Protocol for data extraction: how real-world data have been used in the National Institute for Health and Care Excellence appraisals of cancer therapy

IntroductionDue to the limitations of relying on randomised controlled trials, the potential benefits of real-world data (RWD) in enriching evidence for health technology assessment (HTA) are highlighted. Despite increased interest in RWD, there is limited systematic research investigating how RWD have been used in HTA. The main purpose of this protocol is to extract relevant data from National Institute for Health and Care Excellence (NICE) appraisals in a transparent and reproducible manner in order to determine how NICE has incorporated a broader range of evidence in the appraisal of oncology medicines.Methods and analysisThe appraisals issued between January 2011 and May 2021 are included following inclusion criteria. The data extraction tool newly developed for this research includes the critical components of economic evaluation. The information is extracted from identified appraisals in accordance with extraction rules. The data extraction tool will be validated by a second researcher independently. The extracted data will be analysed quantitatively to investigate to what extent RWD have been used in appraisals. This is the first protocol to enable data to be extracted comprehensively and systematically in order to review the use of RWD.Ethics and disseminationThis study is approved by the Ethics Committee of the London School of Hygiene and Tropical Medicine on 14 November 2019 (17315). Results will be published in peer-reviewed journals.

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The Value of Real-World Data in Understanding Prostate Cancer Risk and Improving Clinical Care: Examples from Swedish Registries

Cancers ◽

10.3390/cancers13040875 ◽

2021 ◽

Vol 13 (4) ◽

pp. 875

Author(s):

Kerri Beckmann ◽

Hans Garmo ◽

Ingela Franck Lissbrant ◽

Pär Stattin

Keyword(s):

Prostate Cancer ◽

Real World ◽

Clinical Care ◽

Prostate Cancer Risk ◽

Real World Data ◽

Level Of Evidence ◽

World Data ◽

Cancer Data ◽

Using Data ◽

Randomised Controlled

Real-world data (RWD), that is, data from sources other than controlled clinical trials, play an increasingly important role in medical research. The development of quality clinical registers, increasing access to administrative data sources, growing computing power and data linkage capacities have contributed to greater availability of RWD. Evidence derived from RWD increases our understanding of prostate cancer (PCa) aetiology, natural history and effective management. While randomised controlled trials offer the best level of evidence for establishing the efficacy of medical interventions and making causal inferences, studies using RWD offer complementary evidence about the effectiveness, long-term outcomes and safety of interventions in real-world settings. RWD provide the only means of addressing questions about risk factors and exposures that cannot be “controlled”, or when assessing rare outcomes. This review provides examples of the value of RWD for generating evidence about PCa, focusing on studies using data from a quality clinical register, namely the National Prostate Cancer Register (NPCR) Sweden, with longitudinal data on advanced PCa in Patient-overview Prostate Cancer (PPC) and data linkages to other sources in Prostate Cancer data Base Sweden (PCBaSe).

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Blockchain-Authenticated Sharing of Genomic and Clinical Outcomes Data of Patients With Cancer: A Prospective Cohort Study

Journal of Medical Internet Research ◽

10.2196/16810 ◽

2020 ◽

Vol 22 (3) ◽

pp. e16810 ◽

Cited By ~ 3

Author(s):

Benjamin Scott Glicksberg ◽

Shohei Burns ◽

Rob Currie ◽

Ann Griffin ◽

Zhen Jane Wang ◽

...

Keyword(s):

Real World ◽

Web Application ◽

Data Extraction ◽

Data Representation ◽

Health Data ◽

Common Data Model ◽

Patient Privacy ◽

Real World Data ◽

World Data ◽

Patients With Cancer

Background Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. Objective The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. Methods We created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). Results Although the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. Conclusions Our pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.

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A systematic review of ICD complications in randomised controlled trials versus registries: is our ‘real-world’ data an underestimation?

Open Heart ◽

10.1136/openhrt-2014-000198 ◽

2015 ◽

Vol 2 (1) ◽

pp. e000198 ◽

Cited By ~ 64

Author(s):

Vivienne A Ezzat ◽

Victor Lee ◽

Syed Ahsan ◽

Anthony W Chow ◽

Oliver Segal ◽

...

Keyword(s):

Systematic Review ◽

Real World ◽

Randomised Controlled Trials ◽

Controlled Trials ◽

Real World Data ◽

World Data ◽

Randomised Controlled

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PMU68 Emulating the Main Outcomes of Randomised Controlled Studies through Statistical Analysis of Real World Data Directly Extracted from Electronic Medical Records.

Value in Health ◽

10.1016/j.jval.2021.04.780 ◽

2021 ◽

Vol 24 ◽

pp. S157

Author(s):

D. Drake ◽

Wouwe L Van ◽

Rhali A El ◽

R. Abdi ◽

M. Kouki

Keyword(s):

Statistical Analysis ◽

Electronic Medical Records ◽

Real World ◽

Medical Records ◽

Real World Data ◽

World Data ◽

Randomised Controlled

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What happens after randomised controlled trials? Uterine fibroids and ulipristal acetate: systematic review and meta-analysis of "real-world" data

Archives of Gynecology and Obstetrics ◽

10.1007/s00404-020-05918-3 ◽

2021 ◽

Author(s):

Neha Shah ◽

Elizabeth Egbase ◽

Michael Sideris ◽

Funlayo Odejinmi

Keyword(s):

Systematic Review ◽

Real World ◽

Randomised Controlled Trials ◽

Meta Analysis ◽

Uterine Fibroids ◽

Controlled Trials ◽

Real World Data ◽

Ulipristal Acetate ◽

World Data ◽

Randomised Controlled

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Blockchain-Authenticated Sharing of Genomic and Clinical Outcomes Data of Patients With Cancer: A Prospective Cohort Study (Preprint)

10.2196/preprints.16810 ◽

2019 ◽

Author(s):

Benjamin Scott Glicksberg ◽

Shohei Burns ◽

Rob Currie ◽

Ann Griffin ◽

Zhen Jane Wang ◽

...

Keyword(s):

Real World ◽

Web Application ◽

Data Extraction ◽

Data Representation ◽

Health Data ◽

Common Data Model ◽

Patient Privacy ◽

Real World Data ◽

World Data ◽

Patients With Cancer

BACKGROUND Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. OBJECTIVE The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. METHODS We created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). RESULTS Although the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. CONCLUSIONS Our pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.

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Real-World Data and Randomised Controlled Trials: The Salford Lung Study

Advances in Therapy ◽

10.1007/s12325-019-01192-1 ◽

2020 ◽

Vol 37 (3) ◽

pp. 977-997

Author(s):

David A. Leather ◽

Rupert Jones ◽

Ashley Woodcock ◽

Jørgen Vestbo ◽

Loretta Jacques ◽

...

Keyword(s):

Real World ◽

Randomised Controlled Trials ◽

Controlled Trials ◽

Real World Data ◽

World Data ◽

Randomised Controlled

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Contextualising Single-Arm Ophthalmology Trials With Real-World Data: An Emulated Target Trial Comparing The Efficacy Of Interventions For Neovascular Age-Related Macular Degeneration

10.1101/2020.08.10.20171538 ◽

2020 ◽

Author(s):

Darren S Thomas ◽

Aaron Y. Lee ◽

Philipp L. Muller ◽

Roy Schwartz ◽

Abraham Olvera-Barrios ◽

...

Keyword(s):

Visual Acuity ◽

Macular Degeneration ◽

Real World ◽

Age Related Macular Degeneration ◽

Target Trial ◽

Real World Data ◽

World Data ◽

Off Label ◽

Age Related ◽

Randomised Controlled

Methods of causal inference have shown promise in replicating randomised trials using real-world data recorded by Electronic Health Records (EHRs). We herein emulated a target trial on the intention-to-treat efficacy of off-label bevacizumab (q6w) pro re nata relative to fixed-interval aflibercept (q8w) for improving week-54 visual acuity of eyes affected by neovascular age-related macular degeneration. The bevacizumab arm (n 65) was taken from the ABC randomised controlled trial. A total of 4,471 aflibercept-treated eyes aligning with the ABC trial eligibility were identified from EHRs and synthetic control arms were created by emulating randomisation conditional on age, sex, and baseline visual read via exact matching and propensity score methods. We undertook an inferiority analysis on mean difference at 54 weeks; outcomes regression on achieving a change in visual acuity of ≥ 15, ≥ 10, and ≤ -15 Early Treatment Diabetic Retinopathy Letters (ETDRS) letters at week 54; and a time-to-event analysis on achieving a change in visual acuity of ≥ 15, ≥ 10, and ≤ -15 ETDRS letters by week 54. Our findings suggest off-label bevacizumab to be neither non-inferior nor superior to licensed aflibercept. While being no substitute for randomised controlled trials, emulated target trials could aid the interpretation of single-armed trials.

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