a high risk for endocrine late effects.ObjectiveTo assess endocrine late effects and their relevance for the development of osteopathologies in survivors.MethodsThis single center cross sectional study investigated data from 102 CPBT survivors with a mean age of 13.0 years and a mean age at diagnosis of 8.7 years. Clinical, biochemical, radiographic, and anamnestic data regarding endocrine and bone health were obtained at study visits. In addition, data regarding tumor stage and therapy was obtained by chart review. An expert opinion was applied to define presence of osteopathologies.ResultsImpaired bone health, defined by at least one pathological screening parameter, was present in 65% of patients. 27.5% were found to have overt osteopathologies per expert opinion. 37.8% displayed a severe vitamin D deficiency (25-OH vitamin D < 10 ng/ml) and 11% a secondary hyperparathyroidism. Patients with osteopathologies had lower 25-OH vitamin D levels compared to patients without osteopathologies. Multiple endocrine late effects were present: diabetes insipidus in 10.8%, aberrant pubertal development in 13.7%, central hypocortisolism in 14.9%, thyroid dysfunction in 23.8% and growth hormone deficiency in 21.8%. A total of 31.3% of survivors displayed any endocrinopathy. Tumors located near hypothalamic structures and patients who received irradiation had a higher likelihood of endocrine morbidity.ConclusionThis study indicates that endocrine deficiencies are common in pediatric survivors of CPBTs. Osteopathologies are present in this cohort. A prominent effect of hormonal deficiencies on bone health was not detected, possibly because patients were sufficiently treate for their endocrine conditions or indicating resilience of the childhood bone remodeling process. Vitamin D deficiency is frequent and should be treated as recommended.

The objective of the ACRIN 6684 multi-center clinical trial was to determine the association of baseline FMISO PET uptake (maximal tumor to blood ratio, hypoxic volume) and MRI parameters (K^trans, CBV) with overall survival, time to disease progression, and 6-month progression free survival in participants with newly diagnosed glioblastoma multiforme (GBM). The trial also collected standard brain cancer data such as Karnofsky performance status, but also pathological biomarkers that included MGMT status, HIF1-alpha, GLUT1, CAIX, CD31, and alpha-SMA expression assays.

There are two sets of volumes of interest (VOI) included with the ACRIN 6684 collection of MRI, PET and low-dose CT patient images. These include delineation of enhancing brain tumor lesions and ¹⁸F-FMISO PET hypoxia maps. More information about these masks can be found on the Detailed Description tab below. Additional information about the trial is available in the Study Protocol and Case Report Forms.

ACRIN 6684 Study Protocol

After establishing eligibility and enrollment to the study, baseline imaging of both MR and PET was performed within 2 weeks of starting therapy. FMISO, has been helpful in evaluating tumor oxygenation status, which may affect how well it responds to radiation and chemotherapy. The MRI scans were designed to measure tumor characteristics related to oxygenation status, including changes in blood flow, blood volume, and blood vessel size.

In the original protocol, following baseline imaging was an optional test-retest scan for FMISO PET only. Also included were PET and MRI scans at 3 weeks after the onset of chemo/radiation therapy, and 4 weeks following the end of standard treatment. Of the 50 patients enrolled in the study only one patient had a test-retest FMISO scan, and the requirement of scans mid and post therapy were dropped after the 4^th case. The current protocol appears in the figure on the right, and can be found online ( Protocol-ACRIN 6684 Amendment 7, 01.24.12 ). The latest protocol for ACRIN 6684 had PET and MR imaging performed only at baseline, up to 2 weeks prior to standard treatment (chemo + radiation therapy). Mid and post-therapy scans were eliminated from the protocol after Case 4, and only one patient had a retest FMISO scan. Of the 50 enrolled patients, 42 patients had evaluable imaging data for the primary aims of the study (see Gerstner et al. 2016).

Note: The MRI DWI/DTI series acquired through GE or Siemens scanners for 30 patients have been stripped of their b-values and diffusion gradient matrix DICOM header fields making them unable to be processed for ADC map production. The patients scanned with Philips MRI scanners are intact.

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Glioblastoma (GBM) is an incurable brain tumor carrying a dismal prognosis, which displays considerable heterogeneity. We have recently identified recurrent H3F3A mutations affecting two critical positions of histone H3.3 (K27, G34) in one-third of pediatric GBM. Here we show that each of these H3F3A mutations defines an epigenetic subgroup of GBM with a distinct global methylation pattern, and are mutually exclusive with IDH1 mutation (characterizing a CpG-Island Methylator Phenotype (CIMP) subgroup). Three further epigenetic subgroups were enriched for hallmark genetic events of adult GBM (EGFR amplification, CDKN2A/B deletion) and/or known transcriptomic signatures. We also demonstrate that the two H3F3A mutations give rise to GBMs in separate anatomic compartments, with differential regulation of OLIG1/2 and FOXG1, possibly reflecting different cellular origins. To further dissect the biological differences between epigenetic glioblastoma subgroups, we looked at the transcriptomic profiles of glioblastoma samples. Overall design: 46 glioblastoma samples from patients of various ages were selected for RNA extraction and hybridization on Affymetrix Affymetrix Human Genome U133 Plus 2.0 Arrays.

Objective: Diffuse low-grade gliomas (DLGG) are defined by a continuous growth and an almost unavoidable malignant transformation. Foci of malignant glioma can be found within DLGG samples obtained from surgical resections. As the medical management of patients is classically based on the higher tumor grade, an immediate adjuvant treatment is usually proposed. To determine whether postponing the medical treatment in selected patients is feasible, we conducted a single-center retrospective study. Methods: Single-center retrospective analysis of a consecutive series of DLGG managed with this conservative strategy. Inclusion criteria were: at least one focus of malignant tumor (grade III-IV, WHO 2016), no previous chemotherapy or radiotherapy, no less than a subtotal resection of the FLAIR tumor volume, no intention of treating with immediate adjuvant therapy, minimum two years of follow-up. The time interval to the following oncological medical treatment was analyzed, as well as the functional and survival results. Results: 45 patients met the inclusion criteria (median age 36.5, median time interval from diagnosis: 7.3 months). Most tumors (86.7%) were IDH-mutant and 1p19q intact (60.0%); 10 presented with grade IV foci. With a median follow-up of 6.3 years, 75.5% of patients received a subsequent medical treatment, after a median time of 3.7 years since surgery. At the time of analysis, 9 patients (20.0%) had died (5-years and 7-years survival rates: 95.2% and 67.0%). Most surviving patients were still active professionally, without seizures. Conclusions: Postponing the medical treatment in DLGG with foci of malignant tumor following total or subtotal resection should be considered in selected patients.

The Get Data Out programme from the National Disease Registration Service publishes detailed statistics about small groups of cancer patients in a way that ensures patient anonymity is maintained. The 19 cancer sites currently covered by Get Data Out are: ‘Bladder, urethra, renal pelvis and ureter’, ‘Bone’, ‘Brain’, ‘Eye’, ‘Blood cancer (haematological neoplasms)’, ‘Blood cancer (haematological neoplasm) transformations’, ‘Head and neck’, ‘Kaposi sarcoma’, ‘Kidney’, ‘Liver and biliary tract’, ‘Lung, mesothelioma, and other thoracic', Oesophagus and stomach’, ‘Ovary’, ‘Pancreas’, ‘Prostate’, ‘Sarcoma’, ‘Skin tumours’, ‘Soft tissue’, ‘Testes’. Anonymisation standards are designed into the data by aggregation at the outset. Patients diagnosed with a certain type of tumour are divided into many smaller groups, each of which contains approximately 100 patients with the same characteristics. These groups are aimed to be clinically meaningful and differ across cancer sites. For each group of patients, Get Data Out routinely publish statistics about incidence, routes to diagnosis, treatments and survival. This release covers a refresh of the 2013-2020 incidence data plus the addition of the diagnosis years 2021 and 2022 for incidence. It also covers a refresh of the 2013-2020 treatment data plus the addition of the diagnosis year 2021 for treatment statistics. It also covers a refresh of the 2013-2018 routes to diagnosis data plus the addition of the diagnosis years 2019 and 2020 for routes to diagnosis data. In this release some of our group names have been revised to more concise or more meaningful names. This better aligns us with other NDRS publications. For example, the group which was previously called 'Ovary, fallopian tube and primary peritoneal carcinomas' is now called 'Ovary', and the group which was previously called 'Haematological malignancies' is now called 'Blood cancer (haematological neoplasms)'. Finally, this release includes some new columns in the incidence data. As well as publishing crude incidence rates, we are now publishing age gender standardised incidence rates along which their upper and lower confidence intervals. This will allow for better international comparison of our groups. We have also added 50 new incidence columns which break down the incidence in the whole group by different patient characteristics. These are five-year-age and gender, broad ethnicity group, and deprivation quintile. For a specific GDO group therefore (row in our output data), a user will be able to identify the incidence for that group as a whole and then the incidence in, for example, the '65-69 male' group, the '40-44 female' group, the 'Black' group, or the 'Deprivation quintile 4' group. All releases and documentation are available on the Get Data Out dashboard. Before using the data, we recommend that you read the 'Introduction', 'FAQs' and 'Known limitations' tabs. The data is available in an open format for anyone to access and use. We hope that by releasing anonymous detailed data like this we can help researchers, the public and patients themselves discover more about cancer. If you have feedback or any other queries about Get Data Out, please email us at NDRSenquires@nhs.net and mention 'Get Data Out' in your email.