Good TREs work

Evidera Ltd projects

21 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


Descriptive Epidemiology, Treatment Patterns, and Outcomes of Patients with Renal Cell Carcinoma in England: A Retrospective Cohort Study Using SACT Data and Cancer Registry (DORCES) ( ODR2021_055 ) — DARS-NIC-656879-L3Y5Z

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Research)

Sensitive: Sensitive

When:DSA runs 2024-03-29 — 2024-08-31

Access method: One-Off

Data-controller type: EVIDERA LTD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care (HES APC)
  2. Hospital Episode Statistics Outpatients (HES OP)
  3. NDRS Cancer Registrations
  4. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

Evidera Ltd are requesting an extension to retain the data provided under DARS-NIC-656879 for a few months longer. Evidera Ltd are currently working on preparing a manuscript to disseminate results of the study. Therefore, Evidera Ltd are requesting that the data sharing agreement is extended in case Evidera Ltd are required to go back to the data due to queries raised in manuscript review. Evidera Ltd are not requesting any new data and use of the data remains for the same purpose/objectives as the original application.
Evidera Ltd utilised existing Cancer Registration data from Public Health England (PHE) to assess the trends in treatment patterns and survival outcomes of patients with kidney cancer (renal cell carcinoma [RCC]) in England, and how the trends vary by stage at diagnosis, disease histology, line of therapy, year of diagnosis and receipt of nephrectomy (surgical removal of the kidney). Specifically, Evidera Ltd analysed the data to describe patient characteristics. Evidera Ltd also calculated a measured called “overall survival”, which is an estimate of the length of time between a defined time point, such as the date of diagnosis of a condition, and the date of death.
The Cancer Registration dataset includes data on demographics, characteristics of the tumour, patients’ vital status and basic information regarding the treatment received. Evidera Ltd utilized the Systemic Anti-Cancer Therapy dataset, which contained information on systemic treatment received by patients in the cancer registry. This was linked to another dataset, Hospital Episode Statistics, which contains information on all hospital visits, admissions and procedures in England.


The following NHS England data will be accessed:
• BAU Hospital Episode Statistics Admitted Patient Care (HESAPC)
• BAU Hospital Episode Statistics Outpatient Patient (HESOP)
• NDRS Cancer Registration
• NDRS Systemic Anti-Cancer Therapy (SACT)
The level of the data will be pseudonymised.


The data will be minimised as follows:
• Limited to patients diagnosed with malignant neoplasm of kidney, except renal pelvis (ICD-10 code: C64x) between 01 April 2014 to 31 December 2018
• Limited to the following geographic areas England
• Limited to patients above the age of 18


Evidera Ltd is the data controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above.

Although BMS UK is the research sponsor, BMS UK will not carry out any data controllership activities.


The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child.
Evidera have legitimate interest in processing the data as part of a client agreement with BMS to study the treatment and outcomes in patients with renal cell carcinoma.

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
There is public interest in the processing of this data as it is scientific research regarding treatment and outcomes of patients with renal cell carcinoma in England. Evidera anticipate several potential public health benefits for their analysis. It is necessary to determine any trends in treatment patterns and outcomes in patients with RCC to better understand the evolving treatment landscape in the UK. The dataset contains variables that are not commonly available in UK primary or secondary care data sources, such as cancer stage. This allows for a more granular description of mortality trends within subgroups known to have very different survival experiences. SACT data contain detailed information on cancer treatments received during follow-up. The Cancer Registration data from PHE covers the entire English population, and results are therefore generalisable to the population of England. Evidera have already presented findings at two scientific conferences and are in the process of preparing a manuscript for journal submission.


The funding is provided by BMS UK. The funding is specifically for the study described. Funding is in place until completion of the agreed study. The funder will have no ability to suppress or otherwise limit the publication of findings.


Evidera Ltd is the sole data controller and the data processor.

Yielded Benefits:

Two conference posters containing aggregate results have been presented at ASCO Genitourinary Cancers symposium 2023, and the International Kidney Cancer Symposium, Europe, 2023

Expected Benefits:

Evidera Ltd anticipate several potential public health benefits for the analysis and dissemination. It is necessary to determine any trends in treatment patterns and outcomes in patients with RCC to better understand the evolving treatment landscape in the UK. The dataset previously received contained variables that are not commonly available in UK primary or secondary care data sources, such as cancer stage. This allowed for a more granular description of mortality trends within subgroups known to have very different survival experiences. SACT data contained detailed information on cancer treatments received during follow-up. The cancer registration data from PHE (called PHE at the time of receiving the data) covered the entire English population, and results will therefore be generalisable to the population of England.


The information generated from this study provides insight on characteristics of patients with RCC, and it highlights populations with potentially unmet needs regarding treatment persistence and survival. This information available to healthcare professionals will indirectly impact patient care.


Based on the information published from this study, healthcare professionals will be able to further understand the characteristics of patients with RCC and their treatment patterns using real-world evidence.

Outputs:

The expected outputs of the processing will be:
• An internal report
• Presentations to various conferences in the form of posters in 2023
• Submissions to peer reviewed journals at the end of the study in late 2023


The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.


The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Posters displayed at ASCO Genitourinary Cancers symposium 2023, and the International Kidney Cancer Symposium, Europe, 2023.


The target dates for submission of the manuscript is by the end of 2023.

Processing:

No data will flow to NHS England for the purposes of this Agreement.


NHS England data have provided the relevant records from the NDRS HESAPC, NDRS HESOP, NDRS SACT and NDRS Cancer Registration datasets to Evidera Ltd. The data contains no direct identifying data items but will contain a unique person ID which can be used to link the datasets together.


The data will not be transferred to any other location.


The data will be stored and backed-up on servers at Evidera Ltd.


The data will be accessed by authorised personnel via remote access . The data will remain on the servers at Evidera Ltd at all times.
Personnel are prohibited from downloading or copying data to local devices.


The data will not leave England/Wales at any time.


Access is restricted to employees or agents of Evidera Ltd who have authorisation from the Principal Investigator .


BMS UK is not permitted to access the data.


All personnel accessing the data have been appropriately trained in data protection and confidentiality.


The data will not be linked with any other data outside the scope of this agreement.


There will be no requirement and no attempt to reidentify individuals when using the data. As in the previous agreement, Evidera Ltd do not have access to identifiable information such as a patient’s name, NHS number, geographic location or date of birth. This study did not use identifiable personal data. Publications will only summarize aggregate level data void of any personal identifying information. Small numbers will be anonymised.


Analysts from Evidera Ltd will analyse the data for the purposes described above.


Health Burden of COVID-19 and Healthcare Resource Utilisation in England — DARS-NIC-561357-X0F3N

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261(5)(d)

Purposes: Yes (Research)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-11-18 — 2023-11-17 2022.12 — 2024.05.

Access method: System Access, One-Off
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: ASTRAZENECA UK LIMITED, HEALTH & SOCIAL CARE INFORMATION CENTRE, ASTRAZENECA UK LIMITED, NHS ENGLAND - X26, ASTRAZENECA UK LIMITED

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. COVID-19 Second Generation Surveillance System
  3. COVID-19 Vaccination Status
  4. GPES Data for Pandemic Planning and Research (COVID-19)
  5. Hospital Episode Statistics Accident and Emergency
  6. Hospital Episode Statistics Admitted Patient Care
  7. Hospital Episode Statistics Critical Care
  8. Hospital Episode Statistics Outpatients
  9. Medicines dispensed in Primary Care (NHSBSA data)
  10. Uncurated Low Latency Hospital Data Sets - Admitted Patient Care
  11. Uncurated Low Latency Hospital Data Sets - Critical Care
  12. Uncurated Low Latency Hospital Data Sets - Emergency Care
  13. Uncurated Low Latency Hospital Data Sets - Outpatient
  14. Civil Registrations of Death
  15. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  16. COVID-19 Second Generation Surveillance System (SGSS)
  17. Hospital Episode Statistics Accident and Emergency (HES A and E)
  18. Hospital Episode Statistics Admitted Patient Care (HES APC)
  19. Hospital Episode Statistics Critical Care (HES Critical Care)
  20. Hospital Episode Statistics Outpatients (HES OP)
  21. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Expected Benefits:

Benefits from this study are expected to include the following
1. Benefits for regulators (e.g., MHRA): the findings from this study are hoped will support MHRA’s review of EVUSHELD for the use among patients who are immunocompromised and other vulnerable populations to supplement the trial evidence, based on which the Conditional Marketing Authorisation in PrEP (pre-exposure prophylaxis) was granted. Furthermore, the results of this study will provide a baseline against which to benchmark the overall impact of the use of EVUSHELD, until data accrual and maturity allow for a contemporaneous comparative effectiveness and safety assessment, following the administration of sufficient doses. Additionally, should the respective clinical trials confirm EVUSHELD’s safety and efficacy in outpatient and inpatient treatment indications, the results of this study will serve as foundation for the development of the submission dossier to ascertain the most accurate characterisation of the source population in England.

2. Its is anticipated that there will be benefits for Health Technology Assessment and endorsement bodies such as NICE and the Scottish Medicines Consortium (SMC): During the early scientific advice procedure in which AstraZeneca engaged, NICE requested more accurate information on the expected number of patients that would be eligible for EVUSHELD use. NICE also recommended that AstraZeneca conduct an observational study to continue identifying which populations do not respond to vaccinations, beyond patients who are immunocompromised, and expressed concern for the dynamic landscape due to the emergence of new variants, which should also be monitored. Lastly, NICE requested that the health-economic model be populated with efficacy data from the phase III trial PROVENT (NCT04625725, please see - https://clinicaltrials.gov/ct2/show/NCT04625725) but the baseline characteristics be adjusted to more accurately reflect the population in England as well as account for the substantial heterogeneity likely to exist in the target population (e.g., in terms of comorbidities, resource use, risk of severe COVID-19). These are the exact research questions that guided the design of the current study. The results from objectives 2 and 3 will be used to adjust the population characteristics for the cost-effectiveness model. Additionally, the patterns of HCRU and costs associated with an episode of COVID-19 will be an important input for the cost-effectiveness model. The accurate count of patients at risk from objective 1 will also be used in the budget impact model. The exploratory objectives to identify and quantify risk profiles with high unmet clinical need will be the basis for sensitivity analyses in both health-economic models. Furthermore, as the pandemic becomes endemic, regulators and policy makers will also benefit from country-specific estimates on the burden of long-COVID-19 to patients and to the healthcare system to be factored in policy decisions.

3. It is anticipated that there will be benefits for the UK Department of Health and Social Care, clinicians, and healthcare providers: The wide-spread vaccination of the British population has significantly improved the epidemiological situation, thus reducing its pressure on the limited healthcare resources and allowing to plan and act proactively (as opposed to reactively, like during the worst moments of the pandemic). To appropriately plan for the management and administration of resources all agents in the continuum of the healthcare provision will benefit from understanding the nature and magnitude of the outstanding unmet needs in the prevention and treatment of COVID-19. This study will provide these insights. Furthermore, the supply of EVUSHELD to address some of these needs is limited and it is expected that doses will become available in consecutive batches, which means that priorities will need to be established based on formal criteria. This study will also provide the evidence to inform those decisions.

4. It is anticipated that there will be benefits for payers (i.e., NHS and taxpayers in the UK): A thorough and evidence-based understanding of the health and economic burden of COVID-19 across different vulnerable populations enables effective planning and efficient resource allocation. Thus, the benefits described for NICE, healthcare providers, and patients may ultimately translate in cost savings or even costs being averted.

5. It is anticipated that there will be benefits for patients and the general public: Patients and the general public benefit from improved healthcare provision. By making the study results available in the public domain (see Section 5c), the general public can benefit from more accurate assessment of their risk of contracting COVID-19 and developing long-COVID-19 and make informed health decisions (e.g., taking up vaccine boosters or seek advice on eligibility for prophylaxis or treatment).

Outputs:

The initial results for this study are expected within a year following the access to the NHS Digital-linked datasets.

Evidera will be conducting all of the data processing and the analysis. They will send aggregated results that will be in the format of excel tables to AZ for review. The tables that they will send will include patient attrition cells (number of patients excluded during the patient selection process), baseline descriptive results of the study populations (i.e., number and percentage of patient demographics and clinical characteristics identified at baseline), the number and percentage of patients identified as ineligible for COVID-19 vaccine (different row will be provided for each ineligibility criteria), the number and percentage of patients at risk of COVID-19 infection (different row will be provided for each risk factor), the number of new COVID-19 infections and incidence of COVID-19 overall and in each time period of interest, the number of new long COVID-19 infections and incidence of long COVID-19, the rate of resource utilisation per patient and per-patient per COVID-19 episode. Only aggregated data with secondary suppression of cells will be send to AZ. At no point will the patient level data be transferred from Evidera to AZ. The results will also be presented in a study report and sent to AZ for review.

The planned study outputs include a study report, manuscripts in submission to peer-reviewed journals and presentations at scientific conferences. Only aggregated data with secondary suppression of cells will be presented in the planned study outputs. It is anticipated that high impact respiratory/infectious disease conferences/journals will be targeted. These include BMJ, New England Journal of Medicine, Lancet Infectious Disease and BMC Infectious Disease. Where possible, results will be published via the open access route to ensure that all clinicians, policy makers and members of the public can access the results freely. It is also anticipated that the results will be disseminated via presentations at key conferences (e.g., European Congress of Clinical Microbiology and Infectious Disease (ECCMID), International Society for Pharmacoeconomics and Outcomes Research (ISPOR)), webinars to Physicians using key AZ Medical Science staff to communicate results.

In addition, active engagement with charity organisations including the research communities (King’s College London, COVID Symptom Study Team) for topics like Long COVID is planned. AZ intend to work with Long-COVID clinics in the country to identify suitable interested patient groups to disseminate results in the form of presentation, newsletters or sharing of publication summaries. AZ will also be engaging immunocompromised patients, who are considered to not been adequately protected by COVID-19 vaccines due to their body unable to generate an optimal level of antibodies, to provide feedback on the current and future studies. Patients will provide input during study analysis planning, first results readout and publications.

PPIE
AZ will also be engaging immunocompromised patients, who are considered to not been adequately protected by COVID-19 vaccines due to their body unable to generate an optimal level of antibodies, to provide feedback on the current and future studies. Patients will provide input during study analysis planning, first results readout and publications.

Based on an assumed data delivery date in Nov 2022, Evidera estimates to complete data analysis in Jan 2023 and study report in August/September 2023. Once study report has been drafted, manuscripts will be prepared for submission to peer-reviewed journals and abstracts for conference presentation in Q3/Q4 2023.

These planned outputs will be designed with the intention of including sufficient information on methods to ensure research transparency and reproducibility. All types of results, including those sometimes seemed as unfavourable, will be published along with key code list used for case definition. The code lists refer to the SNOMED (https://termbrowser.nhs.uk/) and ICD-10 (https://icd.who.int/browse10/2019/en#/ ) diagnosis codes for identifying patients with COVID or long-COVID. The case definition refers to how cases (i.e., COVID and long COVID-19) are defined and identified from the requested datasets. The proposed study is descriptive in nature, e.g., estimating the size of populations that are not protected by COVID-19 vaccines. The incidence of COVID-19 and long COVID-19, and COVID-19-related healthcare service use, as opposed to estimating the effectiveness of certain treatments/vaccines. The aim is to understand the current health and economic burden of COVID-19. The plan is to publish results regardless of whether the estimates are high or low. With that said, given the data published on COVID dashboard (https://coronavirus.data.gov.uk/), it is unlikely to be low/unfavourable. COVID-19 research results need to and will be interpreted in the wider context, e.g., social restrictions and movement, infection rate, vaccination/booster roll-out and availability of an-viral treatments.

This study is also exploring whether machine learning based methods can help with identifying risk profiles of vaccinated patients who experienced a composite outcome of COVID-19 hospitalisation or COVID-19-related death. As previously mentioned, machine learning methods will first identify all patients that have a COVID-19 hospitalisation or COVID-19 related death after 14 days of a COVID-19 vaccination (i.e., break through infections). Then clustering methods and supervised learning with nested cross-validation will be used to classify these patients into k clusters with similar characteristics. These results, details on the development of algorithms and lessons learned are also planned to be disseminated.